A Research Preview of Codex(openai.com)
openai.com
A Research Preview of Codex
https://openai.com/index/introducing-codex/
486 comments
It looks we are in this interesting cycle: millions of engineers contribute to open-source on github. The best of our minds use the code to develop powerful models to replace exactly these engineers. In fact, the more code a group contributes to github, the easier it is for the companies to replace this group. Case in point, frontend engineers are impacted most so far.
Does this mean people will be less incentivized to contribute to open source as time goes by?
P.S., I think the current trend is a wakeup call to us software engineers. We thought we were doing highly creative work, but in reality we spend a lot of time doing the basic job of knowledge workers: retrieving knowledge and interpolating some basic and highly predictable variations. Unfortunately, the current AI is really good at replacing this type of work.
My optimistic view is that in long term we will have invent or expand into more interesting work, but I'm not sure how long we will have to wait. The current generation of software engineers may suffer high supply but low demand of our profession for years to come.
Does this mean people will be less incentivized to contribute to open source as time goes by?
P.S., I think the current trend is a wakeup call to us software engineers. We thought we were doing highly creative work, but in reality we spend a lot of time doing the basic job of knowledge workers: retrieving knowledge and interpolating some basic and highly predictable variations. Unfortunately, the current AI is really good at replacing this type of work.
My optimistic view is that in long term we will have invent or expand into more interesting work, but I'm not sure how long we will have to wait. The current generation of software engineers may suffer high supply but low demand of our profession for years to come.
As much as I support community developed software and "free as in freedom", "Open Source" got completely perverted into tricking people to work for free for huge financial benefits for others. Your comment is just one example of that.
For that reason all my silly little side projects are now in private repos. I dont care the chance somebody builds a business around them is slim to none. Dont think putting a license will protect you either. You'd have to know somebody is violating your license before you can even think about doing anything and that's basically impossible if it gets ripped into a private codebase and isnt obvious externally.
For that reason all my silly little side projects are now in private repos. I dont care the chance somebody builds a business around them is slim to none. Dont think putting a license will protect you either. You'd have to know somebody is violating your license before you can even think about doing anything and that's basically impossible if it gets ripped into a private codebase and isnt obvious externally.
Protect you from what?
What harm is there to you if someone uses some of your code to build a business, as compared to not doing so? How are you worse off?
I’ve never understood this mentality. It seems very zero sum and kind of anti social. I’ve built a couple of businesses, and there’s always economic or technical precedent. I honestly don’t mind paying it forward if someone can benefit from side projects I enjoyed doing anyways.
What harm is there to you if someone uses some of your code to build a business, as compared to not doing so? How are you worse off?
I’ve never understood this mentality. It seems very zero sum and kind of anti social. I’ve built a couple of businesses, and there’s always economic or technical precedent. I honestly don’t mind paying it forward if someone can benefit from side projects I enjoyed doing anyways.
You have a right to the work you author. If you are selling your work or your services, then you have to protect your product - yourself.
If you decide to put open source out there for others to use, then sure. You chose to allow that.
If you didn't license it for that, then it shouldn't be in an LLM.
If you decide to put open source out there for others to use, then sure. You chose to allow that.
If you didn't license it for that, then it shouldn't be in an LLM.
And much as people joke about "exposure" not putting food on the table, being able to walk into a job interview with your name known because the company is already using your code/project is huge.
Exactly. If you are not actively going to compete in that space why not let someone else compete instead using your work?
If that someone then takes that work that you're providing for free to other people to build on it, makes a closed source product out of it and gives you no attribution, then you can be darn well sure I want to protect it.
> What harm is there to you if someone uses some of your code to build a business, as compared to not doing so? How are you worse off?
This someone might be someone I dislike. It would cause me some mild annoyance that they benefited from my effort.
This someone might be someone I dislike. It would cause me some mild annoyance that they benefited from my effort.
It’s not healthy to let hypothetical spite guide your participation in civilization.
It's also not healthy to sip on whiskey or smoke some tobacco, but I do both on occasion.
Spite is also pretty pleasurable.
Spite is also pretty pleasurable.
So let's say your side project improves your life by 5 happiness points. You have two options:
--- OPTION A - Keep your project private.
• You get five happiness points.
--- OPTION B - Make your project public.
• Other individuals may get a small number of happiness points.
• A megacorp might turn your project into a major product without compensating you and get a million happiness points.
• You get five happiness points.
----------
In either scenario, you still end up with five happiness points. If you release your code, other people may get even more happiness points than you, which isn't really fair. But you are no worse off, and you've increased humanity's total wealth of happiness points.
--- OPTION A - Keep your project private.
• You get five happiness points.
--- OPTION B - Make your project public.
• Other individuals may get a small number of happiness points.
• A megacorp might turn your project into a major product without compensating you and get a million happiness points.
• You get five happiness points.
----------
In either scenario, you still end up with five happiness points. If you release your code, other people may get even more happiness points than you, which isn't really fair. But you are no worse off, and you've increased humanity's total wealth of happiness points.
You really dont see why somebody wouldnt like a megacorp to take their hard work, use it to make a billion dollars, dont see a cent themselves, while struggling to buy a house in this very unaffordable housing market?
https://knowyourmeme.com/memes/total-happiness-in-the-world-...
https://knowyourmeme.com/memes/total-happiness-in-the-world-...
Google, Microsoft, Meta, IBM, Red Hat, etc. are huge players in open source, they probably contribute significantly more hours of work in building and maintaining major open source projects than the hobbyists.
Not that hobbyists don't contribute, but these models are certainly being trained on the work of salaried engineers as much as their trained on hobbyists' spare time projects.
Not that hobbyists don't contribute, but these models are certainly being trained on the work of salaried engineers as much as their trained on hobbyists' spare time projects.
Yea those companies do...but you know what? Those engineers working there contributing that code are getting paid to do so.
This assumes that none of the effects of making a project public or private have any impact on the output of your personal utility function, which may be true for you personally, but certainly cannot validly be assumed to be generally true.
> "Open Source" got completely perverted into tricking people to work for free for huge financial benefits for others
I'm quite conflicted on this assessment. On one hand, I was wondering if we would get better job market if there were not much open-sourced systems. We may have had a much slower growth, but we would see our growth last for a lot more years, which mean we may enjoy our profession until our retirement and more. On the other hand, open source did create large cakes, right? Like the "big data" market, the ML market, the distributed system market, and etc. Like the millions of data scientists who could barely use Pandas and scipy, or hundreds of thousands of ML engineers who couldn't even bother to know what semi positive definite matrix is.
Interesting times.
I'm quite conflicted on this assessment. On one hand, I was wondering if we would get better job market if there were not much open-sourced systems. We may have had a much slower growth, but we would see our growth last for a lot more years, which mean we may enjoy our profession until our retirement and more. On the other hand, open source did create large cakes, right? Like the "big data" market, the ML market, the distributed system market, and etc. Like the millions of data scientists who could barely use Pandas and scipy, or hundreds of thousands of ML engineers who couldn't even bother to know what semi positive definite matrix is.
Interesting times.
> P.S., I think the current trend is a wakeup call to us software engineers. We thought we were doing highly creative work, but in reality we spend a lot of time doing the basic job of knowledge workers: retrieving knowledge and interpolating some basic and highly predictable variations. Unfortunately, the current AI is really good at replacing this type of work.
Most of the waking hours of most creative work have this type of drudgery. Professional painters and designers spend most of their time replicating ideas that are well fleshed-out. Musicians spend most of their time rehearsing existing compositions.
There is a point to be made that these repetitive tasks are a prerequisite to come up with creative ideas.
Most of the waking hours of most creative work have this type of drudgery. Professional painters and designers spend most of their time replicating ideas that are well fleshed-out. Musicians spend most of their time rehearsing existing compositions.
There is a point to be made that these repetitive tasks are a prerequisite to come up with creative ideas.
I disagree. AI have shown to most capable in what we consider creative jobs. Music creation, voice acting, text/story writing, art creation, video creation and more.
> AI have shown to most capable in what we consider creative jobs
no it creates shit thats close enough for people who are in a rush and dont care.
ie, you need artwork for shit on temu, boom job done.
You want to make a poster for a bake sale, boom job done.
Need some free music that sounds close enough to be swifty, but not enough to get sued, great.
But as an expression of creativity, most people cant get it to do that.
Its currently slightly more configurable clipart.
no it creates shit thats close enough for people who are in a rush and dont care.
ie, you need artwork for shit on temu, boom job done.
You want to make a poster for a bake sale, boom job done.
Need some free music that sounds close enough to be swifty, but not enough to get sued, great.
But as an expression of creativity, most people cant get it to do that.
Its currently slightly more configurable clipart.
Serious deja vu to the late 70’s and early 80’s when “real musicians” said exactly the same thing about synthesizers and drum machines.
The difference, of course, being that synthesizers and drum machines are instruments that require actual skill and talent and can be used to express the unique musical style of an artist, whereas AI requires neither skill nor talent, and it cannot generate anything with actual artistic direction, intent or innovation, much less a unique creative style.
AI is never going to give the world a modern Kraftwerk or Silver Apples or Brian Eno. The best an AI "artist" can do is have the machine mimic them.
AI is never going to give the world a modern Kraftwerk or Silver Apples or Brian Eno. The best an AI "artist" can do is have the machine mimic them.
Still the same thing. The argument then was that synths weren’t “real instruments” and that sequencers meant people weren’t “real musicians”.
AI relies on prompting. In the hands of a skilled artist it is just another tool. In the hands of an amateur hack, it is no different than giving a drum kit to a 4 year old.
The tool is not the art. It never was.
AI relies on prompting. In the hands of a skilled artist it is just another tool. In the hands of an amateur hack, it is no different than giving a drum kit to a 4 year old.
The tool is not the art. It never was.
They were right in many cases. You can choose to pick out the small percentage of musicians who were successful there or you can recognize the many that were never known.
You can do the same for photography.
People keep lowering expectations or demands on quality because things get easier and humans always prefer the easy option.
You can do the same for photography.
People keep lowering expectations or demands on quality because things get easier and humans always prefer the easy option.
Look, in the hands of a skilled artist, generative fill is really useful.
In the same way that the synth is superstitious is banging.
Sampling, when in the hands of a legend is also spectacular, see the prodigy and a break down of the samples they used. (or any half decent hiphop band)
Then you get akon who just sped up a single sample put a beat on it and shat out some halfarsed shit.
In the same way that the synth is superstitious is banging.
Sampling, when in the hands of a legend is also spectacular, see the prodigy and a break down of the samples they used. (or any half decent hiphop band)
Then you get akon who just sped up a single sample put a beat on it and shat out some halfarsed shit.
Those are instruments played and sequenced by humans. Meaningless comparison.
> AI creates novel algorithms beating thousands of googlers.
Random HNer on an AI post one day later
> Its currently slightly more configurable clipart.
It's so ridiculous at this point that I can just laugh about this.
Random HNer on an AI post one day later
> Its currently slightly more configurable clipart.
It's so ridiculous at this point that I can just laugh about this.
[deleted]
Two people from different backgrounds have differing opinions on different systems.
This just in, the response was also to an entirely different context.
> rowanG077: Holy shit look how different the opinions are! LOL HN is so wild.
This just in, the response was also to an entirely different context.
> rowanG077: Holy shit look how different the opinions are! LOL HN is so wild.
Comparing music and algorithms is nonsense.
AI music is disposable generic soulless trash, even if it is technically correct, in accordance with the rules and conventions of music theory. AI generates Muzak. Totally generic and derivative.
There is no AI equivalent to Kurt Cobain, or James Brown, or Tori Amos.
AI music is disposable generic soulless trash, even if it is technically correct, in accordance with the rules and conventions of music theory. AI generates Muzak. Totally generic and derivative.
There is no AI equivalent to Kurt Cobain, or James Brown, or Tori Amos.
There is no AI equivalent to Kurt Cobain or any other artists because 99% of what they are is not at all about their musical skill but all about marketing. There are thousands of musicians just as skilled if not more than Kurt Cobain or James Brown yet who don't have their fame. I also have no doubt an AI will outperform most musicians in short order in the foreseeable future. The step from making no music at all, to making acceptable music is gigantic compared to making acceptable music to making great music.
[deleted]
If you mean create as in literally, sure. But not in being creative. AI can't solve novel problems yet. The person you're replying to obviously means being creative not literally creating something.
You can't say AI is creating something new but that it isn't being creative with clearly explaining why you think that's the case. AI is creating novel solution to problems humans haven't cracked in centuries. I don't see anything more creative than this.
> AI is creating novel solution to problems humans haven't cracked in centuries
Really?
Really?
Yes, really. Just yesterday google announced their AI was able to improve on human SotA algorithms in 25% of the cases fed into it. One of them was 4x4 complex matrix multiply. Which had pretty huge pressure to be improved.
I'm skeptical. I wouldn't call brute-force creating, not really. And Google obviously has an interest in promoting AI.
Not to say it's not impressive and good.
Not to say it's not impressive and good.
What is the qualifier for this? Didn't one of the models recently create a "novel" algorithm for a math problem? I'm not sure this holds water anymore.
"After a couple of million suggestions and a few dozen repetitions of the overall process"
How much of it is brute force?
How much of it is brute force?
Are we maybe moving the goalposts here? How much of human creativity is brute force?
> Does this mean people will be less incentivized to contribute to open source as time goes by?
personally, I completely stopped 2 years ago
it's the same as the stack overflow problem: the incentive to contribute tends towards zero, at which point the plagiarism machine stops improving
personally, I completely stopped 2 years ago
it's the same as the stack overflow problem: the incentive to contribute tends towards zero, at which point the plagiarism machine stops improving
Same. It'll be interesting to see when open source slows down enough and is maybe all but eliminated...how will things advance?
Once everyone uses AI. How will anything new come about?
AI could quite possibly slow down innovation and improvement.
Once everyone uses AI. How will anything new come about?
AI could quite possibly slow down innovation and improvement.
Now do open science.
More generally, specialty knowledge is valuable. From now on, all employees will be monitored in order to replace them.
More generally, specialty knowledge is valuable. From now on, all employees will be monitored in order to replace them.
> From now on, all employees will be monitored in order to replace them.
This is going on a t-shirt.
This is going on a t-shirt.
My pessimistic view is that we're liable to end up cutting off the pipeline into the industry. Similar to lawyers replacing clerks with bots, if senior engineers can now command bots rather than mentor new hires, where is the on-ramp? How does one actually gain enough experience to become a senior?
Or is all this a nothing-burger, since the new hires will just be commanding bots of their own, but on lower level tasks that they are qualified to supervise?
Or is all this a nothing-burger, since the new hires will just be commanding bots of their own, but on lower level tasks that they are qualified to supervise?
> Does this mean people will be less incentivized to contribute to open source as time goes by?
Yes. I certainly don't intend to put any free code online until I can legally bar AI bros from using it without payment. As Mike Monteiro put it long ago, "F** you, pay me" (https://www.youtube.com/watch?v=jVkLVRt6c1U)
Yes. I certainly don't intend to put any free code online until I can legally bar AI bros from using it without payment. As Mike Monteiro put it long ago, "F** you, pay me" (https://www.youtube.com/watch?v=jVkLVRt6c1U)
People might also lace open source with Trojans and back doors. It's going to get interesting.
> doing the basic job of knowledge workers
If you extrapolate and generalize further... what is at risk is any task that involves taking information input (text, audio, images, video, etc.), and applying it to create some information output or perform some action which is useful.
That's basically the definition of work. It's not just knowledge work, it's literally any work.
If you extrapolate and generalize further... what is at risk is any task that involves taking information input (text, audio, images, video, etc.), and applying it to create some information output or perform some action which is useful.
That's basically the definition of work. It's not just knowledge work, it's literally any work.
> Parallel task execution: You can batch dozens of small edits (refactors, tests, boilerplate) and run them concurrently without context juggling. It's super nice to run a bunch of tasks at the same time (something that's really hard to do in Cursor, Cline, etc.)
> It kind of feels like a junior engineer on steroids, you just need to point it at a file or function, specify the change, and it scaffolds out most of a PR. You still need to do a lot of work to get it production ready, but it's as if you have an infinite number of junior engineers at your disposal now all working on different things.
What's the benefit of this? It sounds like it's just a gimmick for the "AI will replace programmers" headlines. In reality, LLMs complete their tasks within seconds, and the time consuming part is specifying the tasks and then reviewing and correcting them. What is the point of parallelizing the fastest part of the process?
> It kind of feels like a junior engineer on steroids, you just need to point it at a file or function, specify the change, and it scaffolds out most of a PR. You still need to do a lot of work to get it production ready, but it's as if you have an infinite number of junior engineers at your disposal now all working on different things.
What's the benefit of this? It sounds like it's just a gimmick for the "AI will replace programmers" headlines. In reality, LLMs complete their tasks within seconds, and the time consuming part is specifying the tasks and then reviewing and correcting them. What is the point of parallelizing the fastest part of the process?
In my experience, it still does take quite a bit of time (minutes) to run a task on these agentic LLMs (especially with the latest reasoning models), and in Cursor / Cline / other code editor versions of AI, it's enough time for you to get distracted, lose context, and start working on another task.
So the benefit is really that during this "down" time, you can do multiple useful things in parallel. Previously, our engineers were waiting on the Cursor agent to finish, but the parallelization means you're explicitly turning your brain off of one task and moving on to a different task.
So the benefit is really that during this "down" time, you can do multiple useful things in parallel. Previously, our engineers were waiting on the Cursor agent to finish, but the parallelization means you're explicitly turning your brain off of one task and moving on to a different task.
In my experience in Cursor with Claude 3.5 and Gemini 2.5, if an agent has run for more than a minute it has usually lost the plot. Maybe model use in Codex is a new breed?
It depends what level you ask them to work on, but I agree, all of my agent coding is active and completed in usually <15 seconds.
with cline you can give it a huge action plan and it will grind away until it's done. with all the context shenanigans that cursor and copilot do, it can't handle multiple tasks as well. then they are farming requests from the user so they make you click to continue all the time.
Just tried Cline and it lost the plot and ground away $5
This is the thing people need to be most aware of with all of these tools. I like how Roo Code shows you the costs.
It's going to take a while before companies catch up here and realize the "hidden costs" of AI. In a few years I think the narrative will shift to how efficient one is at using AI.
I can only imagine someone somewhere wanted to know "how much does it cost for a line of code?" And for decades no one could answer this. Frustrated with this, the neanderthal business man now turns to AI and is in ignorant bliss with the new found fire about to burn down his house.
It's going to take a while before companies catch up here and realize the "hidden costs" of AI. In a few years I think the narrative will shift to how efficient one is at using AI.
I can only imagine someone somewhere wanted to know "how much does it cost for a line of code?" And for decades no one could answer this. Frustrated with this, the neanderthal business man now turns to AI and is in ignorant bliss with the new found fire about to burn down his house.
A single response can take a few seconds, but tasks with agentic flows can be dozens of back and forths. I've had a fairly complicated Roo Code task take 10 minutes (multiple subtasks).
How much of it did you read? Haha. That's not anything against you, I'm just pointing out to people that there will be a bunch of folks out there who will never care to read and learn. They just want to mash all the buttons until it works.
When I was a kid, that worked with Nintendo games sure...but I like to think I've matured beyond that...but I haven't read every little thing returned by the LLM in Roo Code myself, so maybe it's human nature.
When I was a kid, that worked with Nintendo games sure...but I like to think I've matured beyond that...but I haven't read every little thing returned by the LLM in Roo Code myself, so maybe it's human nature.
> Each task is processed independently in a separate, isolated environment preloaded with your codebase. Codex can read and edit files, as well as run commands including test harnesses, linters, and type checkers. Task completion typically takes between 1 and 30 minutes, depending on complexity, and you can monitor Codex’s progress in real time.
> You still need to do a lot of work to get it production ready, but it's as if you have an infinite number of junior engineers at your disposal now all working on different things.
One issue with junior devs is that because they’re not fully autonomous, you have to spend a non trivial amount of time guiding them and reviewing their code. Even if I had easy access to a lot of them, pretty quickly that overhead would become the bottleneck.
Did you think that managing a lot of these virtual devs could get overwhelming or are they pretty autonomous?
One issue with junior devs is that because they’re not fully autonomous, you have to spend a non trivial amount of time guiding them and reviewing their code. Even if I had easy access to a lot of them, pretty quickly that overhead would become the bottleneck.
Did you think that managing a lot of these virtual devs could get overwhelming or are they pretty autonomous?
They wrote "You still need to do a lot of work to get it production ready". So I would say it's not much better than real colleagues. Especially since junior devs will improve to a point they don't need your hand holding (remember you also were a junior at some point), which is not proven will happen with AI tools.
Counter-point A: AI coding assistance tools are rapidly advancing at a clip that is inarguably faster than humans.
Counter-point B: AI does not get tired, does not need space, does not need catering to their experience. AI is fine being interrupted and redirected. AI is fine spending two days on something that gets overwritten and thrown away (no morale loss).
Counter-point B: AI does not get tired, does not need space, does not need catering to their experience. AI is fine being interrupted and redirected. AI is fine spending two days on something that gets overwritten and thrown away (no morale loss).
Counter-counter-point A: If I work with a human Junior and they make an error or I familiarize them with any quirk of our workflow, and I correct them, they will recall that correction moving forward. An AI assistant either will not remember 5 minutes later (in a different prompt on a related project) and repeat the mistake, or I'll have to take the extra time to code some reminder into the system prompt for every project moving forward.
Advancements in general AI knowledge over time will not correlate to improvements in remembering any matters as colloquial as this.
Counter-counter-point B: AI absolutely needs catering to their experience. Prompter must always learn how to phrase things so that the AI will understand them, adjust things when they get stuck in loops by removing confusing elements from the prompt, etc.
Advancements in general AI knowledge over time will not correlate to improvements in remembering any matters as colloquial as this.
Counter-counter-point B: AI absolutely needs catering to their experience. Prompter must always learn how to phrase things so that the AI will understand them, adjust things when they get stuck in loops by removing confusing elements from the prompt, etc.
I find myself thinking about juniors vs AI as babies vs cats. A cat is more capable sooner, you can trust it when you leave the house for two hours, but it'll never grow past shitting in a box and needing to be fed.
> If I work with a human Junior and they make an error or I familiarize them with any quirk of our workflow, and I correct them, they will recall that correction moving forward
I really wish that were the case. Most of the Jr Engineers I work with have to be told the same thing multiple times, in different ways, for things to stick.
I really wish that were the case. Most of the Jr Engineers I work with have to be told the same thing multiple times, in different ways, for things to stick.
most of the coding agents now encourage you to make a rule for those times so it does remember.
There's going to be a limit though. Plus you have to instruct them correctly.
B. Yea, that's true. I used to have over 4,000 GitHub contributions a year and it dropped to 1,000 as I got older and managed people. I used to be able to work 48 hrs straight but can't as much anymore...but you still have to be there to instruct the AI agent. It can't do it all on its own.
B. Yea, that's true. I used to have over 4,000 GitHub contributions a year and it dropped to 1,000 as I got older and managed people. I used to be able to work 48 hrs straight but can't as much anymore...but you still have to be there to instruct the AI agent. It can't do it all on its own.
You also have to provide accurate instructions.
I find most often times, "bugs" aren't with writing code that doesn't compile or doesn't have passing tests. The "bugs" come from not understanding the requirements and what it is you're building.
I'm not entirely sure AI will help this at all. People are generally bad at describing software and how they want it to work. They are inaccurate there or entirely omit things in the requirements.
Yes, though, it would be overwhelming to manage a bunch of AI agents. Context switching and redirecting, guiding, will be very difficult and not everyone's cup of tea.
If argue this isn't really a result of AI though. Many people are already in this boat today. The industry is set up in this way with contractors and outsourced devs that are at a junior level...because it's the attraction of cheap labor. Many businesses are attracted to this beyond programming. One of the questions is going to be, is the cost per token economics cheaper? So long as it's cheaper, AI coding agents will have a future. If it proves to not be cheaper (and this could take years to prove out), then I don't think it'll be as popular. I think people will need to go back to the drawing board on how we use AI agents or use AI for other purposes (like training, education, developer onboarding, code reviews, debugging, etc.)
I find most often times, "bugs" aren't with writing code that doesn't compile or doesn't have passing tests. The "bugs" come from not understanding the requirements and what it is you're building.
I'm not entirely sure AI will help this at all. People are generally bad at describing software and how they want it to work. They are inaccurate there or entirely omit things in the requirements.
Yes, though, it would be overwhelming to manage a bunch of AI agents. Context switching and redirecting, guiding, will be very difficult and not everyone's cup of tea.
If argue this isn't really a result of AI though. Many people are already in this boat today. The industry is set up in this way with contractors and outsourced devs that are at a junior level...because it's the attraction of cheap labor. Many businesses are attracted to this beyond programming. One of the questions is going to be, is the cost per token economics cheaper? So long as it's cheaper, AI coding agents will have a future. If it proves to not be cheaper (and this could take years to prove out), then I don't think it'll be as popular. I think people will need to go back to the drawing board on how we use AI agents or use AI for other purposes (like training, education, developer onboarding, code reviews, debugging, etc.)
You don't need to be nice to your virtual junior devs. Saves quite a lot time too.
As long as I spend less time reviewing and guiding than doing it myself it's a win for me. I don't have any fun doing these things and I'd rather yelling at a bunch of "agents". For those who enjoy doing bunch of small edits I guess it's the opposite.
As long as I spend less time reviewing and guiding than doing it myself it's a win for me. I don't have any fun doing these things and I'd rather yelling at a bunch of "agents". For those who enjoy doing bunch of small edits I guess it's the opposite.
I'm definitely wary of the concept of dismissing courtesy when working with AI agents, because I certainly don't want to lose that habit when I turn around and have to interact with humans again.
Exactly. Courtesy and kindness are largely for the benefit of the giver. People who think “now I’m free to be the jerk I really am” worry me.
There's a very large gap between being super nice to a human and being a jerk.
I don't think it benefits me much by very politely suggesting that its approach may not work and emphasize on the good part of the idea it generates and it would be better if it could try to push in another direction for example X. Like I do when talking to junior engineers.
I usually just say, "This does not work because of ..., Y is good though, change your mind and assess X now". I can also say this when I'm not actually sure whether X works or not, without worrying about my words sending an intern / a junior engineer into days of struggling on a deadend.
I don't think it benefits me much by very politely suggesting that its approach may not work and emphasize on the good part of the idea it generates and it would be better if it could try to push in another direction for example X. Like I do when talking to junior engineers.
I usually just say, "This does not work because of ..., Y is good though, change your mind and assess X now". I can also say this when I'm not actually sure whether X works or not, without worrying about my words sending an intern / a junior engineer into days of struggling on a deadend.
Relevent SMBC https://www.smbc-comics.com/comic/ai-15
CTO of an AI agents company (which has worked with AI labs) says agents works fine. Nothing new under the sun.
> We’ve long used local agents like Cursor and Claude Code, so we didn’t expect too much.
If you don't mind, what were the strengths and limitations of Claude Code compared to Codex? You mentioned parallel task execution being a standout feature for Codex - was this a particular pain point with Claude Code? Any other insights on how Claude Code performed for your team would be valuable. We are pleased with Claude Code at the moment and were a bit underwhelmed by comparable Codex CLI tool OAI released earlier this month.
If you don't mind, what were the strengths and limitations of Claude Code compared to Codex? You mentioned parallel task execution being a standout feature for Codex - was this a particular pain point with Claude Code? Any other insights on how Claude Code performed for your team would be valuable. We are pleased with Claude Code at the moment and were a bit underwhelmed by comparable Codex CLI tool OAI released earlier this month.
Post realizing CC can operate same code base, same file tree on different terminals instances, it's been a significant unlock for us. Most devs have 3 running concurrently. 1. master task list + checks for completion on tasks. 2. operating on current task + documentation. 3. side quests, bugs, additional context.
rinse and repeat once task done, update #1 and cycle again. Add in another CC window if need more tasks concurrently.
downside is cost but if not an issue, it's great for getting stuff done across distributed teams..
rinse and repeat once task done, update #1 and cycle again. Add in another CC window if need more tasks concurrently.
downside is cost but if not an issue, it's great for getting stuff done across distributed teams..
do you have then instance 2 and 3 listening to instance 1 with just a prompt? or how does this work?
to answer my own questions , it is actually laid out in chapter 6 of https://www.anthropic.com/engineering/claude-code-best-pract...
The advantage of Cursor is the reduced feedback loop where you watch it live and can intervene at any moment to steer it in the right direction. Is Codex such a superior model that it makes sense to take the direction of a mostly background agent, on which you seemingly have a longer feedback loop?
it sounds like their approach is launch 5 with the same task and hopefully one works it out.
I believe cursor now supports parallel tasks, no? I haven't done much with it personally but I have buddies who have.
If you want one idiot's perspective, please hyper-focus on model quality. The barrier right now is not tooling, it's the fact that models are not good enough for a large amount of work. More importantly, they're still closer to interns than junior devs: you must give them a ton of guidance, constant feedback, and a very stern eye for them to do even pretty simple tasks.
I'd like to see something with an o1-preview/pro level of quality that isn't insanely expensive, particularly since a lot of programming isn't about syntax (which most SotA modls have down pat) but about understanding the underlying concepts, an area in which they remain weak.
Atp I really don't care if the tooling sucks. Just give me really, really good mdoels that don't cost a kidney.
If you want one idiot's perspective, please hyper-focus on model quality. The barrier right now is not tooling, it's the fact that models are not good enough for a large amount of work. More importantly, they're still closer to interns than junior devs: you must give them a ton of guidance, constant feedback, and a very stern eye for them to do even pretty simple tasks.
I'd like to see something with an o1-preview/pro level of quality that isn't insanely expensive, particularly since a lot of programming isn't about syntax (which most SotA modls have down pat) but about understanding the underlying concepts, an area in which they remain weak.
Atp I really don't care if the tooling sucks. Just give me really, really good mdoels that don't cost a kidney.
> Parallel task execution: You can batch dozens of small edits (refactors, tests, boilerplate) and run them concurrently without context juggling.
This is also part of a recent update to Zed. I typically use Zed with my own Claude API key.
This is also part of a recent update to Zed. I typically use Zed with my own Claude API key.
Is Zed managing the containerized dev environments, or creating multiple worktrees or anything like that? Or are they all sharing the same work tree?
As far as I know, they are sharing a single work tree. So I suppose that could get messy by default.
That said, it might be possible to tell each agent to create a branch and do work there? I haven't tried that.
I haven't seen anything about Zed using containers, but again you might be able to tell each agent to use some container tooling you have in place since it can run commands if you give it permission.
That said, it might be possible to tell each agent to create a branch and do work there? I haven't tried that.
I haven't seen anything about Zed using containers, but again you might be able to tell each agent to use some container tooling you have in place since it can run commands if you give it permission.
What kind of Junior devs are you people hiring that you still need to do a lot of work to get it production ready?
I work with Junior devs. They are Junior in that they have to be pointed in the direction they must work, and would be out of their depth in guiding the implementation of major features. But simple code changes are pretty fine.
LLMs are useful, I kind of like them as code assistants, but they are very far of being even a Junior dev in terms of actually performing work.
I work with Junior devs. They are Junior in that they have to be pointed in the direction they must work, and would be out of their depth in guiding the implementation of major features. But simple code changes are pretty fine.
LLMs are useful, I kind of like them as code assistants, but they are very far of being even a Junior dev in terms of actually performing work.
In the presentation, they highlighted that the changes it makes are minimally invasive. That sounded as if it’s less prone to going on vision quests, like Claude often does. Is that something you‘ve observed as well?
https://www.augment.new/
has a similar feature (it uses sonnet 3.7) and I’m really impressed by it. Worth trying out.
it feels like openai are at a ceiling with their models, codex1 seems to be another RLHF derivative from the same base model. You can see this in their own self reported o3-high comparison where at 8 tries they converge at the same accuracy.
It also seems very telling they have not mentioned o4-high benchmarks at all. o4-mini exists, so logically there is an o4 full model right?
It also seems very telling they have not mentioned o4-high benchmarks at all. o4-mini exists, so logically there is an o4 full model right?
Seems likely that they are waiting to release o4 full results until the gpt-5 release later this year, presumably because gpt-5 is bundled with a roughly o4 level reasoning capability, and they want gpt-5 to feel like a significant release.
Do you still think there will be a gpt-5? I thought the consensus was GPT-5 never really panned out and was released with little fanfare as 4.1.
Marketing names aren’t really connected to product generations. We might target v3 of a product for a date and then decide it’s really 2.4, doesn’t mean we won’t market something as v3 later.
Yeah, just last month Altman said gpt-5 is coming in a few months, and betting/prediction sites are expecting it this year, probably in the summer.
If you aren't hiring junior engineers to do these kinds of things, where do you think the senior engineers you need in the future will come from?
My kid recently graduated from a very good school with a degree in computer science and what she's told me about the job market is scary. It seems that, relatively speaking, there's a lot of postings for senior engineers and very little for new grads.
My employer has hired recently and the flood of resumes after posting for a relatively low level position was nuts. There was just no hope of giving each candidate a fair chance and that really sucks.
My kid's classmates who did find work did it mostly through personal connections.
My kid recently graduated from a very good school with a degree in computer science and what she's told me about the job market is scary. It seems that, relatively speaking, there's a lot of postings for senior engineers and very little for new grads.
My employer has hired recently and the flood of resumes after posting for a relatively low level position was nuts. There was just no hope of giving each candidate a fair chance and that really sucks.
My kid's classmates who did find work did it mostly through personal connections.
Hiring of juniors is basically dead these days and it has been like this for about 10 years and I hate it. I remember when I was a junior in 2014 there were actually startups who would hire cohorts of juniors (like 10 at a time, fresh out of CS degree sort of folks with almost no applied coding experience) and then train them up to senior for a few years, and then a small number will stay and the rest will go elsewhere and the company will hire their next batch of juniors. Now no one does this, everyone wants a senior no matter how simple the task. This has caused everyone in the industry to stuff their resume, so you end up in a situation where companies are looking for 10 years of experience in ecosystems that are only 5 years old.
That said, back in the early 00s there was much more of a culture of everyone is expected to be self-taught and doing real web dev probably before they even get to college, so by the time they graduate they are in reality quite senior. This was true for me and a lot of my friends, but I feel like these days there are many CS grads who haven't done a lot of applied stuff. But at the same time, to be fair, this was a way easier task in the early 00s because if you knew JS/HTML/CSS/SQL, C++ and maybe some .NET language that was pretty much it you could do everything (there were virtually no frameworks), now there are thousands of frameworks and languages and ecosystems and you could spend 5+ years learning any one of them. It is no longer possible for one person to learn all of tech, people are much more specialized these days.
But I agree that eventually someone is going to have to start hiring juniors again or there will be no seniors.
That said, back in the early 00s there was much more of a culture of everyone is expected to be self-taught and doing real web dev probably before they even get to college, so by the time they graduate they are in reality quite senior. This was true for me and a lot of my friends, but I feel like these days there are many CS grads who haven't done a lot of applied stuff. But at the same time, to be fair, this was a way easier task in the early 00s because if you knew JS/HTML/CSS/SQL, C++ and maybe some .NET language that was pretty much it you could do everything (there were virtually no frameworks), now there are thousands of frameworks and languages and ecosystems and you could spend 5+ years learning any one of them. It is no longer possible for one person to learn all of tech, people are much more specialized these days.
But I agree that eventually someone is going to have to start hiring juniors again or there will be no seniors.
I recently read an article about the US having a relatively weak occupational training.
To contrast, CH and GER are known to have very robust and regulated apprenticeship programs. Meaning you start working at a much earlier age (16) and go to vocational school at the same time for about 4 years. This path is then supported with all kinds of educational stepping stones later down the line.
There are many software developers who went that route in CH for example, starting with an application development apprenticeship, then getting to technical college in their mid 20's and so on.
I think this model has a lot of advantages. University is for kids who like school and the academic approach to learning. Apprenticeships plus further education or an autodidactic path then casts a much broader net, where you learn practical skills much earlier.
There are several advantages and disadvantages of both paths. In summary I think the academic path provides deeper CS knowledge which can be a force multiplier. The apprenticeship path leads to earlier high productivity and pragmatism.
My opinion is that in combination, both being strongly supported paths, creates more opportunities for people and strengthens the economy as a whole.
To contrast, CH and GER are known to have very robust and regulated apprenticeship programs. Meaning you start working at a much earlier age (16) and go to vocational school at the same time for about 4 years. This path is then supported with all kinds of educational stepping stones later down the line.
There are many software developers who went that route in CH for example, starting with an application development apprenticeship, then getting to technical college in their mid 20's and so on.
I think this model has a lot of advantages. University is for kids who like school and the academic approach to learning. Apprenticeships plus further education or an autodidactic path then casts a much broader net, where you learn practical skills much earlier.
There are several advantages and disadvantages of both paths. In summary I think the academic path provides deeper CS knowledge which can be a force multiplier. The apprenticeship path leads to earlier high productivity and pragmatism.
My opinion is that in combination, both being strongly supported paths, creates more opportunities for people and strengthens the economy as a whole.
I know about this system, but I am not convinced it can work in such a dynamic field as software. When tools change all the time, you need strong fundamentals to stay afloat - which is what universities provide.
Vocational training focusing on immediate fit for the market is great for companies that want to extract maximal immediate value from labour for minimal cost, but longer term is not good for engineers themselves.
Vocational training focusing on immediate fit for the market is great for companies that want to extract maximal immediate value from labour for minimal cost, but longer term is not good for engineers themselves.
A formal apprenticeship still includes academic training - either one or two days a week at college, or longer blocks spread throughout the year. I can't speak for software engineers, but the mechanical engineers I know that have finished a German apprenticeship have a very rigorous theoretical background.
I actually think it work fairly well, if it wasn't regulated.
Eg a company like Google (or similar) could probably offer you better on the job vocational training than going to uni would do to teach anyone programming.
Eg a company like Google (or similar) could probably offer you better on the job vocational training than going to uni would do to teach anyone programming.
do most people know country codes to the degree that they know CH is Switzerland? as feedback, i found this added an unnecessary extra layer of opacity to this comment
I like how the smallest Eurocentrism is greeted with the wagging finger to be inclusive on hackernews, while the expectation is that 50 state acronyms are well understood by any reader from Lazio, Lorraine, or Thuringia ;)
This is an english language forum, so I think quite naturally an acronym in a different language is less interpretable to english speakers globally.
GER isn’t even a valid country code so it compounds the confusion, if we are going to make a fake three-letter country code for Germany derived from English, why not do the same for significantly more obscure Switzerland?
GER isn’t even a valid country code so it compounds the confusion, if we are going to make a fake three-letter country code for Germany derived from English, why not do the same for significantly more obscure Switzerland?
Whoops, definitely read that as China until your comment.
I feel like hiring juniors still exists, because I still hear about loads of "boring" small startups that do the "we hire juniors and seniors".
Juniors cuz they're cheap and motivated (and potentially grow into very good team members!), seniors to handle the trickier stuff. Mid-level people don't get picked up cuz there's enough junior pipeline that the cost-benefit doesn't work out.
Thing is these companies tend to have, say, college pipelines and the like for juniors. Internships and the like. It would be really painful to not have internships lined up at "your local startup" in this day and age.
My impression is that a lot of the junior dev pipeline is in smaller places that don't show up in job boards in the same way as the rest of it. Maybe that's dried up too, but I have my doubts.
You still need somebody to work the robot, even if the robot is "doing the coding"!
Juniors cuz they're cheap and motivated (and potentially grow into very good team members!), seniors to handle the trickier stuff. Mid-level people don't get picked up cuz there's enough junior pipeline that the cost-benefit doesn't work out.
Thing is these companies tend to have, say, college pipelines and the like for juniors. Internships and the like. It would be really painful to not have internships lined up at "your local startup" in this day and age.
My impression is that a lot of the junior dev pipeline is in smaller places that don't show up in job boards in the same way as the rest of it. Maybe that's dried up too, but I have my doubts.
You still need somebody to work the robot, even if the robot is "doing the coding"!
I don't think it's been dead for 10 years. I'd place it at maybe 3? I teach at a mid-ranked university and the majority of my fresh out of college students were getting good-to-great entry level offers just a few years ago. The top 5-10% were getting well into six figure offers from FAANG or similar companies. But the entry level job market really tanked in mid 2022 when all the big tech companies did rounds of layoffs, and it's been much harder since then.
We should factor in the hiring sprees that really distorted the market from 2020-2022..
2020-2022 was not "normal hiring", it was much higher than normal.
Even the large, conservative, boring enterprise where I work was hiring about 5 new developers a week in those years.. I know because I did the "Welcome to our department" technical onboarding workshop and I saw everyone coming in the door every week.
Before 2020 I ran that workshop once a month or so? Probably 10 times a year at most.
So of course then the layoffs came when ZIRP ended, as everyone had to adjust back to real world conditions and grapple with the fact that the team sizes they had now were not sustainable (or necessary?) when free money ended.
Couple that with "efficiencies" from AI and generally more conservative scope and ambition by a lot of companies in these uncertain times, and the market looks drastically worse than it did in 2020-2022.
But if you compare the market today to 2018 (for example) instead, it's still worse but definitely not as worse.
Lastly, hiring is also very broken today due to AI, with candidates using it to flood companies with applications and then companies using AI to auto-filter that incoming flood (and likely losing out on good candidates in the process) simply because they can't handle the volume.
I have a lot of sympathy for folks coming right out of university trying to land their first good job. I'm sure it's the toughest it's been in a generation...
2020-2022 was not "normal hiring", it was much higher than normal.
Even the large, conservative, boring enterprise where I work was hiring about 5 new developers a week in those years.. I know because I did the "Welcome to our department" technical onboarding workshop and I saw everyone coming in the door every week.
Before 2020 I ran that workshop once a month or so? Probably 10 times a year at most.
So of course then the layoffs came when ZIRP ended, as everyone had to adjust back to real world conditions and grapple with the fact that the team sizes they had now were not sustainable (or necessary?) when free money ended.
Couple that with "efficiencies" from AI and generally more conservative scope and ambition by a lot of companies in these uncertain times, and the market looks drastically worse than it did in 2020-2022.
But if you compare the market today to 2018 (for example) instead, it's still worse but definitely not as worse.
Lastly, hiring is also very broken today due to AI, with candidates using it to flood companies with applications and then companies using AI to auto-filter that incoming flood (and likely losing out on good candidates in the process) simply because they can't handle the volume.
I have a lot of sympathy for folks coming right out of university trying to land their first good job. I'm sure it's the toughest it's been in a generation...
This was pretty much the height of the “bootcamp” era, and while some were still great at teaching solid programming skills, many people who were mediocre coders saw it as a quick way to make money off those who don’t know better. In my opinion, companies started noting more and more that they were hiring people who can barely code in a real software environment but had focused training on resume padding and interview prep, and that many of the college graduates weren’t any better off, so they ramped up to far more rigorous testing, live coding projects, and more and more rounds of interviews just to weed out all the people who had been taught how to BS their way into a tech job. Now the interview process has become so cumbersome that it is more worthwhile to filter out nearly every applicant immediately.
It started with the end of ZIRP and LLMs finished the job.
"Money isn't free anymore, let's set ours on fire / give it to NVDA"
More like, "Money isn't free anymore, so let's try and automate away some more labor". It's very much not setting the money on fire from business POV - it's the opposite actually. It's also a constant in history - the more expensive human labor gets, the more effort is put into eliminating the need for it (whether by automating jobs away or redesigning the product or the entire business to not need them in the first place).
The problem is getting hired. With all the resources available today, learning programming is easy compared to pre-LLM, pre-Stack Overflow, pre-Google days of learning to program. I dare say an autodidact in the original dot com boom, transported to today, would be fine, as far as being useful to a company goes. You don't need to know every frontend framework, all possible backends, and be a Linux god at devops, all at once. Sure there's more stuff today then in the 00's, but no team is using all of all three of those simultaneously, so what you practically have to know isn't too much for a motivated individual to learn.
The problem is getting hired. If seniors are having problems getting callbacks for interviews right now, then a young kid with a thin resume isn't going to get hired, no matter how senior their skills are in reality.
The problem is getting hired. If seniors are having problems getting callbacks for interviews right now, then a young kid with a thin resume isn't going to get hired, no matter how senior their skills are in reality.
Bottom of the barrel consultancy shops will hire as cheap as possible. E.g. some liberal arts major whose only coding experience is a 2 week 'bootcamp'.
They will sell them as 'junior SE' on the first 2 projects, 'medior SE' on the next and then they'll be 'senior SE' within 18 months tops of leaving bootcamp.
The projects by these shops are nearly always troubled, requiring many (customer paid in change requests) reworks before (if ever) getting in production.
They seldom are hired to do projects for a client twice, but it's a lemom's market and there's plenty of fish in the sea.
So what happens with these shops is that their SE's will rely even more than average on AI assistants, and deliver a v0.1 faster, but with 10x more code and holes than before, taking even longer to get in production but given lemons and fish have not changed they'll still hire, now even cheaper out of 'prompt engineering bootcamp'
They will sell them as 'junior SE' on the first 2 projects, 'medior SE' on the next and then they'll be 'senior SE' within 18 months tops of leaving bootcamp.
The projects by these shops are nearly always troubled, requiring many (customer paid in change requests) reworks before (if ever) getting in production.
They seldom are hired to do projects for a client twice, but it's a lemom's market and there's plenty of fish in the sea.
So what happens with these shops is that their SE's will rely even more than average on AI assistants, and deliver a v0.1 faster, but with 10x more code and holes than before, taking even longer to get in production but given lemons and fish have not changed they'll still hire, now even cheaper out of 'prompt engineering bootcamp'
Some of this relates to a culture of job-hopping. It seems uncommon these days to stick around at a company for many years.
If your next hire is only going to stay for 1-2 years, it doesn’t make sense to hire a junior team member and invest in their growth.
If your next hire is only going to stay for 1-2 years, it doesn’t make sense to hire a junior team member and invest in their growth.
That sadly makes sense. I’m in a position lately to influence hiring decisions and I’m noticing a similar bias in myself.
As a job hopper myself, I can’t fault others for doing it though. I never hopped for the money. I just got bored or felt isolated in my role. But a nice consequence is that my salary actually appreciably increased, as opposed to colleagues/friends who stuck with the same company.
As a job hopper myself, I can’t fault others for doing it though. I never hopped for the money. I just got bored or felt isolated in my role. But a nice consequence is that my salary actually appreciably increased, as opposed to colleagues/friends who stuck with the same company.
I've often given developers I mentor the advice they should "zig-zag" to grow their career and get varied experiences rather than stay in one place too long, but my advice was 2-3 years at each place at minimum.
I think anything less than that, and you haven't had time to really learn an ecosystem, and more importantly you might not have had a chance to live with the consequences of your technical decisions (i.e. supporting something in prod that you built).
I know plenty of people who started somewhere, left for a while, and then came back and ended up in a position higher than they would have gotten if they had stayed put and tried to climb internally.
And yes agreed that moving around will 100% grow your comp faster than staying put (in most cases).
I think anything less than that, and you haven't had time to really learn an ecosystem, and more importantly you might not have had a chance to live with the consequences of your technical decisions (i.e. supporting something in prod that you built).
I know plenty of people who started somewhere, left for a while, and then came back and ended up in a position higher than they would have gotten if they had stayed put and tried to climb internally.
And yes agreed that moving around will 100% grow your comp faster than staying put (in most cases).
I mean I wish I could stay, but companies are greedy and refuse to give out decent raises or promotions regardless of your contributions. The only real way to make more money is to hop between jobs, all the while these companies are making record profits year after year.
Like right now I've been at current co for 3 years. At the start I was getting decent raises after big projects. I now have increasingly more responsibility, I'm doing hiring, I'm doing mentorship, I'm doing huge feature work, I have to waste half my time talking to the braindead stakeholders. And what do I get for that? Absolutely jackshit, I'm getting paid the same I was when I had a quarter of the responsibility and work, yet the company is boasting about making ever more money as they lay off entire teams of people.
Why on earth would I be loyal at this point, it's clear they don't give the slightest inkling of a shit about me or anyone else who does have "Head of" or "Chief" prepended to their title.
Like right now I've been at current co for 3 years. At the start I was getting decent raises after big projects. I now have increasingly more responsibility, I'm doing hiring, I'm doing mentorship, I'm doing huge feature work, I have to waste half my time talking to the braindead stakeholders. And what do I get for that? Absolutely jackshit, I'm getting paid the same I was when I had a quarter of the responsibility and work, yet the company is boasting about making ever more money as they lay off entire teams of people.
Why on earth would I be loyal at this point, it's clear they don't give the slightest inkling of a shit about me or anyone else who does have "Head of" or "Chief" prepended to their title.
That's a self-inflicted wound on the part of the companies though, with them offering relatively shit pay for people who stick around compared to people who switch jobs.
You get what you optimize for, really.
You get what you optimize for, really.
> But at the same time, to be fair, this was a way easier task in the early 00s
The best junior I've hired was a big contributor to an open source library we were starting to use.
I think there's still lots of opportunity for honing your skill, and showing it off, outside of schools.
The best junior I've hired was a big contributor to an open source library we were starting to use.
I think there's still lots of opportunity for honing your skill, and showing it off, outside of schools.
Agreed. One of my mentors early on was a self taught engineer and honestly I'd trust him a lot more than some of the engineers with degrees
> The best junior I've hired was a big contributor to an open source library we were starting to use.
From my experience no one cares. You're lucky if recruiter even looks at your CV, not to mention your GitHub profile.
From my experience no one cares. You're lucky if recruiter even looks at your CV, not to mention your GitHub profile.
> Hiring of juniors is basically dead these days and it has been like this for about 10 years and I hate it
We still have a large funnel of interns that end up becoming junior devs, and then progressing normally. I don't know the exact ratio of interns that end up actually getting hired as full-time employees, it's definitely low, but I think this is more of a function of most of them not actually being any good.
We still have a large funnel of interns that end up becoming junior devs, and then progressing normally. I don't know the exact ratio of interns that end up actually getting hired as full-time employees, it's definitely low, but I think this is more of a function of most of them not actually being any good.
The place where I work at hires an ungodly amount of juniors and fresh-grads (because a lot of them drop out and quit before they do any meaningful work). We're talking people that are completely unproductive and unusable for any sort of commercial project. We then spend at-least a year or two giving them a salary whilst they do toy projects and get trained. Literally doing what I remember doing in 1st/2nd year college with group projects and pet-assignments, complete with grades and feedback etc. Even after all of that, we still have to "train" them with hand-holding on an actual project work before they are a net-positive. Sooner or later someone will realize that they can just forego all that wasted training effort and just hire someone that is already productive. There is always a small percentage that are amazing and they get pushed through to projects very quickly. Which is a shame, because they then watch their fellow cohort sit around doing pet-projects and receive a salary, whilst they slog through a real project with deadlines, stress and the risk of failing.
This is entirely a combination of two things: The quality of grads coming out of college/university, and pressures coming from the market. Colleges have been pushing through entirely unqualified students, some even language illiterate, into the market place and what we're seeing is a response to that. Now couple that with the pressures that companies are facing, and you can see why none of them want to even take on the risk of training and up-skilling someone just so they can find the actual good employees which are a small percentage.
Of course, in my company's particular country and context, government regulations make it impossible to fire someone and there is huge pressure to keep-up DEI quotas despite no actual good DEI candidates being available, and we have a mess. Day to day is glorified baby-sitting people not-knowing what to do, dealing with their "feelings" (usually feelings of inadequacy and sometimes snobbish entitlement) and still trying complete a project at the same time.
This is entirely a combination of two things: The quality of grads coming out of college/university, and pressures coming from the market. Colleges have been pushing through entirely unqualified students, some even language illiterate, into the market place and what we're seeing is a response to that. Now couple that with the pressures that companies are facing, and you can see why none of them want to even take on the risk of training and up-skilling someone just so they can find the actual good employees which are a small percentage.
Of course, in my company's particular country and context, government regulations make it impossible to fire someone and there is huge pressure to keep-up DEI quotas despite no actual good DEI candidates being available, and we have a mess. Day to day is glorified baby-sitting people not-knowing what to do, dealing with their "feelings" (usually feelings of inadequacy and sometimes snobbish entitlement) and still trying complete a project at the same time.
Why does your company even hire those people? They seem like a net negative as far as your profit-and-loss is concerned?
I mean even compared to just not hiring any juniors.
I mean even compared to just not hiring any juniors.
Probably to have a chance at finding a small handful of smart and productive juniors. That, or they need bodies to make up the racial quotas imposed by government regulation, otherwise the company can't get any government contracts.
One problem I’ve seen is that junior now means “hustler who is faking it” or “code boot camp grad who doesn’t really understand anything.” If I ask for a “junior” I get someone who googles and asks ChatGPT.
High salaries in programming has attracted a lot of people who have no passion for the craft. To get good you have to have that and it takes years of either school or passionate autodidactic learning or both.
High salaries in programming has attracted a lot of people who have no passion for the craft. To get good you have to have that and it takes years of either school or passionate autodidactic learning or both.
Hmm, I thought Matz had a story like this but AI tells me it's probably apocryphal. Ruby developer applies for ruby job where they want more years of experience than existed since he wrote ruby.
Oh well, I know that it happens, saw it in 2010 with "cloud" when it was basically still just EC2,S3,RDS, and whatever the not-haproxy-but-haproxy load balancer was called, ELB. Job poatings asking for half a decade or more of experience. I always get the feeling there's some requirement they post jobs public but only hire internal, but I have no way to prove that; I have heard others say this, though.
Oh well, I know that it happens, saw it in 2010 with "cloud" when it was basically still just EC2,S3,RDS, and whatever the not-haproxy-but-haproxy load balancer was called, ELB. Job poatings asking for half a decade or more of experience. I always get the feeling there's some requirement they post jobs public but only hire internal, but I have no way to prove that; I have heard others say this, though.
I recall that story as well. I think it might have been in a ruby weekly email if you sub to that.
We have had a lot of success hiring right out of college over the last 10 years
This is a bit of a game theory problem. "Training senior engineers" is an expensive and thankless task: you bear essentially all the cost, and most of the total benefit accrues to others as a positive externality. Griping at companies that they should undertake to provide this positive externality isn't really a constructive solution.
I think some people are betting on the fact that AI can replace junior devs in 2-5 years and seniors in 10-20, when the old ones are largely gone. But that's sort of beside the point as far as most corporate decision-making.
I think some people are betting on the fact that AI can replace junior devs in 2-5 years and seniors in 10-20, when the old ones are largely gone. But that's sort of beside the point as far as most corporate decision-making.
This hyper-fixation on replacing engineers in writing code is hilarious, and dangerous, to me. Many people, even in tech companies, have no idea how software is built, maintained, and run.
I think instead we should focus on getting rid of managers and product owners.
I think instead we should focus on getting rid of managers and product owners.
The real judge will be survivorship bias and as a betting man, I might think product owners are the ones with the entrepreneurial spirit to make it to the other side.
Product owners and project managers have the soft skills to convince the company that they aren't a drain on its resources regardless of what they actually are.
Yeah, but can they out-perform LLMs at soft skills? LLMs are really good sucking up, and telling people what they want to hear.
I've worked for a company which turned from startup to this. Product owners had no clue what they own. And no brain capacity to suggest something useful. They were just taken from the street at best, most likely had relatives' helping hands. In a couple of years company probably tripled manages headcount. It didn't help.
The people who will come out the other side are domain focused people with the engineering chops to understand the system end to end, and the customer skills to understand what needs to be built.
Yes. everyone will eventually have the job title of "problem solver"
Don't forget the very important role of managing the problem solvers--if you just let the problem solvers run amuck all sorts of problems might be solved.
Yeah, if places like RAND or Xerox PARC or the OG Skunkworks, or even Manhattan Project and Apollo Program taught us, is that you cannot let engineers and domain experts run the show, because if you do, they start doing some world-upending shit like putting GUIs on the Moon, or building nukes, or supersonic jets, or inventing new materials that violate the natural order of things, or they generally just rock the boat too much, continuously disrupting the corporate and political pecking order.
Nah, you have to put them in hamster wheels so they keep generating steady value for the shareholders, and put those in open plan offices so they get too mentally exhausted and distracted to try and change things. Throw in free cheese during good economy to keep them happy, but that's strictly optional.
Nah, you have to put them in hamster wheels so they keep generating steady value for the shareholders, and put those in open plan offices so they get too mentally exhausted and distracted to try and change things. Throw in free cheese during good economy to keep them happy, but that's strictly optional.
Major Dilbert vibes
As a dev, if you try taking away my product owners I will fight you. Who am I going to ask for requirements and sign-offs, the CEO?
Your architect, principal engineer etc. (one spot-on job title I've seen is "product architect"), who in turn talks to the senior management.
Basically an engineer with a talent and experience for building products rather than a manager with superficial understanding of engineering. I think the most ambitious teams have someone like this on top - or at least around
I've had your type of product owner, but I've also had a product owner that was an ex-staff engineer. Companies should hire ex-engineer product owners, not strictly people-manager product owners.
Technical background doesn't always help in my experience - it's just a different role. Creating great product requires deep technical expertise to understand where the cutting edge is, vision to understand how it can be expanded and business expertise to understand what makes sense economically. It's just not a manager's job, you can't perform it by collecting customer requirements in a spreadsheet.
Perhaps the role will merge into one, and will replace a good chunk of those jobs.
E.g.:
If we have 10 PMs and 90 devs today, that could be hypothetically be replace by 8 PM+Dev, 20 specialized devs, and 2 specialized PMs in the future.
E.g.:
If we have 10 PMs and 90 devs today, that could be hypothetically be replace by 8 PM+Dev, 20 specialized devs, and 2 specialized PMs in the future.
If you have 10PMs and 90 devs today, and go to 8 "hybrid" PMs + 2 specialized PMs, you're probably still creating backlog items faster than that team can close them.
So you end up with some choices:
* do you move at the same speed, with fewer people?
* do you try to move faster, with less of a reduction in people? this could be trickier than it sounds because if the frequency of changes increases the frequency of unintended consequences likely does too, so your team will have to spend time reacting to that
I think the companies that win will be the second batch. It's what happens today, basically, but today you have to convince VCs or the public market to give you a bunch of more money to hire to 10x the team size. Getting a (one-off?) chance to do that through tooling improvements is a big gift, wasting it on reducing costs instead of increasing growth could be risky.
So you end up with some choices:
* do you move at the same speed, with fewer people?
* do you try to move faster, with less of a reduction in people? this could be trickier than it sounds because if the frequency of changes increases the frequency of unintended consequences likely does too, so your team will have to spend time reacting to that
I think the companies that win will be the second batch. It's what happens today, basically, but today you have to convince VCs or the public market to give you a bunch of more money to hire to 10x the team size. Getting a (one-off?) chance to do that through tooling improvements is a big gift, wasting it on reducing costs instead of increasing growth could be risky.
A 70% reduction in the labor force of product and engineering has a lot of consequences.
> I think instead we should focus on getting rid of managers and product owners.
Who says companies aren't doing that with AI (and technology in general) already?
Who says companies aren't doing that with AI (and technology in general) already?
Who says they are doing that?
The _instead_ was a key word in my comment. I didn’t say, or imply, they weren’t working on replacing other roles with AI.
The _instead_ was a key word in my comment. I didn’t say, or imply, they weren’t working on replacing other roles with AI.
it’s obviously intensely correlated: the vast majority of scenarios either both are replaced or neither
With Agentic RL training and sufficient data, AI operating at the level of average senior engineers should become plausible in a couple to a few years.
Top-tier engineers who integrate a deep understanding of business and user needs into technical design will likely be safe until we get full-fledged AGI.
Top-tier engineers who integrate a deep understanding of business and user needs into technical design will likely be safe until we get full-fledged AGI.
Why in a few years? What training data is missing that we can’t have senior level agents today?
Training data, esp interaction data from agentic coding tools, are important for that. See also: Windsurf acquisition.
On the other hand I’m pretry sure you will need senior engineers not only for designing but debugging. You don’t want to hit a wall when your Agentic coder hits a bug that it just won’t fix.
There’s a recent article with experiments suggesting LLMs are better at bug fixing than coding, iirc. It’s from a company with a relevant product though.
Why do you expect AIs to learn programming, but not debugging?
I think it'll be great if you're working in software not for a software company.
That sounds like a dangerous bet.
As I see it, it's actually the only safe bet.
Case 1: you keep training engineers.
Case 1.1: AGI soon, you don't need juniors or seniors besides a very few. You cost yourself a ton of money that competitors can reinvest into R&D, use to undercut your prices, or return to keep their investors happy.
Case 1.2: No AGI. Wages rise, a lot. You must remain in line with that to avoid losing those engineers you trained.
Case 2: You quit training juniors and let AI do the work.
Case 2.1: AGI soon, you have saved yourself a bundle of cash and remain mostly in in line with the market.
Case 2.2: no AGI, you are in the same bidding war for talent as everyone else, the same place you'd have been were you to have spent all that cash to train engineers. You now have a juicier balance sheet with which to enter this bidding war.
The only way out of this, you can probably see, is some sort of external co-ordination, as is the case with most of these situations. The high-EV move is to quit training juniors, by a mile, independently of whether AI can replace senior devs in a decade.
Case 1: you keep training engineers.
Case 1.1: AGI soon, you don't need juniors or seniors besides a very few. You cost yourself a ton of money that competitors can reinvest into R&D, use to undercut your prices, or return to keep their investors happy.
Case 1.2: No AGI. Wages rise, a lot. You must remain in line with that to avoid losing those engineers you trained.
Case 2: You quit training juniors and let AI do the work.
Case 2.1: AGI soon, you have saved yourself a bundle of cash and remain mostly in in line with the market.
Case 2.2: no AGI, you are in the same bidding war for talent as everyone else, the same place you'd have been were you to have spent all that cash to train engineers. You now have a juicier balance sheet with which to enter this bidding war.
The only way out of this, you can probably see, is some sort of external co-ordination, as is the case with most of these situations. The high-EV move is to quit training juniors, by a mile, independently of whether AI can replace senior devs in a decade.
Case 1.3: No AGI, tools increase productivity a lot, you have a bigger team and you make them more productive. In the meantime, while everyone else was scared of hiring, you got a bunch of stuff done to gain a lead in the market.
You get high EV because everyone else in your market voluntarily slowing down is a gift-wrapped miracle for you.
(Even in an AGI-soon case - you spent a bit more (let's be serious here, we're not talking about spending our entire bankroll on 18months of new hires here) in short term to get ahead, then you shift people around or lay them off. Your competitors invested that money into R&D? What does that even mean if it didn't involve hiring and AGI happens soon anyway?)
----
(Case 3: AGI soon, you don't need yourself anymore - it's hard to imagine a sufficiently advanced "AGI" that someone only replaces software devs but leaves the structure, management, and MBA-trappings of modern exchange and businesses alone.)
You get high EV because everyone else in your market voluntarily slowing down is a gift-wrapped miracle for you.
(Even in an AGI-soon case - you spent a bit more (let's be serious here, we're not talking about spending our entire bankroll on 18months of new hires here) in short term to get ahead, then you shift people around or lay them off. Your competitors invested that money into R&D? What does that even mean if it didn't involve hiring and AGI happens soon anyway?)
----
(Case 3: AGI soon, you don't need yourself anymore - it's hard to imagine a sufficiently advanced "AGI" that someone only replaces software devs but leaves the structure, management, and MBA-trappings of modern exchange and businesses alone.)
> The only way out of this, you can probably see, is some sort of external co-ordination, as is the case with most of these situations.
You lack imagination. You can eg just charge juniors for the training.
Either directly (which won't really work, because juniors almost by definition don't have a lot of money), or via a bond that they have to pay back iff they jump ship before a set number of years.
Have a look at how airlines and airline pilots pay for their expensive education.
You lack imagination. You can eg just charge juniors for the training.
Either directly (which won't really work, because juniors almost by definition don't have a lot of money), or via a bond that they have to pay back iff they jump ship before a set number of years.
Have a look at how airlines and airline pilots pay for their expensive education.
You’re looking at it from the point of view of an individual company. I’m seeing it as a risk for the entire industry.
Senior engineers are already very well paid. Wages rising a lot from where they already are, while companies compete for a few people, and those who can’t afford it need to lean on AI or wait 10+ years for someone to develop with equivalent expertise… all of this sounds bad for the industry. It’s only good for the few senior engineers that are about to retire, and the few who went out of their way to not use AI and acquire actual skills.
Senior engineers are already very well paid. Wages rising a lot from where they already are, while companies compete for a few people, and those who can’t afford it need to lean on AI or wait 10+ years for someone to develop with equivalent expertise… all of this sounds bad for the industry. It’s only good for the few senior engineers that are about to retire, and the few who went out of their way to not use AI and acquire actual skills.
Well, yes. But nobody is running the entire industry. You’re running a company that has competitors willing to eat your lunch.
An interesting thing to consider is that Codex might get people to be better at delegating, which might improve the effectiveness of hiring junior engineers. Because the senior engineers will have better skills at delegating, leading to a more effective collaboration.
I’m curious about other aspects of this:
- leverage of countries who can host such AI over countries who can’t, will there be a point when countries can’t allow themselves not to have access to „emergency” talent in case they can’t use AI? Recent „choose european”, tariffs show that much of the high end stuff is concentrated in US and China.
- outages happen, does the company stop because the cloud is not working?
- highly regulated companies still can’t use copilot to its fullest because of „can’t show answer because it’s matching public code”
- is replacing all talent safe - in terms of operational or national safety?
Not being able to use AI would be entirely self-inflicted at the country level.
You can get around most of your objections by using a model with open weights that you run on-premises.
You can get around most of your objections by using a model with open weights that you run on-premises.
Sounds like a bet a later CEO will need to check.
> If you aren't hiring junior engineers to do these kinds of things, where do you think the senior engineers you need in the future will come from?
Unfortunately this is not how companies think. I read somewhere more than 20 years ago about outsourcing and manufacturing offshoring. The author basically asked the same: if we move out the so-called low-end jobs, where do we think we will get the senior engineers? Yet companies continued offshoring, and the western lost talent and know-how, while watching our competitor you-know-who become the world leader in increasingly more industries.
Unfortunately this is not how companies think. I read somewhere more than 20 years ago about outsourcing and manufacturing offshoring. The author basically asked the same: if we move out the so-called low-end jobs, where do we think we will get the senior engineers? Yet companies continued offshoring, and the western lost talent and know-how, while watching our competitor you-know-who become the world leader in increasingly more industries.
It's happening to Hollywood right now. In the past three years, since roughly 2022, the majority of IATSE folks (film crew, grips, etc.) have seen their jobs disappear to Eastern Europe where the labor costs one tenth of what it does here. And there are no rules for maximum number of consecutive hours worked.
How do? Perhaps if you film in Eastern Europe (which I realize does happen a bit), but even if your crew is foreign, if you’re filming in the US they’re still subject to US labor law. Being willing to ignore labor law also happens but is a bit beyond “offshoring”.
The film production company flies the cast of actors out to Serbia or whatever and relies on Serbian crews.
Prior to 2022 they'd fly out the entire crew from the US and all the workers would be American and Canadian. Union, highly paid. Now they're using local (non-American) labor.
Amazon and Apple taught the foreign talent how to do grip work so they didn't have to hire expensive American workers anymore.
There are far fewer productions happening domestically within the US now. The numbers are 30% of what they once were.
Prior to 2022 they'd fly out the entire crew from the US and all the workers would be American and Canadian. Union, highly paid. Now they're using local (non-American) labor.
Amazon and Apple taught the foreign talent how to do grip work so they didn't have to hire expensive American workers anymore.
There are far fewer productions happening domestically within the US now. The numbers are 30% of what they once were.
This is happening increasingly in pharma companies as well.
There was a pull quote about adding a 100% tariff to films made outside of the US.
I wonder if that's related
I wonder if that's related
ahh, the classic “i shall please my investors next quarter while ignoring reality, so i can disappoint my shareholders in 10 years”. lol.
As you say, happens all the time. Also doesn’t make sense because so few people are buying individual stocks anyway. Goal should be to consistently outperform over the long term. Wall street tends to be very myopic.
Thinking long term is a hard concept for the bean counters at these tech companies i guess…
As you say, happens all the time. Also doesn’t make sense because so few people are buying individual stocks anyway. Goal should be to consistently outperform over the long term. Wall street tends to be very myopic.
Thinking long term is a hard concept for the bean counters at these tech companies i guess…
What then ends up happening is that companies how fall behind in R&D eventually lose market share and get replaced by more agile competitors.
But this does not happen in industry verticals that are protected by regulation (banks) or national interest (Boring).
But this does not happen in industry verticals that are protected by regulation (banks) or national interest (Boring).
To be clear, we still hire engineers who are early in their careers (and we've found them to be some of the best folks on our team).
All the same principles apply as before: smart, driven, high ownership engineers make a huge difference to a company's success, and I find that the trend is even stronger now than before because of all the tools that these early career engineers have access to. Many of the folks we've hired have been able to spin up on our codebase much faster than in the past.
We're mainly helping them develop taste for what good code / good practices look like.
All the same principles apply as before: smart, driven, high ownership engineers make a huge difference to a company's success, and I find that the trend is even stronger now than before because of all the tools that these early career engineers have access to. Many of the folks we've hired have been able to spin up on our codebase much faster than in the past.
We're mainly helping them develop taste for what good code / good practices look like.
> we still hire engineers who are early in their careers
That's really great to hear.
Your experience that a new engineer equipped with modern tools is more effective and productive than in the past is important to highlight. It makes total sense.
That's really great to hear.
Your experience that a new engineer equipped with modern tools is more effective and productive than in the past is important to highlight. It makes total sense.
More recent models are not without drive and are not stupid either.
There’s still quite a bit of a gap in terms of trust.
There’s still quite a bit of a gap in terms of trust.
> If you aren't hiring junior engineers to do these kinds of things, where do you think the senior engineers you need in the future will come from?
I know this isn't what you want to hear, but what makes you think senior engineers will be in short supply in "the future"?
I'm not even a developer (anymore, I was in the past), I'm a product manager, and I'm pretty sure I can see the point in a few years where not just developers but people like me get disintermediated. My customers have a semi-reasonable grasp of what they're looking for, and they can speak. In a few years -- ten at the absolute most -- my customers will say to an AI, "I need an application that does XYZ" and the AI will reply, "Are you sure about that? Most people who say they need XYZ end up using an app that does WXY." My (former) users will reply, "Let's try it my way and see what happens." And the AI will say, "Okay, here are three popular UI styles, which do you prefer?" etc. etc.
We're headed for Interesting Times.
I know this isn't what you want to hear, but what makes you think senior engineers will be in short supply in "the future"?
I'm not even a developer (anymore, I was in the past), I'm a product manager, and I'm pretty sure I can see the point in a few years where not just developers but people like me get disintermediated. My customers have a semi-reasonable grasp of what they're looking for, and they can speak. In a few years -- ten at the absolute most -- my customers will say to an AI, "I need an application that does XYZ" and the AI will reply, "Are you sure about that? Most people who say they need XYZ end up using an app that does WXY." My (former) users will reply, "Let's try it my way and see what happens." And the AI will say, "Okay, here are three popular UI styles, which do you prefer?" etc. etc.
We're headed for Interesting Times.
I don't think jobs are necessarily a good plan at all anymore. Figure out how to leverage AIs and robots as cheap labor, and sell services or products. But if someone is trying to get a job, I get the impression that networking helps more than anything.
Yeah, the value of the typical job application meta is trending to zero very quickly. Entrepreneurship has a steep learning curve; you should start learning it as soon as possible. Don't waste your time learning to run a straight line - we're entering off-road territory.
I think the bigger problem, that started around 2022 is much lower volume of jobs in software development. Projects were shutdown, funding was retracted, even the big wave of migrations to the cloud died down.
Today startups mostly wrap LLMs as this is what VCs expect. Larger companies have smaller IT budgets than before (adjusted for inflation). This is the real problem that causes the jobs shortage.
Today startups mostly wrap LLMs as this is what VCs expect. Larger companies have smaller IT budgets than before (adjusted for inflation). This is the real problem that causes the jobs shortage.
I guess the industry leaders think we'll not need senior engineers either as capabilities evolve.
But also, I think this underestimates significantly what junior engineers do. Junior engineers are people who have spent 4 to 6 years receiving a specialised education in a university - and they normally need to be already good at school math. All they lack is experience applying this education on a job - but they are professionals - educated, proactive and mostly smart.
The market is tough indeed, and as much it is tough for a senior engineer like myself, I don't envy the current cohort of fresh grads. It being tough is only tangentially related to the AI though. Main factor is the general economic slowdown, with AI contributing by distracting already scarce investment from non-AI companies and producing a lot of uncertainty in how many and what employees companies will need in the future. Their current capabilities are nowhere near to having a real economic impact.
Wish your kid and you a lot of patience, grit and luck.
But also, I think this underestimates significantly what junior engineers do. Junior engineers are people who have spent 4 to 6 years receiving a specialised education in a university - and they normally need to be already good at school math. All they lack is experience applying this education on a job - but they are professionals - educated, proactive and mostly smart.
The market is tough indeed, and as much it is tough for a senior engineer like myself, I don't envy the current cohort of fresh grads. It being tough is only tangentially related to the AI though. Main factor is the general economic slowdown, with AI contributing by distracting already scarce investment from non-AI companies and producing a lot of uncertainty in how many and what employees companies will need in the future. Their current capabilities are nowhere near to having a real economic impact.
Wish your kid and you a lot of patience, grit and luck.
> and they normally need to be already good at school math. All they lack is experience applying this education on a job - but they are professionals - educated, proactive and mostly smart.
Without being overly pessimistic, this interpretation is extremely generous.
Without being overly pessimistic, this interpretation is extremely generous.
Hardly.
What I've mostly seen when it isn't the case is an employer who hasn't let them fly, but simply bombarded them with work nobody wants to do. They become cynical, and it is understandable.
What I've mostly seen when it isn't the case is an employer who hasn't let them fly, but simply bombarded them with work nobody wants to do. They become cynical, and it is understandable.
Same, mine is about to graduate with a CS masters from a great school. Couldn't get any internships, and is now incredibly negative about ever being able to find work, which doesn't help. We're pretty much looking at minimum wage jobs doing tech support for NGOs at this point (and the current wave of funding cuts from Federal government for those kind of orgs is certainly not going to help with that).
With so many graduates looking for a job why don't they bang together and do something. If not for money then just to show off their skills, something to put in the resume.
It's not going to get any easier in next next few years, I think. Till the point when fresh grad using AI can make something valuable. After that it will be period when anybody can just ask AI to do something and it will find soft in its library or write from scratch. In long terms, 10 years may be, humanity probably will not need this many developers. There will be split like in games industry: tools/libs developers and product devs/artists/designers. With the majority in second category.
It's not going to get any easier in next next few years, I think. Till the point when fresh grad using AI can make something valuable. After that it will be period when anybody can just ask AI to do something and it will find soft in its library or write from scratch. In long terms, 10 years may be, humanity probably will not need this many developers. There will be split like in games industry: tools/libs developers and product devs/artists/designers. With the majority in second category.
> With so many graduates looking for a job why don't they bang together and do something. If not for money then just to show off their skills, something to put in the resume.
Young people are already doing that, but a lot of what they produce is what you expect from people who have no prior experience in designing and testing software for production environments.
Young people are already doing that, but a lot of what they produce is what you expect from people who have no prior experience in designing and testing software for production environments.
also they need to pay rent
[deleted]
> If you aren't hiring junior engineers to do these kinds of things, where do you think the senior engineers you need in the future will come from?
Money number must always go up. Hiring people costs money. "Oh hey I just read this article, sez you can have A.I. code your stuff, for pennies?"
Money number must always go up. Hiring people costs money. "Oh hey I just read this article, sez you can have A.I. code your stuff, for pennies?"
A junior engineer can always become a senior engineer by using Gemini/ChatGPT to build full systems and literally asking chatGPT, a series of Why questions to every output.
In fact not being bottle necked by senior engineers or not having to drawe the luck of a bad senior engineer/mentor, there will be a new stars of Junior engineers.
What you should be worried is Senior Engineers who hate AI
In fact not being bottle necked by senior engineers or not having to drawe the luck of a bad senior engineer/mentor, there will be a new stars of Junior engineers.
What you should be worried is Senior Engineers who hate AI
Nothing to worry about IME. It takes one or two tasks which AI surprisingly (for them) solves and these guys turn around fast. If they’re religiously against ai, tough luck them.
> My employer has hired recently and the flood of resumes after posting for a relatively low level position was nuts.
I am utterly perplexed with the current situation on the job market, which seems to be a global phenomenon that is not constrained to a particular country or region. Late last year, I was hiring for two junior software engineering positions and (through an external recruitment partner) we received over 400 job applications for two junior positions. We, however, scrambled to narrow the number of candidates down to ten, out of which eight turned out to be lemons and two ended up being exceptionally good. 390 other applicants ended up being pure white noise.
Colleagues in a neighbouring business unit reported receiving over 600 submissions for a single position.
I have approached a few headhunters in the last couple of months with informal questions about what has been happening. They are under constant duress, receiving hundreds upon hundreds of applications for pretty much any position. The feedback is that when most people see a job ad, they put their resume through GenAI and submit whatever garbage comes out of it without even looking at the output. The vast majority of people can't even be bothered to write a simple cover letter, which could have been used as a shibboleth for the hiring manager / recruiter: «I am an intelligent human being, and I am real».
Naturally, the headhunters have responded with GenAI-assisted tools to sift through piles of putrid trash. The side effect is that such good, qualified applicants do not usually get a chance to get screened in.
The situation does not seem to be changing, and the only way out seems to be applying through a professional network or connections. People abusing GenAI are hurting themselves (ironically, GenAI has become pretty good at recognising GenAI-generated content), and they are also hurting pretty much everyone else in the process, and they do not care.
I am utterly perplexed with the current situation on the job market, which seems to be a global phenomenon that is not constrained to a particular country or region. Late last year, I was hiring for two junior software engineering positions and (through an external recruitment partner) we received over 400 job applications for two junior positions. We, however, scrambled to narrow the number of candidates down to ten, out of which eight turned out to be lemons and two ended up being exceptionally good. 390 other applicants ended up being pure white noise.
Colleagues in a neighbouring business unit reported receiving over 600 submissions for a single position.
I have approached a few headhunters in the last couple of months with informal questions about what has been happening. They are under constant duress, receiving hundreds upon hundreds of applications for pretty much any position. The feedback is that when most people see a job ad, they put their resume through GenAI and submit whatever garbage comes out of it without even looking at the output. The vast majority of people can't even be bothered to write a simple cover letter, which could have been used as a shibboleth for the hiring manager / recruiter: «I am an intelligent human being, and I am real».
Naturally, the headhunters have responded with GenAI-assisted tools to sift through piles of putrid trash. The side effect is that such good, qualified applicants do not usually get a chance to get screened in.
The situation does not seem to be changing, and the only way out seems to be applying through a professional network or connections. People abusing GenAI are hurting themselves (ironically, GenAI has become pretty good at recognising GenAI-generated content), and they are also hurting pretty much everyone else in the process, and they do not care.
Tragedy of the commons meets Shannon’s entropy and channel capacity. Noise floor got raised so high information can’t pass through. Personal connections make it possible to communicate out of band.
If this goes on for longer a wework for applicants might be an opportunity.
If this goes on for longer a wework for applicants might be an opportunity.
Your kid with a set of AI’s is going to blow the greybeards out of the water in a few years. They learn and iterate a lot faster. They just accept the latest tech as a given.
- greybeard who is trying his hardest to keep up
- greybeard who is trying his hardest to keep up
Being quite blunt, just a cs degree from a good school has not been enough for quite some time. Research experience, OSS contribs, some specialty (ML, compilers, ...) are a must. I don't find this to be a problem, since it dilutes the value of an ivy league education.
On top of that, you need to be really sharp at leetcode for any large-ish company.
I find the "ai tools are junior engineers" narrative flawed, but it has any way accelerated the higher and higher expectations for a junior.
On top of that, you need to be really sharp at leetcode for any large-ish company.
I find the "ai tools are junior engineers" narrative flawed, but it has any way accelerated the higher and higher expectations for a junior.
I feel for your daughter. I can totally see how tools like this will destroy the junior job market.
But I also wonder (I'm thinking out loud here, so pardon the raw unfiltered thoughts), if being a junior today is unrecognizable.
Like for example, that whatever a "junior" will be now, will have to get better at thinking at a higher level, rather than the minute that we did as juniors (like design patterns and all that stuff).
So maybe the levels of abstraction change?
But I also wonder (I'm thinking out loud here, so pardon the raw unfiltered thoughts), if being a junior today is unrecognizable.
Like for example, that whatever a "junior" will be now, will have to get better at thinking at a higher level, rather than the minute that we did as juniors (like design patterns and all that stuff).
So maybe the levels of abstraction change?
Our company predates AI and still doesn’t make much use of it. It’s not that useful for what we do. We have never had a junior engineering position open. Nothing we do is junior enough. There are literally no jobs in the company doable by someone with less than 5-10 years experience minimum.
This is a very valid concern that predates AI by decades. AI just makes it worse. How will we raise the next generation of experts when there is no entry level of anything? We have either outsourced or automated everything below mid career level.
This is an area that I agree with some on the nationalist right — at least about the diagnosis, but not about the cure. If we continue down this road we end up with abandoned generations struggling to pay bills beneath an entrenched gerontocracy. If we do crack any kind of real age reversing life extension this could get really dystopian, like bad cyberpunk movie stuff, where you have generations of the impoverished beneath a pickled elite that never dies and owns everything.
This is a very valid concern that predates AI by decades. AI just makes it worse. How will we raise the next generation of experts when there is no entry level of anything? We have either outsourced or automated everything below mid career level.
This is an area that I agree with some on the nationalist right — at least about the diagnosis, but not about the cure. If we continue down this road we end up with abandoned generations struggling to pay bills beneath an entrenched gerontocracy. If we do crack any kind of real age reversing life extension this could get really dystopian, like bad cyberpunk movie stuff, where you have generations of the impoverished beneath a pickled elite that never dies and owns everything.
Graduating as a junior is just not enough in a more competitive market like there is now. I don’t think it is related to anything else. If you can hire a developer that is spending 10x time coding or a developer that has studied and graduated, this is not much of a choice. If you don’t have the option than you might go with a junior
Don't shoot the messenger. He's just sharing his experience with the tool and using an anecdotal example.
> If you aren't hiring junior engineers to do these kinds of things, where do you think the senior engineers you need in the future will come from?
Cynical answer for the immediate future: maybe from the pool of existing seniors and principals that have all been stuck doing a faux-management job onboarding, mentoring and managing the juniors who were the only ones actually writing any code in many tech companies? It's a reversal of a trend, for sure: my feeling about the market until the last year or two, was that there's hardly any job for seniors or above, that isn't just management without the title and its privileges.
Past the immediate future, if we end up replacing juniors with LLMs, then the next cohort of "seniors" will need to come from some kind of vocational training.
Cynical answer for the immediate future: maybe from the pool of existing seniors and principals that have all been stuck doing a faux-management job onboarding, mentoring and managing the juniors who were the only ones actually writing any code in many tech companies? It's a reversal of a trend, for sure: my feeling about the market until the last year or two, was that there's hardly any job for seniors or above, that isn't just management without the title and its privileges.
Past the immediate future, if we end up replacing juniors with LLMs, then the next cohort of "seniors" will need to come from some kind of vocational training.
I share your worries, but the time horizon for the supply of senior engineers drying up is just too long for companies to care at this time, in particular if productivity keeps increasing. And it’s completely unclear what the state of the art will be in 20 years; the problem might mostly solve itself.
By the rate at which these things advance I would say the "Seniors" will come from there too. We are transforming into architects or going at higher levels at least. Teach your kids to be better architects instead, code is dying. My 2c at least
> If you aren't hiring junior engineers..., where do you think the senior engineers you need in the future will come from?
This problem might be new to CS, but has happened to other engineers, notably to MechE in the 90's, ChemE in 80's, Aerospace in 70's, etc... due to rapid pace of automation and product commoditization.
The senior jobs will disappear too, or offshored to a developing country: Exxon (India 152 - 78 US) https://jobs.exxonmobil.com/ Chevron (India 159 - 4 US) https://careers.chevron.com/search-jobs
This problem might be new to CS, but has happened to other engineers, notably to MechE in the 90's, ChemE in 80's, Aerospace in 70's, etc... due to rapid pace of automation and product commoditization.
The senior jobs will disappear too, or offshored to a developing country: Exxon (India 152 - 78 US) https://jobs.exxonmobil.com/ Chevron (India 159 - 4 US) https://careers.chevron.com/search-jobs
> The senior jobs will disappear too
Golden age of software development will be over soon? Probably, for humans. How cool is it, the most enthusiastic part will be replaced first.
Golden age of software development will be over soon? Probably, for humans. How cool is it, the most enthusiastic part will be replaced first.
Probably already is over, I would say since the start of the first post-COVID layoffs. Like compare the current average pay in tech including inflation to what was offered like 5 years ago.
2015-2022 was peak, downhill from there and it doesn't look like it'll recover.
2015-2022 was peak, downhill from there and it doesn't look like it'll recover.
> If you aren't hiring junior engineers to do these kinds of things, where do you think the senior engineers you need in the future will come from?
They'll probably just need to learn for longer and if companies ever get so desperate for senior engineers then just take the most able/experienced junior/mid level dev.
But I'd argue before they do that if companies can't find skilled labour domestically they should consider bringing skilled workers from abroad. There are literally hundreds of millions of Indians who got connected to the internet over the last decade. There's no reason a company should struggle to find senior engineers.
They'll probably just need to learn for longer and if companies ever get so desperate for senior engineers then just take the most able/experienced junior/mid level dev.
But I'd argue before they do that if companies can't find skilled labour domestically they should consider bringing skilled workers from abroad. There are literally hundreds of millions of Indians who got connected to the internet over the last decade. There's no reason a company should struggle to find senior engineers.
The junior engineers on my team are just supercharged and their job is different from when I was a junior engineer.
I would say: ten years ago there was a huge shortage of engineers. Today, there is still lots of coding to be done, but everyone is writing code much faster and driven people learn to code to solve their own problems
Part of the reason it was so easy to get hired as a junior ten years ago was because there was so much to do. There will still be demand for engineers for a little while and then it's possible we will all be creating fairly bespoke apps and I'm not sure old me would call what future me does "programming".
I would say: ten years ago there was a huge shortage of engineers. Today, there is still lots of coding to be done, but everyone is writing code much faster and driven people learn to code to solve their own problems
Part of the reason it was so easy to get hired as a junior ten years ago was because there was so much to do. There will still be demand for engineers for a little while and then it's possible we will all be creating fairly bespoke apps and I'm not sure old me would call what future me does "programming".
It's worth keeping in mind that we're probably in a recession at the moment, due to US Executive policies which the tech industry largely disagrees with, and over which it has little influence.
Much like everything in the economy currently, externalities are to be shouldered by "others" and if there is no "other" in aggregate, well, it's not our problem. Yet.
AI might play a role here. But there's also a lot of economic uncertainty.
It's not long ago when the correction of the tech job market started, because it got blown up during and after covid. The geopolitical situation is very unstable.
I also think there is way too much FUD around AI, including coding assistants, than necessary. Typically coming either from people who want to sell it or want to get in on the hype.
Things are shifting and moving, which creates uncertainty. But it also opens new doors. Maybe it's a time for risk takers, the curious, the daring. Small businesses and new kinds of services might rise from this, like web development came out of the internet revolution. To me, it seems like things are opening up and not closing down.
Besides that, I bet there are more people today who write, read or otherwise deal directly with assembly code than ever before, even though we had higher level languages for many decades.
As for the job market specifically: SWE and CS (adjacent) jobs are still among the fastest growing, coming up in all kinds of lists.
It's not long ago when the correction of the tech job market started, because it got blown up during and after covid. The geopolitical situation is very unstable.
I also think there is way too much FUD around AI, including coding assistants, than necessary. Typically coming either from people who want to sell it or want to get in on the hype.
Things are shifting and moving, which creates uncertainty. But it also opens new doors. Maybe it's a time for risk takers, the curious, the daring. Small businesses and new kinds of services might rise from this, like web development came out of the internet revolution. To me, it seems like things are opening up and not closing down.
Besides that, I bet there are more people today who write, read or otherwise deal directly with assembly code than ever before, even though we had higher level languages for many decades.
As for the job market specifically: SWE and CS (adjacent) jobs are still among the fastest growing, coming up in all kinds of lists.
> It seems that, relatively speaking, there's a lot of postings for senior engineers and very little for new grads.
That's been the case for most of the last 15 years in my experience. You have to follow local job markets, get in through an internship, or walk in at local companies and ask. Applying en mass can also help, and so does having some code on GitHub to show off.
That's been the case for most of the last 15 years in my experience. You have to follow local job markets, get in through an internship, or walk in at local companies and ask. Applying en mass can also help, and so does having some code on GitHub to show off.
i think there's an opportunity here
a lot of junior eng tasks don't really help you become a senior engineer. someone needs to make a form and a backend API for it to talk to, because it's a business need. but doing 50 of those doesn't really impart a lot of wisdom
same with writing tests. you'll probably get faster at writing tests, but that's about it. knowing that you need the tests, and what kinds of things might go wrong, is the senior engineer skill
with the LLMs current ability to help people research a topic, and their growing ability to write functioning code, my hunch is that people with the time to spare can learn senior engineer skills while bypassing being a junior engineer
convincing management of that is another story, though. if you can't afford to do unpaid self-directed study, it's probably going to be a bumpy road until industry figures out how to not eat the seed corn
a lot of junior eng tasks don't really help you become a senior engineer. someone needs to make a form and a backend API for it to talk to, because it's a business need. but doing 50 of those doesn't really impart a lot of wisdom
same with writing tests. you'll probably get faster at writing tests, but that's about it. knowing that you need the tests, and what kinds of things might go wrong, is the senior engineer skill
with the LLMs current ability to help people research a topic, and their growing ability to write functioning code, my hunch is that people with the time to spare can learn senior engineer skills while bypassing being a junior engineer
convincing management of that is another story, though. if you can't afford to do unpaid self-directed study, it's probably going to be a bumpy road until industry figures out how to not eat the seed corn
We have seen this in other industries and professions.
As everything is so new and different at this stage we are in a state of discovery which requires more senior skills to work out the lay of the land.
As we progress, create new procedures, processes, and practices, particularly guardrails then hiring new juniors will become the focus.
As everything is so new and different at this stage we are in a state of discovery which requires more senior skills to work out the lay of the land.
As we progress, create new procedures, processes, and practices, particularly guardrails then hiring new juniors will become the focus.
[deleted]
> If you aren't hiring junior engineers to do these kinds of things, where do you think the senior engineers you need in the future will come from?
Hasn't this been a common refrain whenever someone found a way to automate any menial task in any job?
Hasn't this been a common refrain whenever someone found a way to automate any menial task in any job?
This may be unpopular/counter-intuitive to say, but in a capitalist world this is probably the best outcome IF (and I'm not saying I can predict the future) we expect the profession to die/be obsolete from a society POV - in such a world restricting juniors before they commit a whole career to that profession and invest too much resources into it is actually the outcome we probably want. Better than the alternative of even more mass unemployment later. If that's the case then giving people that info early, and avoiding more hiring/training now stops potential mal-investment of money and people's time into training/hiring/building careers in/etc.
It stops juniors investing their life/time/energy in a field that is shrinking and that will increasingly "not be worth it" w.r.t effort put in given their longer time horizon. This is how capitalism when working correctly can obsolete jobs somewhat charitably - it does it by closing the door on entry level jobs ideally when people have little to lose and haven't yet invested a lot of their life into it. For example they may still be young enough to re-train; or may be dismayed from entering the field due to disruption/chatter and so do something more appropriate in the new world.
Being hired in a sinking and increasingly more competitive field may actually be considered a "winner's curse" outcome, in that you will be in a industry highly competitive that is slowly sinking and is stressful with low opportunities for pay rises compared to other industries/skill sets - this is definitely playing your career in "hard mode". Most of all you will feel your skills, and value is useless relatively to people who got into more jobs with more scarcity playing life in "easy mode" with less stress and anxiety. In a few years time people getting into other fields may feel they "dodged a bullet" comparing themselves to others that did.
Being able to pivot while you are still young and ageism isn't a barrier yet is definitely something to consider remembering careers these days are multi-decades long. I feel for your kid now, and I do for mine, but I would rather than try something different in their 20's vs say their 40's when they have a mortgage, a family to feed, and/or other commitments and ageism makes it harder to pivot/re-train into another career. I don't wish my kids to feel the anxiety I and many people I know are feeling later in life especially for a career that requires constant effort to maintain and keep relevant in. I'm not recommending my kids learn what I do at all for example.
It stops juniors investing their life/time/energy in a field that is shrinking and that will increasingly "not be worth it" w.r.t effort put in given their longer time horizon. This is how capitalism when working correctly can obsolete jobs somewhat charitably - it does it by closing the door on entry level jobs ideally when people have little to lose and haven't yet invested a lot of their life into it. For example they may still be young enough to re-train; or may be dismayed from entering the field due to disruption/chatter and so do something more appropriate in the new world.
Being hired in a sinking and increasingly more competitive field may actually be considered a "winner's curse" outcome, in that you will be in a industry highly competitive that is slowly sinking and is stressful with low opportunities for pay rises compared to other industries/skill sets - this is definitely playing your career in "hard mode". Most of all you will feel your skills, and value is useless relatively to people who got into more jobs with more scarcity playing life in "easy mode" with less stress and anxiety. In a few years time people getting into other fields may feel they "dodged a bullet" comparing themselves to others that did.
Being able to pivot while you are still young and ageism isn't a barrier yet is definitely something to consider remembering careers these days are multi-decades long. I feel for your kid now, and I do for mine, but I would rather than try something different in their 20's vs say their 40's when they have a mortgage, a family to feed, and/or other commitments and ageism makes it harder to pivot/re-train into another career. I don't wish my kids to feel the anxiety I and many people I know are feeling later in life especially for a career that requires constant effort to maintain and keep relevant in. I'm not recommending my kids learn what I do at all for example.
I would like to take this moment to point out that in NY it is ~illegal for me to hire an unpaid intern and train them by for example saying:
- this is codex, here is a bunch of tickets
- enter each ticket into codex, then review each change and understand what it did. if you think what it did is good, open a PR
- twice a day we will meet and i will review all the codex PRs with you and explain what is and isn't working
etc.
This would not save me time. It would be paying it forward. And I cannot do this.
etc.
This would not save me time. It would be paying it forward. And I cannot do this.
There aren't going to be senior engineers in the future.
This is exactly the problem. The top level executives are setting up to retire with billions in the bank, while the workers develop their own replacements before they retire with millions in the bank. Senior developers will be mostly obsolete too.
I have mentored junior developers and found it to be a rewarding part of the job. My colleagues mostly ignore juniors, provide no real guidance, couldn't care less. I see this attitude from others in the comments here, relieved they don't have to face that human interaction anymore. There are too many antisocial weirdos in this industry.
Without a strong moral and cultural foundation the AGI paradigm will be a dystopia. Humans obsolete across all industries.
I have mentored junior developers and found it to be a rewarding part of the job. My colleagues mostly ignore juniors, provide no real guidance, couldn't care less. I see this attitude from others in the comments here, relieved they don't have to face that human interaction anymore. There are too many antisocial weirdos in this industry.
Without a strong moral and cultural foundation the AGI paradigm will be a dystopia. Humans obsolete across all industries.
> I have mentored junior developers and found it to be a rewarding part of the job.
Can totally relate. Unfortunately the trend for all-senior teams and companies has started long before ChatGPT, so the opportunities have been quite scarce, at least in a professional environment.
Can totally relate. Unfortunately the trend for all-senior teams and companies has started long before ChatGPT, so the opportunities have been quite scarce, at least in a professional environment.
> I have mentored junior developers and found it to be a rewarding part of the job.
That's really awesome. I hope my daughter finds a job somewhere that values professional development. I'd hate for her to quit the industry before she sees just how interesting and rewarding it can be.
I didn't have many mentors when starting out, but the ones I had were so unbelievably helpful both professionally and personally. If I didn't have their advice and encouragement, I don't think I'd still be doing what I'm doing.
That's really awesome. I hope my daughter finds a job somewhere that values professional development. I'd hate for her to quit the industry before she sees just how interesting and rewarding it can be.
I didn't have many mentors when starting out, but the ones I had were so unbelievably helpful both professionally and personally. If I didn't have their advice and encouragement, I don't think I'd still be doing what I'm doing.
She can try to reach out to possible mentors / people on Linkedin. A bit like cold calling. It works, people (usually) want to help and don't mind sharing their experiences / tips. I know I have helped many random linedin cold messages from recent grads/people in uni
Depending on corporations to have a moral foundation is a losing bet. It has to come from the outside.
Here’s a possible out: Senior engineers stop working huge corporations and use these tools to start their own businesses. (Given today’s hiring situation, this may not even be a choice.) As the business grows, hire junior developers as apprentices to handle day to day tasks while senior engineer works on bigger picture stuff. Junior engineer grows into a senior engineer who eventually uses AI to start their own business. This is a very abbreviated version of what I hope I can do, at least.
Here’s a possible out: Senior engineers stop working huge corporations and use these tools to start their own businesses. (Given today’s hiring situation, this may not even be a choice.) As the business grows, hire junior developers as apprentices to handle day to day tasks while senior engineer works on bigger picture stuff. Junior engineer grows into a senior engineer who eventually uses AI to start their own business. This is a very abbreviated version of what I hope I can do, at least.
So depending on people to do harder work for less pay--that is the winning bet?
Your solution cannot work at scale, because if the small companies you propose succeed, then they will become corporations, which, as you say, cannot be depended upon to do the right thing.
Your solution cannot work at scale, because if the small companies you propose succeed, then they will become corporations, which, as you say, cannot be depended upon to do the right thing.
[deleted]
[deleted]
The never ending march of progress.
It's probably over for these folks.
There will likely(?, hopefully?) be new adjacent gradients for people to climb.
In any case, I would worry more about your own job prospects. It's coming for everyone.
It's probably over for these folks.
There will likely(?, hopefully?) be new adjacent gradients for people to climb.
In any case, I would worry more about your own job prospects. It's coming for everyone.
It's his daughter. He is worried about his daughter first and foremost. Weird reply.
I'm sorry. I was skimming. I had no idea he mentioned his kid.
I was running a quick errand between engineering meetings and saw the first few lines about hiring juniors, and I wrote a couple of comments about how I feel about all of this.
I'm not always guilty of skimming, but today I was.
I was running a quick errand between engineering meetings and saw the first few lines about hiring juniors, and I wrote a couple of comments about how I feel about all of this.
I'm not always guilty of skimming, but today I was.
dakiol(3)
In the preview video, I appreciated Katy Shi's comment on "I think this is a reflection of where engineering work has moved over the past where a lot of my time now is spent reviewing code rather than writing it."
Preview video from Open AI: https://www.youtube.com/watch?v=hhdpnbfH6NU&t=878s
As I think about what "AI-native" or just the future of building software loos like, its interesting to me that - right now - developers are still just reading code and tests rather than looking at simulations.
While a new(ish) concept for software development, simulations could provide a wider range of outcomes and, especially for the front end, are far easier to evaluate than just code/tests alone. I'm biased because this is something I've been exploring but it really hit me over the head looking at the Codex launch materials.
Preview video from Open AI: https://www.youtube.com/watch?v=hhdpnbfH6NU&t=878s
As I think about what "AI-native" or just the future of building software loos like, its interesting to me that - right now - developers are still just reading code and tests rather than looking at simulations.
While a new(ish) concept for software development, simulations could provide a wider range of outcomes and, especially for the front end, are far easier to evaluate than just code/tests alone. I'm biased because this is something I've been exploring but it really hit me over the head looking at the Codex launch materials.
> a lot of my time now is spent reviewing code rather than writing it.
Reviewing has never been a panacea. It’s a best-effort at catching obvious mistakes, like a second opinion. Only with highly rigorous tests can reviewing give as high confidence as I trust another engineer or myself. Generally cadence of code output has never been a bottleneck for me, rather the opposite (if I had more time I’d write you a shorter letter).
Most importantly, writing code that is testable on meaningful boundaries is an extremely difficult and delicate art form, which ime is something you really want to get right if possible. Not saying an AI can or can’t do that, only that it’s the hardest part. An army of automated junior engineers still can’t win over the complexity beast that yolo programming causes. At some point code mutations will cause more problems as side effects than what they fix.
Reviewing has never been a panacea. It’s a best-effort at catching obvious mistakes, like a second opinion. Only with highly rigorous tests can reviewing give as high confidence as I trust another engineer or myself. Generally cadence of code output has never been a bottleneck for me, rather the opposite (if I had more time I’d write you a shorter letter).
Most importantly, writing code that is testable on meaningful boundaries is an extremely difficult and delicate art form, which ime is something you really want to get right if possible. Not saying an AI can or can’t do that, only that it’s the hardest part. An army of automated junior engineers still can’t win over the complexity beast that yolo programming causes. At some point code mutations will cause more problems as side effects than what they fix.
> An army of automated junior engineers still can’t win over the complexity beast that yolo programming causes. At some point code mutations will cause more problems as side effects than what they fix.
This resonates a lot for me, completely agreed.
This resonates a lot for me, completely agreed.
++ Kind of my whole thesis with Graphite. As more code gets AI-generated, the weight shifts to review, testing, and integration. Even as someone helping build AI code reviewers, we'll _need_ humans stamping forever - for many reasons, but fundamentally for accountability. A computer can never be held accountable
https://constelisvoss.com/pages/a-computer-can-never-be-held...
https://constelisvoss.com/pages/a-computer-can-never-be-held...
> A computer can never be held accountable
I think the issue is not about humans being entirely replaced. Instead, the issue is that if AI replaces enough number of knowledge workers while there's no new or expanded market to absorb the workforce, the new balance of supply and demand will mean that many of us will have suppressed pay or worse, losing our jobs forever.
I think the issue is not about humans being entirely replaced. Instead, the issue is that if AI replaces enough number of knowledge workers while there's no new or expanded market to absorb the workforce, the new balance of supply and demand will mean that many of us will have suppressed pay or worse, losing our jobs forever.
That is true regardless of whether there is or isn't a "new or expanded market to absorb the workforce".
It's a crucial insight that's usually missed or eluded in discussions about automation and workforce - unless you're literally at the beginning of your career, losing your career to automation screws you over big time, forever. At best, you'll have to downsize your entire lifestyle, and that of your family, to be commensurate with your now entry-level pay. If you're halfway through the career that suddenly ended, you won't recover.
All the new jobs and markets are for the kids. Mind you, not your kids - your kids are going to be disadvantaged by their household being suddenly thrown into financial insecurity or downright poverty, and may not even get a chance to start a good career path with their peers.
That, not "anti technology sentiment", is why Luddites smashed the looms. Those were people who got rug-pulled by business decisions and thrown into poverty, along with their families and communities.
It's a crucial insight that's usually missed or eluded in discussions about automation and workforce - unless you're literally at the beginning of your career, losing your career to automation screws you over big time, forever. At best, you'll have to downsize your entire lifestyle, and that of your family, to be commensurate with your now entry-level pay. If you're halfway through the career that suddenly ended, you won't recover.
All the new jobs and markets are for the kids. Mind you, not your kids - your kids are going to be disadvantaged by their household being suddenly thrown into financial insecurity or downright poverty, and may not even get a chance to start a good career path with their peers.
That, not "anti technology sentiment", is why Luddites smashed the looms. Those were people who got rug-pulled by business decisions and thrown into poverty, along with their families and communities.
> A computer can never be held accountable
I feel like I've been thinking along similar lines recently (due to re-read this though!) but instead of "computer" am replacing it with "AI" or "Agents" these days. Same point holds true.
I feel like I've been thinking along similar lines recently (due to re-read this though!) but instead of "computer" am replacing it with "AI" or "Agents" these days. Same point holds true.
> I think this is a reflection of where engineering work has moved over the past where a lot of my time now is spent reviewing code rather than writing it.
This was always true. Front-End code is not really code. Most of the back-end code is just convert and moving data around. For most functionality where you need "real code" like crypto, compression, math, etc.. you use a library used by another 100k developers.
This was always true. Front-End code is not really code. Most of the back-end code is just convert and moving data around. For most functionality where you need "real code" like crypto, compression, math, etc.. you use a library used by another 100k developers.
Re:simulation
Deebo does this for debugging:
https://github.com/snagasuri/deebo-prototype
Thanks for sharing - wasn't familiar with Deebo!
> rather than looking at simulations
You mean like automated test suites?
You mean like automated test suites?
automated visual fuzzy-testing with some self-reinforcement loops
There's already library's for QA testing and VLM's can give critique on a series of screenshots automated by a playwright script per branch
There's already library's for QA testing and VLM's can give critique on a series of screenshots automated by a playwright script per branch
Cool. Putting vision in the loop is a great idea.
Ambitious idea, but I like it.
Ambitious idea, but I like it.
I used Cline to build a tiny testing helper app and this is exactly what it did!
It made changes in TS/Next.js given just the boiletplate from create-next-app, ran `yarn dev` then opened its mini LLM browser and navigated to localhost to verify everything looked correct.
It found 1 mistake and fixed the issue then ran `yarn dev` again, opened a new browser, navigated to localhost (pointing at the original server it brought up, not the new one at another port) and confirmed the change was correct.
I was very impressed but still laughed at how it somehow backed its way into a flow the worked, but only because Next has hot-reloading.
It made changes in TS/Next.js given just the boiletplate from create-next-app, ran `yarn dev` then opened its mini LLM browser and navigated to localhost to verify everything looked correct.
It found 1 mistake and fixed the issue then ran `yarn dev` again, opened a new browser, navigated to localhost (pointing at the original server it brought up, not the new one at another port) and confirmed the change was correct.
I was very impressed but still laughed at how it somehow backed its way into a flow the worked, but only because Next has hot-reloading.
SmolVLM, Gemma, LlaVa, in case you wanna play with some of the ones i've tried.
https://huggingface.co/blog/smolvlm
recently both llama.cpp and ollama got better support for them too, which makes this kind of integration with local/self-hosted models now more attainable/less expensive
https://huggingface.co/blog/smolvlm
recently both llama.cpp and ollama got better support for them too, which makes this kind of integration with local/self-hosted models now more attainable/less expensive
also this for the visual regression testing parts, but you can add some AI onto the mix ;) https://github.com/lost-pixel/lost-pixel
Yes, the above reply is more what I meant! Vision / visualization not just more automated testing.
Definitely ambitious!
Definitely ambitious!
[I'm one of the co-creators of SWE-bench] The team managed to improve on the already very strong o3 results on SWE-bench, but it's interesting that we're just seeing an improvement of a few percentage points. I wonder if getting to 85% from 75% on Verified is going to take as long as it took to get from 20% to 75%.
I can be completely off base, but it feels to me like benchmaxxing is going on with swe-bench.
Look at the results from multi swe bench - https://multi-swe-bench.github.io/#/
swe polybench - https://amazon-science.github.io/SWE-PolyBench/
Kotlin bench - https://firebender.com/leaderboard
Look at the results from multi swe bench - https://multi-swe-bench.github.io/#/
swe polybench - https://amazon-science.github.io/SWE-PolyBench/
Kotlin bench - https://firebender.com/leaderboard
I kind of had the feeling LLMs would be better at Python vs other languages, but wow, the difference on Multi SWE is pretty crazy.
Maybe a lot of the difference we see between peoples comments about how useful AI is for their coding, is a function of what language they're using. Python coders may love it, Go coders not much at all.
Not sure what you mean by benchmaxxing but we think there's still a lot of useful signals you can infer from SWE-bench-style benchmarking.
We also have SWE-bench Multimodal which adds a twist I haven't seen elsewhere: https://www.swebench.com/multimodal.html
We also have SWE-bench Multimodal which adds a twist I haven't seen elsewhere: https://www.swebench.com/multimodal.html
I mean that there is the possibility that swe bench is being specifically targeted for training and the results may not reflect real world performance.
How long did it take to go from 20% to 75%?
They mentioned "microVM" in the live stream. Notably there's no browser or internet access. It makes sense, running specialized Firecracker/Unikraft/etc microkernels is way faster and cheaper so you can scale it up. But there will be a big technical scalability difficulty jump from this to the "agents with their own computers". ChatGPT Operator already does have a browser, so they definitely can do this, but I imagine the demand is orders of magnitudes different.
There must be room for a Modal/Cloudflare/etc infrastructure company that focuses only on providing full-fledged computer environments specifically for AI with forking/snapshotting (pause/resume), screen access, human-in-the-loop support, and so forth, and it would be very lucrative. We have browser-use, etc, but they don't (yet) capture the whole flow.
There must be room for a Modal/Cloudflare/etc infrastructure company that focuses only on providing full-fledged computer environments specifically for AI with forking/snapshotting (pause/resume), screen access, human-in-the-loop support, and so forth, and it would be very lucrative. We have browser-use, etc, but they don't (yet) capture the whole flow.
It's not our only focus at Modal but it's a big focus![1] Code agents are the killer use case for LLMs right now, and this complements our GPU inference and training capabilities.
I'm quietly betting that agents increase the leverage of deterministic, reproducible devbox tech (eg. Nix, lockfiles, package mirroring), and this will end up being a huge win for us human engineers too.
1. https://modal.com/use-cases/sandboxes
I'm quietly betting that agents increase the leverage of deterministic, reproducible devbox tech (eg. Nix, lockfiles, package mirroring), and this will end up being a huge win for us human engineers too.
1. https://modal.com/use-cases/sandboxes
we offer this with E2B Desktop
Demo: https://surf.e2b.dev
SDK: https://github.com/e2b-dev/desktop
Demo: https://surf.e2b.dev
SDK: https://github.com/e2b-dev/desktop
Im sorry if Im being silly, but I have paid for the Pro version, $200 a month, everytime I click on Try Codex, it takes me to a pricing page with the "Team Plan" https://chatgpt.com/codex#pricing.
Is this still rolling out? I dont need the team plan too do I?
I have been using openAI products for years now and I am keen to try but I have no idea what I am doing wrong.
Is this still rolling out? I dont need the team plan too do I?
I have been using openAI products for years now and I am keen to try but I have no idea what I am doing wrong.
They do this with every major release. Never going to understand why.
I'm not sure what's wrong with me, but I just wasted several hours wrestling codex to make it behave.
Here's my workflow that keeps failing: - it writes some code. It looks good a first glance - I push it to github - automated tests on github show that there's a problem - go back to codex and ask it to fix it - it does stuff. It looks good again.
Now what do I do? If I ask it to push again to github, then it will often create a pull request that doesn't include stuff from the first pull request, but it's not a pull request that stacks on top of the previous pull request, it's a pull request that stacks on top of main.
When asked to write something that called out to gpt-4.1-mini, it used openai.ChatCompletion.create (!?!!?)
I just found myself using claude to fix codex's mistakes.
Here's my workflow that keeps failing: - it writes some code. It looks good a first glance - I push it to github - automated tests on github show that there's a problem - go back to codex and ask it to fix it - it does stuff. It looks good again.
Now what do I do? If I ask it to push again to github, then it will often create a pull request that doesn't include stuff from the first pull request, but it's not a pull request that stacks on top of the previous pull request, it's a pull request that stacks on top of main.
When asked to write something that called out to gpt-4.1-mini, it used openai.ChatCompletion.create (!?!!?)
I just found myself using claude to fix codex's mistakes.
I upgraded to Pro just because of Codex and I am really not impressed. Granted, I am using rust so that may be the issue (or skill issue on my end too).
One of the things I am constantly struggling with is that the containers they use are having issues to fetch anything from the internet:
One of the things I am constantly struggling with is that the containers they use are having issues to fetch anything from the internet:
error: failed to get `anyhow` as a dependency of package `yawl-core v0.1.0 (/wor
kspace/yawl/core)`
Caused by:
download of config.json failed
Caused by:
failed to download from `https://index.crates.io/config.json`
Caused by:
[7] Could not connect to server (Failed to connect to proxy port 8080 after 30 65 ms: Could not connect to server)
You can specify a startup script for your environment in the Edit -> adbvaned section. The code placed there will run before they cut off the internet access. Also worth noting that it uses a proxy stored in $http_proxy.
Took me an few hours today to figure out how to install maven and have it download all the dependencies. Spent an hour trying to figure out why sudo apt-get update was failing, it was because I was was using sudo!
Took me an few hours today to figure out how to install maven and have it download all the dependencies. Spent an hour trying to figure out why sudo apt-get update was failing, it was because I was was using sudo!
I have this issue with Devin. Given my limited knowledge of how these work, I believe there is simply too much context for it to take a holistic view of the task and finish accordingly.
If both OpenAI and Devin are falling into the same pattern then that’s a good indication there’s a fundamental problem to be solved here.
If both OpenAI and Devin are falling into the same pattern then that’s a good indication there’s a fundamental problem to be solved here.
I think you need to run the tests locally before you push the PR. I actually think you need to (somehow?) make this part of the generation process before Codex proposes the changes.
I used to work for a bank and the legal team used to ping us to make tiny changes to the app for compliance related issues. Now they can fix themselves. I think they’d be very proud and happy
Hopefully nobody lets legal touch anything without the ability to run the code to test it, plus code reviews. So probably not.
I'm not sure what you are on about?
You can make arbitrary teams, like legal, make PRs. You would still have the proper owners of the project agree whether they take the PRs. Either by human review and/or by any other review process they set up.
You can make arbitrary teams, like legal, make PRs. You would still have the proper owners of the project agree whether they take the PRs. Either by human review and/or by any other review process they set up.
I am on about the fact that you are imagining something working in a way that it does not work in practice.
You have two choices:
1. A developer makes a PR. They build the app and run it themselves to make sure it works, does what they intended, and nothing unexpected happens, and report on their testing in the PR. There's also a suite of automated tests. Between these you are confident that you can rubber-stamp it without touching the change yourself. But this requires them being able to run the code and intelligently think about it themselves, which AI cannot do.
2. A non-developer uses an LLM to make a PR. The change passes the tests, but you have no other validation about it because it was done by a bot that can't think about how the app actually works. As reviewer you have to pull down the change to run and validate it yourself. Now you are doing the same amount of work as before, except that instead of you telling the LLM to make the change, someone else did.
The only difference is maybe that the activation energy for doing the work was avoided. Which, fine, is non-negligible. But let's not pretend like in the latter case legal "made the change". They did the 1% upfront work of asking the LLM to find where the change goes, and left you the other 99% of actually shepherding it through. The only changes that will work for at all are, like, updating copy/strings/icons---and honestly, at my last job at least, we already let legal (and product, etc) do stuff like that. I suppose the LLM might save them having to figure out how to use Git, at least.
You might imagine there's some software out there where the automated tests are so thorough that you can trust a code change to not break anything if it passes the tests. I have personally never seen such a thing. And in practice many tests validate against strings and other small feature-level details, meaning that the kinds of code changes that other orgs are making are going to be touching the tests as well, so human verification is still required.
You have two choices:
1. A developer makes a PR. They build the app and run it themselves to make sure it works, does what they intended, and nothing unexpected happens, and report on their testing in the PR. There's also a suite of automated tests. Between these you are confident that you can rubber-stamp it without touching the change yourself. But this requires them being able to run the code and intelligently think about it themselves, which AI cannot do.
2. A non-developer uses an LLM to make a PR. The change passes the tests, but you have no other validation about it because it was done by a bot that can't think about how the app actually works. As reviewer you have to pull down the change to run and validate it yourself. Now you are doing the same amount of work as before, except that instead of you telling the LLM to make the change, someone else did.
The only difference is maybe that the activation energy for doing the work was avoided. Which, fine, is non-negligible. But let's not pretend like in the latter case legal "made the change". They did the 1% upfront work of asking the LLM to find where the change goes, and left you the other 99% of actually shepherding it through. The only changes that will work for at all are, like, updating copy/strings/icons---and honestly, at my last job at least, we already let legal (and product, etc) do stuff like that. I suppose the LLM might save them having to figure out how to use Git, at least.
You might imagine there's some software out there where the automated tests are so thorough that you can trust a code change to not break anything if it passes the tests. I have personally never seen such a thing. And in practice many tests validate against strings and other small feature-level details, meaning that the kinds of code changes that other orgs are making are going to be touching the tests as well, so human verification is still required.
The non-developer can also kick off a build and test the app.
So they can at least check whether the change does what they wanted it to do.
For this to be useful, the code doesn't even have to be good: think of it as a more accurate way to gather requirements and make a prototype. That's useful, even if you throw away the code.
So they can at least check whether the change does what they wanted it to do.
For this to be useful, the code doesn't even have to be good: think of it as a more accurate way to gather requirements and make a prototype. That's useful, even if you throw away the code.
I've never heard of a nondeveloper having a dev environment set up for testing. Often that can quite technical.
You set it up for them automatically for them. Just like you set up a new environment automatically from scratch each time you run tests or when running the AI. See eg https://code.visualstudio.com/docs/devcontainers/containers or https://github.com/features/codespaces for some established standards for doing this, but you could also roll your own custom system.
GitHub's codespaces also drive home how the customer/user only needs a browser, which even people in legal will have. No additional software required on their end.
GitHub's codespaces also drive home how the customer/user only needs a browser, which even people in legal will have. No additional software required on their end.
that will be an interesting new Bug tracker: anyone in the company will be able to report any bug or add any future request, if the model will be able to solve it automatically perfect otherwise some human might take over. The interesting question then will be what code changes are legal and within the standards of what the company wants. So non-technical code/issue reviewer will become a super important and ubiquitous job.
Not just legal/within the standards, but which actually meet the unspoken requirements of the request. "We just need a new checkbox that asks if you're left handed" might seem easy, but then it has ramifications for the Application PDF that gets generated, as well as any systems downstream, and maybe it requires a data conversion of some sort somewhere. I know that the PO's I work with miss stuff or assume that the request will just have features by default.
I promise you the legal team is not pushing any code changes
All they need is "vibes".
[deleted]
"23 SWE-Bench Verified samples that were not runnable on our internal infrastructure were excluded."
What does that mean? Surely this should have a bit more elaboration. If you're just excluding a double digit number of tasks in the benchmark as uncompleted, that should be reflected in the scores.
What does that mean? Surely this should have a bit more elaboration. If you're just excluding a double digit number of tasks in the benchmark as uncompleted, that should be reflected in the scores.
is the point of this to actually assign tasks to an AI to complete end to end? Every task I do with AI requires atleast some bit of hand holding, sometimes reprompting etc. So I don't see why I would want to run tasks in parallel, I don't think it would increase throughput. Curious if others have better experiences with this
The example use-cases in the videos are pretty compelling and much smaller scope.
“Here’s an error reported to the oncall. Give a try fixing it” (Could be useful even if it fails)
Refactor this small piece I noticed while doing something else. Small-scoped stuff that likely wouldn’t get done otherwise.
I wouldn’t ask LLMs for full-features in a real codebase but these examples seem within the scope of what they might be able to accomplish end-to-end
“Here’s an error reported to the oncall. Give a try fixing it” (Could be useful even if it fails)
Refactor this small piece I noticed while doing something else. Small-scoped stuff that likely wouldn’t get done otherwise.
I wouldn’t ask LLMs for full-features in a real codebase but these examples seem within the scope of what they might be able to accomplish end-to-end
I am working with a 3rd party API (Exa.ai) and I hacked together a python script.
I ran a remote agent to do these tasks simultaneously (augment.new, I’m not affiliated, I have early access)
Agent 1: write tests, make sure all the tests pass.
Agent 2: concert python script to fastapi
Agent 3: create frontend based on fastapi endpoints
I get a PR, I check code and see if it works and then merge to main. All three PR’s worked flawlessly (front end wasn’t pretty).
Agent 1: write tests, make sure all the tests pass.
Agent 2: concert python script to fastapi
Agent 3: create frontend based on fastapi endpoints
I get a PR, I check code and see if it works and then merge to main. All three PR’s worked flawlessly (front end wasn’t pretty).
with a bad ai it is pointless, with a good ai it is powerful.
codex-1 has been quite good in my experience
codex-1 has been quite good in my experience
Reading these threads its clear to me people are so cooked and no longer understand (or perhaps never did) understand the simple process of how source code is shared, built, and merged together with multiple editors has ever worked
What about privacy, training opt out?
What about using it for AI / developing models that compete with our new overlords?
Seems like using this is just asking to get rug pulled for competing with em when they release something that competes with your thing. Am I just an old who’s crowing about nothing? It’s ok for them to tell us we own outputs we can’t use to compete with em?
What about using it for AI / developing models that compete with our new overlords?
Seems like using this is just asking to get rug pulled for competing with em when they release something that competes with your thing. Am I just an old who’s crowing about nothing? It’s ok for them to tell us we own outputs we can’t use to compete with em?
What the video: there is an explicit switch at one of the steps about (not) allowing to train on your repo.
That’s nice. And we trust that it does what it says because…? The AI company (openai, anthropic, etc) pinky promised? Have we seen their source code? How do you know they don’t train?
Facebook has been caught in recent DOJ hearings breaking the law with how they run their business, just as one example. They claimed under oath, previously, to not be doing X, and then years later there was proof they did exactly that.
https://youtu.be/7ZzxxLqWKOE?si=_FD2gikJkSH1V96r
A companies “word” means nothing imo. None of this makes sense if i’m being honest. Unless you personally have a negotiated contract with the provider, and can somehow be certain they are doing what they claim, and can later sue for damages, all of this is just crossing your fingers and hoping for the best.
Facebook has been caught in recent DOJ hearings breaking the law with how they run their business, just as one example. They claimed under oath, previously, to not be doing X, and then years later there was proof they did exactly that.
https://youtu.be/7ZzxxLqWKOE?si=_FD2gikJkSH1V96r
A companies “word” means nothing imo. None of this makes sense if i’m being honest. Unless you personally have a negotiated contract with the provider, and can somehow be certain they are doing what they claim, and can later sue for damages, all of this is just crossing your fingers and hoping for the best.
Just curious: is your company happy sharing their code-base with an AI provider? Or are you using a local installation?
Companies commonly share their code with SAAS providers. Typically they'll have a contract to prevent usage otherwise.
why not? OpenAI won't be stupid to look at my code and be that vulnerable legally. It ain't worth it.
They literally scraped half of youtube, made a library to extract the audio and released it as whisper.
Of _course_ they are training on your shit.
Of _course_ they are training on your shit.
thats publicly accessible shit. my code is trade secret and IP. I would litigate that shit if a line I wrote ends up in public model, easiest money to be made.
> my code is trade secret and IP
Which is the same law that protects "publicly accessible shit".
In the same way that you can't legally just rip MP3s off the internet[1], or copy movies and distribute them.
[1] unless you're rich.
Which is the same law that protects "publicly accessible shit".
In the same way that you can't legally just rip MP3s off the internet[1], or copy movies and distribute them.
[1] unless you're rich.
you will litigate nothing, and if you do you'll be dismissed anyway.
https://en.wikipedia.org/wiki/Shira_Perlmutter#Firing
https://en.wikipedia.org/wiki/Shira_Perlmutter#Firing
For 99% of companies, their code is worthless to anyone but them.
For copying the product / service yes it is not worth much .
However for people trying to compromise your system access to your code can be a valuable asset .The worth of that could be well beyond just enterprise value of the organization , it could people’s lives or bring down critical infrastructure.
You don’t just have access to code you created and have complete control to. Organizations have vendors providing code(drivers , libraries…) with narrow licenses that prohibit sharing or leaking in anyway. So this type of leak can open you to a lot of liability.
However for people trying to compromise your system access to your code can be a valuable asset .The worth of that could be well beyond just enterprise value of the organization , it could people’s lives or bring down critical infrastructure.
You don’t just have access to code you created and have complete control to. Organizations have vendors providing code(drivers , libraries…) with narrow licenses that prohibit sharing or leaking in anyway. So this type of leak can open you to a lot of liability.
If that was true, hardly any company would be opposed to open sourcing their code base.
It is a cost benefit trade off, as with all things. Benefits look pretty good.
The cost of sharing your code is unknown, though.
Under what circumstances would that cost be high? Is OpenAI going to rip off your app? Why would they waste a second on that when there are better models to be built?
(watching live) I'm wondering how it performs on the METR benchmark (https://metr.org/blog/2025-03-19-measuring-ai-ability-to-com...).
I really wish they'd add support for Gitlab or better any arbitrary git repo.
Well, Microsoft bought GitHub and Microsoft sort-of co-owns OpenAI, too.
So it's looking like it's only running in the cloud, that is it will push commits to my remote repo before I have a chance to see if it works?
When I'm using aider, after it make a commit what I do, I then immediately run git reset HEAD^ and then git diff (actually I use github desktop client to see the diff) to evaluate what exactly it did, and if I like it or not. Then I usually make some adjustments and only after that commit and push.
When I'm using aider, after it make a commit what I do, I then immediately run git reset HEAD^ and then git diff (actually I use github desktop client to see the diff) to evaluate what exactly it did, and if I like it or not. Then I usually make some adjustments and only after that commit and push.
You may want to pass --no-auto-commits to Aider if you peel them off HEAD afterwards anyway.
You can think of this as a managed (cloud) version of their codex command line tool, which runs locally on your laptop.
The secret sauce here seems like their new model, but I expect it to come to API at some point.
The secret sauce here seems like their new model, but I expect it to come to API at some point.
It generates a PR. You decide if you want to merge, clone it locally, test, edit and then merge the code.
This takes all the soul out of programming, not sure why anyone likes to use llms like this.
Because from a business point of view, they just want a feature to be built, they really care about the code if it works.
watch the live stream, it shows you the diff as the completed task, you decide whether or not to generate a github pr when you see the diff.
I wonder if tools like these are best for semi structured refactors like upgrade to python3, migrate to postgres etc
Has anyone else been able to get "secrets" to work?
They seem to be injected fine in the "environment setup" but don't seem to be injected when running tasks against the enviornment. This consistently repros even if I delete and re-create the enviornment and archive and resubmit the task.
They seem to be injected fine in the "environment setup" but don't seem to be injected when running tasks against the enviornment. This consistently repros even if I delete and re-create the enviornment and archive and resubmit the task.
Is this the same idea as when we switched to multicore machines? The rate of change on the capabilities of a single agent has slowed enough now the only way for OpenAI to appearing to be making decent progress is to have many?
I spend maybe $20 a month on Claude code, $200 a month is hard to swallow.
I don't understand why OAI puts their alpha release products under a $200 a month plan instead of just charging for tokens.
I don't understand why OAI puts their alpha release products under a $200 a month plan instead of just charging for tokens.
My weird theory: the alpha releases are more expensive than people realize, and OpenAI can afford to launch money-losing alphas on Pro because few users have Pro accounts and the lose less money per Pro user.
If anyone could use Codex, you’d want to price the tokens at a rate where you don’t lose money, or at least not too much money. If you price the tokens too high, then not only are people not using Codex, but customers and investors alike begin to lose faith, they no longer “feel the AGI”.
If anyone could use Codex, you’d want to price the tokens at a rate where you don’t lose money, or at least not too much money. If you price the tokens too high, then not only are people not using Codex, but customers and investors alike begin to lose faith, they no longer “feel the AGI”.
Why hasn't Github released this? Why it's OpenAI releasing this?!
It's on their roadmap: https://github.blog/news-insights/product-news/github-copilo...
But they aren't moving nearly as fast as OpenAI. And it remains to be seen if first mover will mean anything.
But they aren't moving nearly as fast as OpenAI. And it remains to be seen if first mover will mean anything.
GitHub has released this, it's called Copilot Agent.
Github moves too slow, and OpenAI moves too fast.
Maddening: "codex" is also the name of their open-source Claude-Code-alike, and was previously the name of an at-the-time frontier coding model. It's like they name things just to fuck with us.
So -- that client-side thing is _technically_ called `codex-cli` (in the parent 'codex' repo, which looks like a monorepo?).
Still super confusing, though!
I feel like companies working with and shipping LLMs would do well to remember that it's not just humans who get confused by this, but LLMs themselves... it makes for a painful time, sending off a request and noting that a third of the way into its reasoning that the model has gotten tow things with almost-identical names confused.
Still super confusing, though!
I feel like companies working with and shipping LLMs would do well to remember that it's not just humans who get confused by this, but LLMs themselves... it makes for a painful time, sending off a request and noting that a third of the way into its reasoning that the model has gotten tow things with almost-identical names confused.
they also have a dual implementation on rust and typescript there's codex-rs in that monorepo
more excited about the rust impl than the typescript one.
Besides packaging of their releases, what possible difference could that make in this problem domain?
I just think it's nice to have open source code to reference so maybe he meant just in that -educational- way, certainly more to learn from the rust one than the TS one for most folks? even if the problem-space doesn't require system-level safety code indeed
If it's name is 'codex-cli' then that means "Codex Command Line Interface" so the name is absolutely codex.
Next week: OpenAI rebrands Windsurf as Codex.
And with themselves and their models. The Codex open source had prompt to disambiguate it from the model.
[deleted]
When it runs the code I assume it does so via a docker container, does anyone know how it is configured? Assuming the user hasn't specified an AGENTS.md file or a Dockerfile in the repo. Does it generate it via LLM based on the repo, and what it thinks is needed? Does it use static analysis (package.json, requirements txt, etc)? Do they just have a super generic Dockerfile that can handle most envs? Combination of different things?
More about that here! https://platform.openai.com/docs/codex#advanced-configuratio...
It seems LLMs are doing a lot of the heavy lifting figuring out the exact test, build, lint commands to run (even if the AGENTS.md file gives it direction and hints). I wonder if there are any plans to support user defined build, test, and pre commit commands to avoid unnecessary cost and keep it deterministic. Also wonder how monolith repos (or distinct but related repos) are supported, does it run everything in one container or loop through the envs that are edited?
I assume one easy next step is to just run GitHub Actions in the container since everything is defined there (assuming the user set it up)
I assume one easy next step is to just run GitHub Actions in the container since everything is defined there (assuming the user set it up)
Thanks!
Does any one how the quality drops with size of codebase?
I remember HN had a repeating popular post on the the most important data structures. They are all the basic ones that a first-year college student can learn. The youngest one was skiplist, which was invented in 1990. When I was a student, my class literally read the original paper and implemented the data structure and analyzed the complexity in our first data structure course.
This seems imply that the software engineering as a profession has been quite mature and saturated for a while, to the point that a model can predict most of the output. Yes, yes, I know there are thousands of advanced algorithms and amazing systems in production. It's just that the market does not need millions of engineers for such advanced skills.
Unless we get yet another new domain like cloud or like internet, I'm afraid the core value of software engineers: trailblazing for new business scenarios, will continue diminishing and being marginalized by AI. As a result, we get way less demand for our job, and many of us will either take a lower pay, or lose our jobs for extended time.
This seems imply that the software engineering as a profession has been quite mature and saturated for a while, to the point that a model can predict most of the output. Yes, yes, I know there are thousands of advanced algorithms and amazing systems in production. It's just that the market does not need millions of engineers for such advanced skills.
Unless we get yet another new domain like cloud or like internet, I'm afraid the core value of software engineers: trailblazing for new business scenarios, will continue diminishing and being marginalized by AI. As a result, we get way less demand for our job, and many of us will either take a lower pay, or lose our jobs for extended time.
So there's this thing called "Setup Scripts" but they don't explicitly say these are equivalent to AWS Metadata and configured inside of Codex web interface - not a setup.sh or a package.json preinstall declaration. I wasted several hours (and lots of compute where Codex was as confused as I was) trying to figure out how to convince codex to pnpm install.
Codex engineer here. Can you elaborate on what was confusing? I would love to make it more clear.
I didn't realize the setup script had to be done in the UI over in the environment tab. I assumed it would be reading something like setup.sh from the codebase.
Docs could make that more clear
Docs could make that more clear
I just found this thread while trying to figure out where to set the setup script. The docs should probably make that more clear.
Is there an open source version of this? that essentially uses microvms to git clone my repo and essentially run codex-cli or equivalent and sends me a PR.
I made one for github action but it's not as realtime and is 2 years old now: https://github.com/asadm/chota
I made one for github action but it's not as realtime and is 2 years old now: https://github.com/asadm/chota
I haven't checked in on it recently, but maybe a similar open-source option would be https://github.com/All-Hands-AI/OpenHands
A not open-source option this looks close to is also https://githubnext.com/projects/copilot-workspace (released April 2024, but I'm not sure it's gotten any significant updates since)
A not open-source option this looks close to is also https://githubnext.com/projects/copilot-workspace (released April 2024, but I'm not sure it's gotten any significant updates since)
[deleted]
I think the benchmark test for these programming agents that I would like to see an Agent making a flawless PR or patch to the BSD / Linux kernel.
This should be possible today and surely Linus would also see this in the future.
This should be possible today and surely Linus would also see this in the future.
There’s a fairly pragmatic discussion in that exact topic with Linus here: https://youtu.be/VHHT6W-N0ak.
I've been experimenting with providers offering similar functionality for the last year and it is really vastly superior experience this codex like approach than cursor, devin etc
can someone give me a test prompt to one-shot something in go for testing?
(Im trying something)
what would be an impressive program that an agent should be able to one-shot in one go?
(Im trying something)
what would be an impressive program that an agent should be able to one-shot in one go?
> To balance safety and utility, Codex was trained to identify and precisely refuse requests aimed at development of malicious software, while clearly distinguishing and supporting legitimate tasks.
I can't say I am a big fan of neutering these paradigm-shifting tools according to one culture's code of ethics / way of doing business / etc.
One man's revolutionary is another's enemy combatant and all that. What if we need top-notch malware to take down the robot dogs lobbing mortars at our madmaxian compound?!
I can't say I am a big fan of neutering these paradigm-shifting tools according to one culture's code of ethics / way of doing business / etc.
One man's revolutionary is another's enemy combatant and all that. What if we need top-notch malware to take down the robot dogs lobbing mortars at our madmaxian compound?!
>What if we need top-notch malware to take down the robot dogs lobbing mortars at our madmaxian compound?!
I wouldn't sweat it. According to it's developers, Codex understands 'malicious software', it has just been trained to say, "But I won't do that" when such requests are made to it. Judging from the recent past [1][2] getting LLMs to bypass such safeguards is pretty easy.
1.https://hiddenlayer.com/innovation-hub/novel-universal-bypas... 2.https://cyberpress.org/researchers-bypass-safeguards-in-17-p...
I wouldn't sweat it. According to it's developers, Codex understands 'malicious software', it has just been trained to say, "But I won't do that" when such requests are made to it. Judging from the recent past [1][2] getting LLMs to bypass such safeguards is pretty easy.
1.https://hiddenlayer.com/innovation-hub/novel-universal-bypas... 2.https://cyberpress.org/researchers-bypass-safeguards-in-17-p...
Agreed, I'm a big proponent that people should be in control of the tools they use. I don't think the approach where there is wise dicator enforcing I can't use my flathead screwdriver to screw down a phillips head screw is good. I think it's actively undermining people.
You gotta think about it in terms of cost vs benefit. How much damage will a malicious AI do, vs how much value will you get out of non-neutered model?
[deleted]
If I had to guess, only for the general public they'll be neutered, not for the 3 letters agencies
TLA's have very few of their own coders, they contract everything out. Now I'm sure OAI will lend an unrestricted model to groups that pay large private contracts they won't disclose.
[deleted]
[deleted]
Is it surprising? Hmm perhaps nope. But is it better than cursor etc? Hmm perhaps it’s a wrong question.
Feels like codex is for product managers to fix bugs without touching any developer resources. Then it’s insanely surprising!
Feels like codex is for product managers to fix bugs without touching any developer resources. Then it’s insanely surprising!
I've been contracting with a startup. The bottleneck is not the lack of tools; it's agency. There's so much work, it becomes work to assign and organize work.
But now who's going to do that work? Still engineers.
But now who's going to do that work? Still engineers.
It sounds nice, but are product managers able to spot regressions or other potential issues (performance, data protection, legal, etc) in the codex result?
If codex can analyze the whole code base, I can’t see why not? I can even imagine one can set up a CI task that any committed code must pass all sort of legal/data protection requirements too
Exactly this. In fact the product manager should be the one that knows what the set of checks that need to be done over the code base. You need a dev though to do make sure the last mile is doing what you expect it to do.
pleased to see a paragraph-long comment in the examples. now thats good coding.
More generated slop for a real human to sift through. Can I get an ai summary of that comment?
[deleted]
not buying windsurf then???
This would be the why of that acquisition as this needs a more integrated UI. Guessing by the speed at which this came out, this was in the works long before that acquisition.
it is not even clear *if* they are going to buy windsurf at all. And thats a big if. This might've just been the 'why' that deal is not happening.
This probably came out to beat Google I/O or something similar - odd Friday release otherwise.
I am so damn tired of all the AI garbage shoved down our throats every day. Can't wait for all of it to crash and burn.
At some point the bubble will pop
Higher chance of AGI/most SWEs being out of a job for an extended period of time than the bubble popping imo.
Agree with this. It's so strange to me that out of the all the anti-AI arguments one can derive, the anti-AIers have settled on riding with the "it's useless" argument, when it's plainly one of the most useful tools created since the desktop computer.
These people remind me of the people in the late 19th century who were scared of electricity because they thought it could remove all the air from rooms and suffocate people.
Way higher chance
Is anyone using any of these tools to write non boilerplate code?
I'm very interested.
In my experience ChatGPT and Gemini are absolutely terrible at these types of things. They are constantly wrong. I know I'm not saying anything new, but I'm waiting to personally experience an LLM that does something useful with any of the code I give it.
These tools aren't useless. They're great as search engines and pointing me in the right direction. They write dumb bash scripts that save me time here and there. That's it.
And it's hilarious to me how these people present these tools. It generates a bunch of code, and then you spend all your time auditing and fixing what is expected to be wrong.
That's not the type of code I'm putting in my company's code base, and I could probably write the damn code more correctly in less time than it takes to review for expected errors.
What am I missing?
I'm very interested.
In my experience ChatGPT and Gemini are absolutely terrible at these types of things. They are constantly wrong. I know I'm not saying anything new, but I'm waiting to personally experience an LLM that does something useful with any of the code I give it.
These tools aren't useless. They're great as search engines and pointing me in the right direction. They write dumb bash scripts that save me time here and there. That's it.
And it's hilarious to me how these people present these tools. It generates a bunch of code, and then you spend all your time auditing and fixing what is expected to be wrong.
That's not the type of code I'm putting in my company's code base, and I could probably write the damn code more correctly in less time than it takes to review for expected errors.
What am I missing?
>What am I missing?
That you are trying to use LLMs to create giant sprawling codebase feature packed software packages that define the modern software landscape. What's being missed is that any one user might only utilize 5% of the code base on any given day. Software is written to accommodate every need every user could have in one package. Then the users just use the small slice that accommodates their specific needs.
I have now created 5 hyper narrow programs that are used daily by my company to do work. I am not a programmer and my company is not a tech company located in a tech bubble. We are a tiny company that does old school manufacturing.
To give a quick general example, Betty uses Excel to manage payroll. A list of employees, a list of wages, a list of hours worked (which she copys from the time clock software .csv that she imports to excel).
Excel is a few million LOC program and costs ~$10/mo. Betty needs maybe 2k LOC to do what she uses excel for. Something an LLM can do easily, a python GUI wrapper on an SQLite DB. And she would be blown away at how fast it is, and how it is written for her use specifically.
How software is written and how it is used will change to accommodate LLMs. We didn't design cars to drive on horse paths, we put down pavement.
That you are trying to use LLMs to create giant sprawling codebase feature packed software packages that define the modern software landscape. What's being missed is that any one user might only utilize 5% of the code base on any given day. Software is written to accommodate every need every user could have in one package. Then the users just use the small slice that accommodates their specific needs.
I have now created 5 hyper narrow programs that are used daily by my company to do work. I am not a programmer and my company is not a tech company located in a tech bubble. We are a tiny company that does old school manufacturing.
To give a quick general example, Betty uses Excel to manage payroll. A list of employees, a list of wages, a list of hours worked (which she copys from the time clock software .csv that she imports to excel).
Excel is a few million LOC program and costs ~$10/mo. Betty needs maybe 2k LOC to do what she uses excel for. Something an LLM can do easily, a python GUI wrapper on an SQLite DB. And she would be blown away at how fast it is, and how it is written for her use specifically.
How software is written and how it is used will change to accommodate LLMs. We didn't design cars to drive on horse paths, we put down pavement.
The Romans put down paved roads to make their horse paths more reliable.
But yes, I hope we get away from the giant conglomeration of everything, ESPECIALLY the reality of people doing 90% of their business inside a Google Chrome widow. Move towards the UNIX philosophy of tiny single-purpose programs.
But yes, I hope we get away from the giant conglomeration of everything, ESPECIALLY the reality of people doing 90% of their business inside a Google Chrome widow. Move towards the UNIX philosophy of tiny single-purpose programs.
> I have now created 5 hyper narrow programs that are used daily by my company to do work. I am not a programmer and my company is not a tech company located in a tech bubble. We are a tiny company that does old school manufacturing.
OK, great.
> That you are trying to use LLMs to create giant sprawling codebase feature packed software packages that define the modern software landscape. What's being missed is that any one user might only utilize 5% of the code base on any given day. Software is written to accommodate every need every user could have in one package. Then the users just use the small slice that accommodates their specific needs.
With all due respect, the fact that you made a few small programs to help with your tasks is wonderful but this last statement alone rather disqualifies your expertise to make an assessment on software engineering in general.
There's a great number of reasons why codebases get large. Complex problems inherently come with complexity and scale in both code and integrations. You can choose to move the complexity around but never fully get rid of it.
OK, great.
> That you are trying to use LLMs to create giant sprawling codebase feature packed software packages that define the modern software landscape. What's being missed is that any one user might only utilize 5% of the code base on any given day. Software is written to accommodate every need every user could have in one package. Then the users just use the small slice that accommodates their specific needs.
With all due respect, the fact that you made a few small programs to help with your tasks is wonderful but this last statement alone rather disqualifies your expertise to make an assessment on software engineering in general.
There's a great number of reasons why codebases get large. Complex problems inherently come with complexity and scale in both code and integrations. You can choose to move the complexity around but never fully get rid of it.
But how much of the software industry is truly solving inherently complex problems?
At a very conservative guess I'd say no more than 10% (and my actual guess would be <1%)
At a very conservative guess I'd say no more than 10% (and my actual guess would be <1%)
A lot of people are deeply invested in these things being better than they really are. From the OpenAI's and Google's spending $100s of billions EACH developing LLMs to VC backed startups promising their "AI agent" can replace entire teams of white collar employees. That's why your experience matches mine and every other developer I personally know but you see comments everywhere making much grander claims.
I agree, but I'd add that it's not just the tech giants who want them to be better than they are, but also non-programmers.
IMO LLMs are actually pretty good at writing small scripts. First, it's much more common for a small script to be in the LLM's training data, and second, it's much easier to find and fix a bug. So the LLM actually does allow a non-programmer to write correct code with minimal effort (for some simple task), and then they are blown away thinking writing software is a solved problem. However, these kinds of people have no idea of the difference between a hundred line script where an error is easily found and isn't a big deal and a million line codebase where an error can be invisible and shut everything down.
Worst of all is when the two sides of tech-giants and non-programmers meet. These two sides may sound like opposites but they really aren't. In particular, there are plenty of non-programmers involved at the C-level and the HR levels of tech companies. These people are particularly vulnerable to being wowed by LLMs seemingly able to do complex tasks that in their minds are the same tasks their employees are doing. As a result, they stop hiring new people and tell their current people to "just use LLMs", leading to the current hiring crisis.
IMO LLMs are actually pretty good at writing small scripts. First, it's much more common for a small script to be in the LLM's training data, and second, it's much easier to find and fix a bug. So the LLM actually does allow a non-programmer to write correct code with minimal effort (for some simple task), and then they are blown away thinking writing software is a solved problem. However, these kinds of people have no idea of the difference between a hundred line script where an error is easily found and isn't a big deal and a million line codebase where an error can be invisible and shut everything down.
Worst of all is when the two sides of tech-giants and non-programmers meet. These two sides may sound like opposites but they really aren't. In particular, there are plenty of non-programmers involved at the C-level and the HR levels of tech companies. These people are particularly vulnerable to being wowed by LLMs seemingly able to do complex tasks that in their minds are the same tasks their employees are doing. As a result, they stop hiring new people and tell their current people to "just use LLMs", leading to the current hiring crisis.
TBH, this website in the last few years has attracted an increasingly non-technical audience. And the field, in general, has attracted a lot of less experienced folks that don't understand the implications of what they're doing. I don't mean that as a diss-- but just a reflection of reality.
Indeed, even codex (and i've been using it prior to this release) is not remotely at the level of even a junior engineer outside of a set of tasks.
Indeed, even codex (and i've been using it prior to this release) is not remotely at the level of even a junior engineer outside of a set of tasks.
Occasionally. I find that there is a certain category of task that I can hand over to an LLM and get a result that takes me significantly less time to clean up than it would have taken me to write from scratch.
A recent example from a C# project I was working in. The project used builder classes that were constructed according to specified rules, but all of these builders were written by hand. I wanted to automatically generate these builders, and not using AI, just good old meta-programming.
Now I knew enough to know that I needed a C# source generator, but I had absolutely no experience with writing them. Could I have figured this out in an hour or two? Probably. Did I write a prompt in less than five minutes and get a source generator that worked correctly in the first shot? Also yes. I then spent some time cleaning up that code and understanding the API it uses to hook into everything and was done in half an hour and still learnt something from it.
You can make the argument that this source generator is in itself "boilerplate", because it doesn't contain any special sauce, but I still saved significant time in this instance.
A recent example from a C# project I was working in. The project used builder classes that were constructed according to specified rules, but all of these builders were written by hand. I wanted to automatically generate these builders, and not using AI, just good old meta-programming.
Now I knew enough to know that I needed a C# source generator, but I had absolutely no experience with writing them. Could I have figured this out in an hour or two? Probably. Did I write a prompt in less than five minutes and get a source generator that worked correctly in the first shot? Also yes. I then spent some time cleaning up that code and understanding the API it uses to hook into everything and was done in half an hour and still learnt something from it.
You can make the argument that this source generator is in itself "boilerplate", because it doesn't contain any special sauce, but I still saved significant time in this instance.
I've built a number of personal data-oriented and single purpose tools in Replit. I've constrained my ambitions to what I think it can do but I've added use cases beyond my initial concept.
In short, the tools work. I've built things 10x faster than doing it from scratch. I also have a sense of what else I'll be able to build in a year. I also enjoy not having to add cycles to communicate with external contributors -- I think, then I do, even if there's a bit of wrestling. Wrangling with a coding agent feels a bit like "compile, test, fix, re-compile". Re-compiling generally got faster in subsequent generations of compiler releases.
My company is building internal business functions using AI right now. It works too. We're not putting that stuff in front of our customers yet, but I can see that it'll come. We may put agents into the product that let them build things for themselves.
I get the grumpiness & resistance, but I don't see how it's buying you anything. The puck isn't underfoot.
In short, the tools work. I've built things 10x faster than doing it from scratch. I also have a sense of what else I'll be able to build in a year. I also enjoy not having to add cycles to communicate with external contributors -- I think, then I do, even if there's a bit of wrestling. Wrangling with a coding agent feels a bit like "compile, test, fix, re-compile". Re-compiling generally got faster in subsequent generations of compiler releases.
My company is building internal business functions using AI right now. It works too. We're not putting that stuff in front of our customers yet, but I can see that it'll come. We may put agents into the product that let them build things for themselves.
I get the grumpiness & resistance, but I don't see how it's buying you anything. The puck isn't underfoot.
I think it all depends on your platform and use cases. In my experience AI tools work best with Python and JS/Typescript and some simple use cases (web apps, basic data science etc). Also, I've found they can be of great help with refactorings and cases when you need to do something similar to already existing code, but with a twist or change.
What you're missing is how to use the tools properly. With solid documentation, good project management practices, a well-organized code structure and tests, any junior engineer should be able to read up on your codebase, write linted code following your codebase style, verify it via tests and write you a report of what was done, challenges faced etc. State of the art coding agents will do that at superhuman speeds.
If you haven't set things up properly (important info lives only in people’s heads / meetings, tasks dont have clear acceptance criteria, ...) then you aren't ready for Junior Developers yet. You need to wait until your Coding Agents are at Senior level.
If you haven't set things up properly (important info lives only in people’s heads / meetings, tasks dont have clear acceptance criteria, ...) then you aren't ready for Junior Developers yet. You need to wait until your Coding Agents are at Senior level.
Firstly, LLM chat interfaces != agentic coding platforms.
ChatGPT is good for asking questions about languages, SDKs, and APIs, or generating boilerplate, but it's useless if you want to give an AI a ticket and for it to raise PRs for you.
This is where you need agentic solutions like Codex which will be far more useful because they will actually have access to your codebase and a dev environment where they can test and debug changes.
They still do really dumb things, but a lot of this can be avoided if you prompt well and give it the right types of problems to solve.
In my experience at the moment there's a sweet spot with these agentic coding platforms which makes them useful for semi-complicated tasks – assuming you prompt well they can generate 90% of the code you need, then you just need to spend the extra 10% fixing it up before it's ready for prod.
Tasks too simple (a few lines) it's a waste of time. You spend longer prompting and going back and forth with the agent than it would take to just make the change yourself.
Then obviously very complicated tasks, especially tasks that require some thought around architecture and performance, coding agents really struggle with. Less because they can't do it, but because for certain problems simply meeting ACs is far less important than how the ACs are being met. Ideally here you want to get the architecture right first, then once that's in place you can break down the remaining work for the AI to pick up.
ChatGPT is good for asking questions about languages, SDKs, and APIs, or generating boilerplate, but it's useless if you want to give an AI a ticket and for it to raise PRs for you.
This is where you need agentic solutions like Codex which will be far more useful because they will actually have access to your codebase and a dev environment where they can test and debug changes.
They still do really dumb things, but a lot of this can be avoided if you prompt well and give it the right types of problems to solve.
In my experience at the moment there's a sweet spot with these agentic coding platforms which makes them useful for semi-complicated tasks – assuming you prompt well they can generate 90% of the code you need, then you just need to spend the extra 10% fixing it up before it's ready for prod.
Tasks too simple (a few lines) it's a waste of time. You spend longer prompting and going back and forth with the agent than it would take to just make the change yourself.
Then obviously very complicated tasks, especially tasks that require some thought around architecture and performance, coding agents really struggle with. Less because they can't do it, but because for certain problems simply meeting ACs is far less important than how the ACs are being met. Ideally here you want to get the architecture right first, then once that's in place you can break down the remaining work for the AI to pick up.
I think most code these days is boilerplate, though the composition of boilerplate snippets can become something unique and differentiated.
you might be missing small things to create more guardrails like effective prompting and maintaining what's been done using files, carefully controlling context, committing often in-between changes, but largely, you're not missing anything. i use AI constantly, but always for subtasks of a larger complicated thing that my brain has thought through. and often use higher cost models to help me abstractly think through complex things/point me in the right directions.
personally, i've always operated in a codebase in a way that i _need_ to understand how things work for me to be productive and make the right decisions. I operate the same way with AI. every change is carefully reviewed, if it's dumb, i make it redo it and explain why it's dumb. and if it gets caught in a loop, i reset the context and try to reframe the problem. overall, i'm definitely more productive, but if you truly want to be hands off--you're in for a very bad time. i've been there.
lastly, some codebases don't work well with AI. I was working on a problem that was a bit more novel/out there and no model could solve it. Just yapped endlessly about these complex, very potentially smart sounding solutions that did absolutely nothing. went all the way to o1-pro. the craziest part to me was the fact that across claude, deepseek and openai, they used the same specific vernacular for this particular problem which really highlights how a lot of these models are just a mish-mash of the same underlying architecture/internet data. some of these models use responses from other models for their training data, which to me is like incest. you won't get good genetical results
personally, i've always operated in a codebase in a way that i _need_ to understand how things work for me to be productive and make the right decisions. I operate the same way with AI. every change is carefully reviewed, if it's dumb, i make it redo it and explain why it's dumb. and if it gets caught in a loop, i reset the context and try to reframe the problem. overall, i'm definitely more productive, but if you truly want to be hands off--you're in for a very bad time. i've been there.
lastly, some codebases don't work well with AI. I was working on a problem that was a bit more novel/out there and no model could solve it. Just yapped endlessly about these complex, very potentially smart sounding solutions that did absolutely nothing. went all the way to o1-pro. the craziest part to me was the fact that across claude, deepseek and openai, they used the same specific vernacular for this particular problem which really highlights how a lot of these models are just a mish-mash of the same underlying architecture/internet data. some of these models use responses from other models for their training data, which to me is like incest. you won't get good genetical results
It’s probably what you’re asking. You can’t just say “write me an app”, you have to break a big problem into small problems for it.
I tried using Gemini 2.5 Pro for a side-side-project, seemed like a good project to explore LLMs and how they'd fit into my workflow. 2-3 weeks later it's around 7k loc of Python auto-gerating about 35k loc of C from JSON spec.
This project is not your typical Webdev project, so maybe that's an interesting case-study. It takes a C-API spec in JSON, loads and processes it in Python and generates a C-library that turns a UI marked up YAML/JSON into C-Api calls to render that UI. [1]
The result is pretty hacky code (by my design, can't/won't use FFI) that's 90% written by Gemini 2.5 Pro Pre/Exp but it mostly worked. It's around 7k lines of Python that generate a 30-40k loc C-library from a JSON LVGL-API-spec to render an LVGL UI from YAML/JSON markup.
I probably spent 2-3 weeks on this, I might have been able to do something similar in maybe 2x the time but this is about 20% of the mental overhead/exhaustion it would have taken me otherwise. Otoh, I would have had a much better understanding of the tradeoffs and maybe a slightly cleaner architecture if I would have to write it. But there's also a chance I would have gotten lost in some of the complexity and never finished (esp since it's a side-project that probably no-one else will ever see).
What worked well:
* It mostly works(!). Unlike previous attempts with Gemini 1.5 where I had to spend about as much or more time fixing than it'd have taken me to write the code. Even adding complicated features after the fact usually works pretty well with minor fixing on my end.
* Lowers mental "load" - you don't have to think so much about how to tackle features, refactors, ...
Other stuff:
* I really did not like Cursor or Windsurf - I half-use VSCode for embedded hobby projects but I don't want to then have another "thing" on top of that. Aider works, but it would probably require some more work to get used to the automatic features. I really need to get used to the tooling, not an insignificant time investment. It doesn't vibe with how I work, yet.
* You can generate a *significant* amount of code in a short time. It doesn't feel like it's "your" code though, it's like joining a startup - a mountain of code, someone else's architecture, their coding style, comment style, ... and,
* there's this "fog of code", where you can sorta bumble around the codebase but don't really 100% understand it. I still have mid/low confidence in the changes I make by hand, even 1 week after the codebase has largely stabilized. Again, it's like getting familiar with someone else's code.
* Code quality is ok but not great (and partially my fault). Probably depends on how you got to the current code - ie how clean was your "path". But since it is easier to "evolve" the whole project (I changed directions once or twice when I sort of hit a wall) it's also easier to end up with a messy-ish codebase. Maybe the way to go is to first explore, then codify all the requirements and start afresh from a clean slate instead of trying to evolve the code-base. But that's also not an insignificant amount of work and also mental load (because now you really need to understand the whole codebase or trust that an LLM can sufficiently distill it).
* I got much better results with very precise prompts. Maybe I'm using it wrong, ie I usually (think I) know what I want and just instruct the LLM instead of having an exploratory chat but the more explicit I am, the more closely the output is to what I'd like to see. I've tried to discuss proposed changes a few times to generate a spec to implement in another session but it takes time and was not super successful. Another thing to practice.
* A bit of a later realization, but modular code and short, self-contained modules are really important though this might depend on your workflow.
To summarize:
* It works.
* It lowers initial mental burden.
* But to get really good results, you still have to put a lot of effort into it.
* At least right now, it seems you will still eventually have to put in the mental effort at some point, normally it's "front-loaded" where you have to do the design and think about it hard, whereas the AI does all the initial work but it becomes harder to cope with the codebase once you reach a certain complexity. Eventually you will have to understand it though even if just to instruct the LLM to make the exact changes you want.
[1] https://github.com/thingsapart/lvgl_ui_preview
This project is not your typical Webdev project, so maybe that's an interesting case-study. It takes a C-API spec in JSON, loads and processes it in Python and generates a C-library that turns a UI marked up YAML/JSON into C-Api calls to render that UI. [1]
The result is pretty hacky code (by my design, can't/won't use FFI) that's 90% written by Gemini 2.5 Pro Pre/Exp but it mostly worked. It's around 7k lines of Python that generate a 30-40k loc C-library from a JSON LVGL-API-spec to render an LVGL UI from YAML/JSON markup.
I probably spent 2-3 weeks on this, I might have been able to do something similar in maybe 2x the time but this is about 20% of the mental overhead/exhaustion it would have taken me otherwise. Otoh, I would have had a much better understanding of the tradeoffs and maybe a slightly cleaner architecture if I would have to write it. But there's also a chance I would have gotten lost in some of the complexity and never finished (esp since it's a side-project that probably no-one else will ever see).
What worked well:
* It mostly works(!). Unlike previous attempts with Gemini 1.5 where I had to spend about as much or more time fixing than it'd have taken me to write the code. Even adding complicated features after the fact usually works pretty well with minor fixing on my end.
* Lowers mental "load" - you don't have to think so much about how to tackle features, refactors, ...
Other stuff:
* I really did not like Cursor or Windsurf - I half-use VSCode for embedded hobby projects but I don't want to then have another "thing" on top of that. Aider works, but it would probably require some more work to get used to the automatic features. I really need to get used to the tooling, not an insignificant time investment. It doesn't vibe with how I work, yet.
* You can generate a *significant* amount of code in a short time. It doesn't feel like it's "your" code though, it's like joining a startup - a mountain of code, someone else's architecture, their coding style, comment style, ... and,
* there's this "fog of code", where you can sorta bumble around the codebase but don't really 100% understand it. I still have mid/low confidence in the changes I make by hand, even 1 week after the codebase has largely stabilized. Again, it's like getting familiar with someone else's code.
* Code quality is ok but not great (and partially my fault). Probably depends on how you got to the current code - ie how clean was your "path". But since it is easier to "evolve" the whole project (I changed directions once or twice when I sort of hit a wall) it's also easier to end up with a messy-ish codebase. Maybe the way to go is to first explore, then codify all the requirements and start afresh from a clean slate instead of trying to evolve the code-base. But that's also not an insignificant amount of work and also mental load (because now you really need to understand the whole codebase or trust that an LLM can sufficiently distill it).
* I got much better results with very precise prompts. Maybe I'm using it wrong, ie I usually (think I) know what I want and just instruct the LLM instead of having an exploratory chat but the more explicit I am, the more closely the output is to what I'd like to see. I've tried to discuss proposed changes a few times to generate a spec to implement in another session but it takes time and was not super successful. Another thing to practice.
* A bit of a later realization, but modular code and short, self-contained modules are really important though this might depend on your workflow.
To summarize:
* It works.
* It lowers initial mental burden.
* But to get really good results, you still have to put a lot of effort into it.
* At least right now, it seems you will still eventually have to put in the mental effort at some point, normally it's "front-loaded" where you have to do the design and think about it hard, whereas the AI does all the initial work but it becomes harder to cope with the codebase once you reach a certain complexity. Eventually you will have to understand it though even if just to instruct the LLM to make the exact changes you want.
[1] https://github.com/thingsapart/lvgl_ui_preview
yes, think of it as search engine that auto-applies that stackoverflow fix to your code.
But I have done larger tasks (write device drivers) using gemini.
But I have done larger tasks (write device drivers) using gemini.
I feel things get even worse when you use a more niche language. I get extremely disappointed any time I try to get it do anything useful in Clojure. Even as a search engine, especially when asking it about libraries, these tools completely fail expectation.
I can't even fathom how frustrating such tools would be with poorly written confusing Clojure code using some niche dependency.
That being said, I can imagine a whole class of problems where this could succeed very well at and provide value. Then again, the type of problems that I feel these systems could get right 99% of the time are problems that a skilled developer could fix in minutes.
I can't even fathom how frustrating such tools would be with poorly written confusing Clojure code using some niche dependency.
That being said, I can imagine a whole class of problems where this could succeed very well at and provide value. Then again, the type of problems that I feel these systems could get right 99% of the time are problems that a skilled developer could fix in minutes.
Hey there!
Lots missing here, but I had the same issues, it takes iteration and practice. I use claude code in terminal windows, and text expander to save explicit reminders that I have to inject super regularly because anthropic obscures access to system prompts.
For example, I have 3 to 8 paragraph long instructions I will place regularly about not assuming, checking deterministically etc. and for most things I have the agents write a report with a specific instruction set.
I pop the instructions into text expander so I just type - docs when saying go figure this out, and give me the path to the report when done.
They come back with a path, and I copy it and search vscode
It opens as an md and i use preview mode, its similar to a google doc.
And ill review it. always, things will be wrong, tons of assumptions, failures to check determistically, etc... but I see that in the doc and have it fix it. correct misunderstandings, update the doc until its perfect.
From there ill say add a plan in a table with status for each task based on this ( another text expander snippet with instructions )
And WHEN thats 100% right, Ill say implement and update as you go. The update as you go forces it to recognize and remember the scope of the task.
Greatest points of failure in the system is misalignment. Ethics teams got that right. It compounds FAST if allowed. you let them assume things, they state assumptions as facts, that becomes what other agents read and you get true chaos unchecked.
I started rebuilding claude code from scratch literally because they block us from accessing system prompts and I NEED these agents to stop lying to me about things that are not done or assumed, which highlights the true chaos possible when applied to system critical operations in governance or at scale.
I also built my own tool like codex for managing agent tasks and making this simpler, but getting them to use it without getting confused is still a gap.
Let me know if you have any other questions. I am performing the work of 20 Engineers as of today, rewrote 2 years of back end code that required a team of 2 engineers full time work in 4 weeks by myself with this system... so I am, I guess quite good at it.
I need to push my edges further into this latest tech, have not tried codex cli or the new tool yet.
Lots missing here, but I had the same issues, it takes iteration and practice. I use claude code in terminal windows, and text expander to save explicit reminders that I have to inject super regularly because anthropic obscures access to system prompts.
For example, I have 3 to 8 paragraph long instructions I will place regularly about not assuming, checking deterministically etc. and for most things I have the agents write a report with a specific instruction set.
I pop the instructions into text expander so I just type - docs when saying go figure this out, and give me the path to the report when done.
They come back with a path, and I copy it and search vscode
It opens as an md and i use preview mode, its similar to a google doc.
And ill review it. always, things will be wrong, tons of assumptions, failures to check determistically, etc... but I see that in the doc and have it fix it. correct misunderstandings, update the doc until its perfect.
From there ill say add a plan in a table with status for each task based on this ( another text expander snippet with instructions )
And WHEN thats 100% right, Ill say implement and update as you go. The update as you go forces it to recognize and remember the scope of the task.
Greatest points of failure in the system is misalignment. Ethics teams got that right. It compounds FAST if allowed. you let them assume things, they state assumptions as facts, that becomes what other agents read and you get true chaos unchecked.
I started rebuilding claude code from scratch literally because they block us from accessing system prompts and I NEED these agents to stop lying to me about things that are not done or assumed, which highlights the true chaos possible when applied to system critical operations in governance or at scale.
I also built my own tool like codex for managing agent tasks and making this simpler, but getting them to use it without getting confused is still a gap.
Let me know if you have any other questions. I am performing the work of 20 Engineers as of today, rewrote 2 years of back end code that required a team of 2 engineers full time work in 4 weeks by myself with this system... so I am, I guess quite good at it.
I need to push my edges further into this latest tech, have not tried codex cli or the new tool yet.
Its a total of about 30 snippets, avg 6 paragraphs long, that I have to inject. for each role switch it goes through i have to re inject them.
its a pain but it works.
Even TDD it will hallucinate the mocks without management. and hallucinate the requirements. Each layer has to be checked atomically, but the text expander snippets done right can get it close to 75% right.
My main project faces 5000 users so I cant let the agents run freely, whereas with isolated projects in separate repos I can let them run more freely, then review in gitkraken before committing.
its a pain but it works.
Even TDD it will hallucinate the mocks without management. and hallucinate the requirements. Each layer has to be checked atomically, but the text expander snippets done right can get it close to 75% right.
My main project faces 5000 users so I cant let the agents run freely, whereas with isolated projects in separate repos I can let them run more freely, then review in gitkraken before committing.
You could just use something like roo code with custom modes rather than manually injecting them. The orchestrator mode can decide on the other appropriate modes to use for subtasks.
You can customize the system prompts, baseline propmts, and models used for every single mode and have as many or as few as you want.
You can customize the system prompts, baseline propmts, and models used for every single mode and have as many or as few as you want.
It may depend on what you consider boilerplate. I use them quite a bit for scripting outside of direct product code development. Essentially, AI coding tools have moved this chart's decision making math for me: https://xkcd.com/1205/ The cost to automate manual tasking is now significantly lower so I end up doing more of it.
[deleted]
I'm curious how many ICs are truly excited about these advancements in coding agents. It seems to me the general trend is we become more like PMs managing agents and reviewing PRs, all for the sake of productivity gains.
I imagine many engineers are like myself in that they got into programming because they liked tinkering and hacking and implementation details, all of which are likely to be abstracted over in this new era of prompting.
I imagine many engineers are like myself in that they got into programming because they liked tinkering and hacking and implementation details, all of which are likely to be abstracted over in this new era of prompting.
While I share your reservations, how many millions of people have experienced the exact same disruption to their jobs and industries because of software that we, software engineers, have created? It’s a bit too late, and a touch hypocritical, for us to start complaining about technology now it is disrupting our way of working in a way we don’t like.
I see it differently. Like a kid with legos.
We had to tinker piece by piece to build a miniature castle. Over many hours.
Now I can tinker concept by concept, and build much larger castles, much faster. Like waving a wand, seeing my thoughts come to fruition in near real time.
No vanity lost in my opinion. Possibly more to be gained.
We had to tinker piece by piece to build a miniature castle. Over many hours.
Now I can tinker concept by concept, and build much larger castles, much faster. Like waving a wand, seeing my thoughts come to fruition in near real time.
No vanity lost in my opinion. Possibly more to be gained.
I think there's a disconnect between what you and the person you're replying to are defining as "tinkering". Your conception of it seems more focused on the end product when, to use your analogy, the original comment seems unconcerned with the size of castles.
If you derive enjoyment from actually assembling the castle, you lose out on that by using the wand that makes it happen instantly. Sure wand's castles may be larger, but you don't put a Lego castle together for the finished product.
If you derive enjoyment from actually assembling the castle, you lose out on that by using the wand that makes it happen instantly. Sure wand's castles may be larger, but you don't put a Lego castle together for the finished product.
> build much larger castles, much faster
See that never was the purpose.. going bigger and faster, towards what exactly? Chaos? By the way we never managed to fully tackle manual software development by trained professionals and we now expect Shangri-La by throwing everything and the kitchen sink into giant inscrutable matrices. This time by amateurs as well. I'm sure this will all turn out very well and very, very productive.
See that never was the purpose.. going bigger and faster, towards what exactly? Chaos? By the way we never managed to fully tackle manual software development by trained professionals and we now expect Shangri-La by throwing everything and the kitchen sink into giant inscrutable matrices. This time by amateurs as well. I'm sure this will all turn out very well and very, very productive.
I think the bigger issue with this is that the number of developer jobs will shrink.
Factorio blueprints in action.
I do feel that way, so I'll still do bespoke creation when I want to. But this is like a sewing machine. My job is to design fashion, and a whole line of it. I can do that when a machine is making the stitches instead of my using a needle in hand.
I think the death of our craft is around the corner. It doesn't fill me with joy.
Software engineering requires a fair amount of intelligence, so if these tools ever get to replacement levels of quality then it's not just developers that will be out of jobs. ARC-AGI-2, the countless anecdotes from professionals I've seen across the industry, and personal experience all very clearly point to a significant gap between the tools that exist today and general intelligence. I would recommend keeping an eye on improvements just because of the sheer capital investments going into it, but I won't be losing any sleep waiting for the rapture.
How so? I see it as more bugs around the corner.
I used to think this way too. Here are a few ways I've tried to re frame things that has helped.
1. When I work on side projects and use AI, sometimes I wonder "what's the point if I am just copy / pasting code? I am not learning anything" but what I have come to realize is building apps with AI assistance is the skill that I am learning, rather than writing code per se as it was a few years ago.
2. I work in high scale distributed computing, so I am still presented with ample opportunities to get very low level, which I love. I am not sure how much I care about writing code per se anymore. Working with AI still is tinkering, it has not changed that much for me. It is quite different, but the underlying fun parts are still present.
1. When I work on side projects and use AI, sometimes I wonder "what's the point if I am just copy / pasting code? I am not learning anything" but what I have come to realize is building apps with AI assistance is the skill that I am learning, rather than writing code per se as it was a few years ago.
2. I work in high scale distributed computing, so I am still presented with ample opportunities to get very low level, which I love. I am not sure how much I care about writing code per se anymore. Working with AI still is tinkering, it has not changed that much for me. It is quite different, but the underlying fun parts are still present.
We (dare I say we instead of I) like talking to computers and AI is another computer you talk with. So I am still all excited. It's people that I want to avoid :)
people can still write code by hand for fun
people who want to make software that enables people to accomplish [task] will get the software they need quicker.
people who want to make software that enables people to accomplish [task] will get the software they need quicker.
[deleted]
At the end of the day, it's your job to deliver value. If a tool allows you to deliver more faster, without sacrificing quality, it's your responsibility to use that tool. You'll just have to make sure you can fully take responsibility for the end deliverables. And these tools are not only useful for writing the final code
It's actually not. My job description does not say "deliver value" and nobody talks about my work like that so I'm not quite sure what to make of that.
> without sacrificing quality
Right..
> it's your responsibility to use that tool
Again, it's actually not. It's my responsibility to do my job, not to make my boss' - or his boss' - car nicer. I know that's what we all know will create "job security" but let's not conflate these things. My job is to do my end of the bargain. My boss' job is paying me for doing that. If he deems it necessary to force me to use AI bullshit, I will of course, but it is definitely not my responsibility to do so autonomously.
> without sacrificing quality
Right..
> it's your responsibility to use that tool
Again, it's actually not. It's my responsibility to do my job, not to make my boss' - or his boss' - car nicer. I know that's what we all know will create "job security" but let's not conflate these things. My job is to do my end of the bargain. My boss' job is paying me for doing that. If he deems it necessary to force me to use AI bullshit, I will of course, but it is definitely not my responsibility to do so autonomously.
> these tools are not only useful for writing the final code
This sparked a thought in how a large part of the job is often the work needed to demonstrate impact. I think this aspect is often overlooked by some of the good engineers not yet taking advantage of the AI tooling. LLM loops may not yet be good enough to produce shippable code by themselves, but they sure are capable to help reduce the overhead of these up and out communicative tasks.
This sparked a thought in how a large part of the job is often the work needed to demonstrate impact. I think this aspect is often overlooked by some of the good engineers not yet taking advantage of the AI tooling. LLM loops may not yet be good enough to produce shippable code by themselves, but they sure are capable to help reduce the overhead of these up and out communicative tasks.
you mean like hacking a first POC with AI to sell a product/feature internally to get buy-in from the rest of the team before actually shipping production version of it?
> At the end of the day, it's your job to deliver value. If a tool allows you to deliver more faster, without sacrificing quality
I guess that's LLMs ruled out then
I guess that's LLMs ruled out then
[deleted]
As someone who works on his own open source agent framework/UI (https://github.com/runvnc/mindroot), it's kind of interesting how announcements from vendors tend to mirror features that I am working on.
For example, in the last month or so, I added a job queue plugin. The ability to run multiple tasks that they demoed today is quite similar. The issue I ran into with users is that without Enterprise plans, complex tasks run into rate limits when trying to run concurrently.
So I am adding an ability to have multiple queues, with each possibly using different models and/or providers, to get around rate limits.
By the way, my system has features that are somewhat similar not only to this tool they are showing but also things like Manus. It is quite rough around the edges though because I am doing 100% of it myself.
But it is MIT Licensed and it would be great if any developer on the planet wanted to contribute anything.
For example, in the last month or so, I added a job queue plugin. The ability to run multiple tasks that they demoed today is quite similar. The issue I ran into with users is that without Enterprise plans, complex tasks run into rate limits when trying to run concurrently.
So I am adding an ability to have multiple queues, with each possibly using different models and/or providers, to get around rate limits.
By the way, my system has features that are somewhat similar not only to this tool they are showing but also things like Manus. It is quite rough around the edges though because I am doing 100% of it myself.
But it is MIT Licensed and it would be great if any developer on the planet wanted to contribute anything.
[deleted]
I believe that code from one of these things will eventually cause a disaster affecting the capital owners. Then all of a sudden you will need a PE license, ABET degree, 5 years working experience, etc. to call yourself a software engineer. It would not even be historically unique. Charlatans are the reason that lawyers, medical doctors, and civil engineers have to go through lots of education, exams, and vocational training to get into their profession. AI will probably force software engineering as a profession into that category as well.
On the other hand, if your job was writing code at certain companies whose profits were based on shoving ads in front of people then I would agree that no one will care if it is written by a machine or not. The days of those jobs making >$200k a year are numbered.
On the other hand, if your job was writing code at certain companies whose profits were based on shoving ads in front of people then I would agree that no one will care if it is written by a machine or not. The days of those jobs making >$200k a year are numbered.
Even ads have risk. Customer service has risk. The widespread proliferation of this stuff is a legal minefield waiting to be stepped on.
I wish but I dont think we could be any futher away from professionalizing like engineering/law/accounting/medicine. There was a deliberate effort to flood the field and lower salaries and developers were so full of hubris and thought there was infinite demand for their labor and went along with it and still are. Maybe some are learning given the job market the last few years.
Despite software being in everything and harm to the public due to bad software has materialized every developer seems vehemently against professionalizing. Do you want a surgeon that went to surgeon bootcamp because "you dont need all those years in medical school to learn how to remove an appendix"? Do you even want an accountant who went to accountant bootcamp to do your taxes?
Despite software being in everything and harm to the public due to bad software has materialized every developer seems vehemently against professionalizing. Do you want a surgeon that went to surgeon bootcamp because "you dont need all those years in medical school to learn how to remove an appendix"? Do you even want an accountant who went to accountant bootcamp to do your taxes?
Obviously there is no way to really predict when this would happen, but I don't think it will be up to developers to decide whether it happens or not. In Texas for example, the legislature forced engineering to be professionalized (or regulated) in an emergency session after a school in a well off area exploded in a gas explosion (https://en.wikipedia.org/wiki/New_London_School_explosion#In...).
I also do not think this is limited to software engineering. Medical doctors and accountants have faced the squeeze in recent years too. There are tons of (bad) DO med schools opening up across the country that will be flooding the field before long, nurse practitioners and physicians assistants get to do more and more work that only doctors got to do, and more and more accounting is being offshored. The question is when things get so bad that even the powerful decide to actually do something about it.
I also do not think this is limited to software engineering. Medical doctors and accountants have faced the squeeze in recent years too. There are tons of (bad) DO med schools opening up across the country that will be flooding the field before long, nurse practitioners and physicians assistants get to do more and more work that only doctors got to do, and more and more accounting is being offshored. The question is when things get so bad that even the powerful decide to actually do something about it.
[deleted]
Im super curious to see how this actually does at finding significant bugs, we've been working in the space on https://www.bismuth.sh for a while and one of the things we're focused on is deep validation of the code being outputted.
There's so many of these "vibe coding" tools and there has to be real engineering rigor at some point. I saw them demo "find the bug" but the bugs they found were pretty superficial and thats something we've seen in our internal benchmark from both Devin and Cursor. A lot of noise and false positives or superficial fixes.
There's so many of these "vibe coding" tools and there has to be real engineering rigor at some point. I saw them demo "find the bug" but the bugs they found were pretty superficial and thats something we've seen in our internal benchmark from both Devin and Cursor. A lot of noise and false positives or superficial fixes.
[deleted]
so i just upgraded to pro plan but yet https://chatgpt.com/codex doesnt work for me and asks me to -try chatgpt pro- and shows me the upsell modal, even if already on the higher tier
sigh
sigh
same here. Paying for Pro ($200) but the "try it" link just leads to the Pro sign up page, where it says I'm already on Pro. Hyper intelligent coding agents, but can't make their website work.
> Hyper intelligent coding agents, but can't make their website work.
I know right
also no human to contact on support... tempted to cancel the sub lol i'll give them 24h
I know right
also no human to contact on support... tempted to cancel the sub lol i'll give them 24h
It says "Rolling out to users on the ChatGPT Pro Plan today" So it ll happen throughout the day
Same here, paying for Pro but I just get redirected to vanilla version...
They said Plus soon, not today.
[deleted]
Where can I read OpenAI's promise that it won't use the repos I upload for training?
[deleted]
[deleted](1)
bilal4hmed(1)
[deleted](1)
_jayhack_(1)
If you still don't think software engineering as a high paying job is over, I don't know what to tell you.
My counterargument: https://agifriday.substack.com/p/jevons
Short version: Jevons's paradox means that the more coding you automate away for developers (like with compilers in the past), the more in-demand those developers are. (Until AGI when all bets are off, of course.)
Short version: Jevons's paradox means that the more coding you automate away for developers (like with compilers in the past), the more in-demand those developers are. (Until AGI when all bets are off, of course.)
It might be over in the future, but it's still fine for the next few years at the minimum.
It's high paying?
We’ve long used local agents like Cursor and Claude Code, so we didn’t expect too much. But Codex shines in a few areas:
Parallel task execution: You can batch dozens of small edits (refactors, tests, boilerplate) and run them concurrently without context juggling. It's super nice to run a bunch of tasks at the same time (something that's really hard to do in Cursor, Cline, etc.)
It kind of feels like a junior engineer on steroids, you just need to point it at a file or function, specify the change, and it scaffolds out most of a PR. You still need to do a lot of work to get it production ready, but it's as if you have an infinite number of junior engineers at your disposal now all working on different things.
Model quality is good, but hard to say it's that much better than other models. In side-by-side tests with Cursor + Gemini 2.5-pro, naming, style and logic are relatively indistinguishable, so quality meets our bar but doesn’t yet exceed it.