Show HN: Dev atrophy test – Can you still code without AI?
41 comments
I am not worried about personal atrophy. I am worried about young people who never learn the fundamentals and blindly believe everything the llm say.
computer science is not social science
if your code doesn't work it doesn't work
you can't bullshit a computer
for people that are doing social science it's an issue
but they where way past the point of no return already so it doesn't really matter
if your code doesn't work it doesn't work
you can't bullshit a computer
for people that are doing social science it's an issue
but they where way past the point of no return already so it doesn't really matter
> if your code doesn't work it doesn't work
Code can definitely only sort of work: only works on the happy path, only works on the computer it was developed on, only works for some versions of some dependencies, only works when single threaded, only works when the network is fast enough, only works for a single user at a time etc etc etc.
Code can definitely only sort of work: only works on the happy path, only works on the computer it was developed on, only works for some versions of some dependencies, only works when single threaded, only works when the network is fast enough, only works for a single user at a time etc etc etc.
yes so then you have a combination of code that works and code that doesn't work
and the code that doesn't work doesn't work
and the code that doesn't work doesn't work
Software engineering is way more of a social practice than you probably want to believe.
Why is the code like that? How are people likely to use an API? How does code change over time? How can we work effectively on a codebase that's too big for any single person to understand? How can we steer the direction of a codebase over a long timescale when it's constantly changing every day?
Why is the code like that? How are people likely to use an API? How does code change over time? How can we work effectively on a codebase that's too big for any single person to understand? How can we steer the direction of a codebase over a long timescale when it's constantly changing every day?
Yes that is very true but social science is more of a social practice than computer science
If you run your organization badly, you'll run into problems sooner, than if you are in social science, where you just have to say all the buzzwords and they'll just rubberstamp you true
If you are arguing that my point is that computer science would be 100% falsifiable and social science is 0% falsifiable then you're argument is a bit of a straw man
If you run your organization badly, you'll run into problems sooner, than if you are in social science, where you just have to say all the buzzwords and they'll just rubberstamp you true
If you are arguing that my point is that computer science would be 100% falsifiable and social science is 0% falsifiable then you're argument is a bit of a straw man
> Why is the code like that? How are people likely to use an API? How does code change over time? How can we work effectively on a codebase that's too big for any single person to understand? How can we steer the direction of a codebase over a long timescale when it's constantly changing every day?
At which point you are studying project management theory, or whatever you call it
At which point you are studying project management theory, or whatever you call it
I’d argue that computer science is on a gradient between social science and physics.
I'd argue that anything that has science at the end isn't :)
Materials science rolls its eyes every time it hears that hoary joke.
Code can absolutely "kinda work" or "mostly work"
aha and if it mostly works there are parts that doesn't work right?
>if your code doesn't work it doesn't work
you can't bullshit a computer
this is wrong. I would argue the difference between a junior dev/intern and a senior engineer is that while both can write code that works, the juniors find local maximas, like solutions that work, but can't scale, or wont be very easy to integrate/add features on top/maintain etc.
This happens in maths, biology, in all science fields. Experience is partly the ability to take decisions between options that both work.
This is why coding assistants are amazing at executing things you are clear on what you want to do, but can't help (yet) on big picture tweaks
you can't bullshit a computer
this is wrong. I would argue the difference between a junior dev/intern and a senior engineer is that while both can write code that works, the juniors find local maximas, like solutions that work, but can't scale, or wont be very easy to integrate/add features on top/maintain etc.
This happens in maths, biology, in all science fields. Experience is partly the ability to take decisions between options that both work.
This is why coding assistants are amazing at executing things you are clear on what you want to do, but can't help (yet) on big picture tweaks
Right I'm not trying to be argumentative here, I see where you are coming from right.
My point being that it's quite easy to demonstrate that it can't scale, by running an experiment.
Meaning that you could quite easily BS your way through that by just agreeing with whatever the status quo is.
Whereas in social science you can't do an empirical experiment, so you're epistemologically on much much more shakier ground
> This happens in maths, biology, in all science fields Right but I wrote social science and not maths or biology.
For instance if someone where to say that due to Hegelian Dialeticts and gender critical theory, in the future women are destined to rule the world, this is a good thing, and this will lead to the abolishment of racial inequality and exploitation through capitalism
how do you prove that?
in comparison if the problem is that your software isn't efficient when there are over 100 instance, you can prove that by spinning up 100 instances?
You can't clone earth and force all the inhabitants to enact ideologically pure race critical theory, and then ask the inhabitants in the control group to try out nazism, wait for a while and then use that to prove that one or the other is the best way can you?
My point being that it's quite easy to demonstrate that it can't scale, by running an experiment.
Meaning that you could quite easily BS your way through that by just agreeing with whatever the status quo is.
Whereas in social science you can't do an empirical experiment, so you're epistemologically on much much more shakier ground
> This happens in maths, biology, in all science fields Right but I wrote social science and not maths or biology.
For instance if someone where to say that due to Hegelian Dialeticts and gender critical theory, in the future women are destined to rule the world, this is a good thing, and this will lead to the abolishment of racial inequality and exploitation through capitalism
how do you prove that?
in comparison if the problem is that your software isn't efficient when there are over 100 instance, you can prove that by spinning up 100 instances?
You can't clone earth and force all the inhabitants to enact ideologically pure race critical theory, and then ask the inhabitants in the control group to try out nazism, wait for a while and then use that to prove that one or the other is the best way can you?
being good at software design isn't about memorizing the specific details of a single language or subjects
languages are subject to change
hire people who are good at finding information
not someone who is good at blindly memorizing details of a specific instance of a language or system
someone who memorized every single detail of COBOL will be a worse coder than someone who spent time thinking about abstract thinking and problem solving
you'll want to double check everything anyway
this shows of a fundamental lack of insight into what it means to be a good developer
it's like someone who thinks they are smarter than everyone else because they spent thousands on hours on playing chess
this student who has memorized the full specification of HTML, CSS and Javascript will be useless if you ask them a question about lets say Erlang, and is easily replaced by a book
languages are subject to change
hire people who are good at finding information
not someone who is good at blindly memorizing details of a specific instance of a language or system
someone who memorized every single detail of COBOL will be a worse coder than someone who spent time thinking about abstract thinking and problem solving
you'll want to double check everything anyway
this shows of a fundamental lack of insight into what it means to be a good developer
it's like someone who thinks they are smarter than everyone else because they spent thousands on hours on playing chess
this student who has memorized the full specification of HTML, CSS and Javascript will be useless if you ask them a question about lets say Erlang, and is easily replaced by a book
So as someone who's not written Javascript in a decade, this on the face of it seems wrong to me:
Your example correct answer to "Write a function that returns the sum of two parameters" is
Your example correct answer to "Write a function that returns the sum of two parameters" is
function myFunction(example) {
example
}
The vibe giveth, the vibe taketh.
This worked but ai wants to rewrite whole files all of the time so it broke. Our designer fixed the issue now.
This worked but ai wants to rewrite whole files all of the time so it broke. Our designer fixed the issue now.
Always love a fun quiz, but some of the example answers are just incorrect. Eg: `document.example('example')` to select a HTML button element. Others are to rigid to allow the true breadth of correct answers.
Ya'll might want to switch from V0 to claude code.
Ya'll might want to switch from V0 to claude code.
It worked on my machine! seems v0 changed how it makes examples when it shouldnt.
> no handholding
I still feel more like the LLMs are the ones who need the handholding.
I still feel more like the LLMs are the ones who need the handholding.
"Questions cover HTML, CSS, JavaScript, databases, and Node." Ah yes, as if Web development = All coding
You are right, it should just focus on React really.
Someone spending too much time in wonderland. Code already ate through your common sense. Next.
some of the tests and standard answers are strange such as the one with debounced function not considering whether there should only be 1 arg / the dev could use the arguments keyword and call, the filter numbers question insisting on === instead of == etc etc.
Typical of the dark side of HN, thinking that web programming represents software development, instead of being just one kind of information systems, which are a subset of software applications.
Have you even dogfooded your quiz once before publishing to the Web?
> JS methods to select an element
> YOUR ANSWER
> getMethod: "getQuerySelectorAll"
> EXAMPLE CORRECT ANSWER
> const button = document.example('example');
TypeError: document.example is not a function
----
> Create an HTML form with an input field and submit button:
> YOUR ANSWER
> <input type="submit">Submit</input>
> EXAMPLE CORRECT ANSWER
> <button type="submit">Submit</button>
Not incorrect answer assessed as incorrect.
> JS methods to select an element
> YOUR ANSWER
> getMethod: "getQuerySelectorAll"
> EXAMPLE CORRECT ANSWER
> const button = document.example('example');
TypeError: document.example is not a function
----
> Create an HTML form with an input field and submit button:
> YOUR ANSWER
> <input type="submit">Submit</input>
> EXAMPLE CORRECT ANSWER
> <button type="submit">Submit</button>
Not incorrect answer assessed as incorrect.
Your button answer is wrong though because the input tag can't have content. The version using input should be <input type="submit" value="Submit" />.
Having said that, I did just get marked down for having filter(num => num % 2 === 0) when the correct answer shouild (apparently) be filter(x => x % 2 === 0) so it's not great.
Classic vibe issue of it regressing how the examples are generated. Will check it.
Not sure what you expected, they built it with AI lol
I don’t see in which context coding without aid is helpful:
- at work, nobody cares. They only want shipped features.
- at home, I only care about having fun (and that doesn’t necessarily mean to not use tools like ides, llms, autocomplete, etc)
- at work, nobody cares. They only want shipped features.
- at home, I only care about having fun (and that doesn’t necessarily mean to not use tools like ides, llms, autocomplete, etc)
it's helpful for them, because it means they can get a lot of VC money by putting some ugly 4chan meme pictures on a website in order to get attention
Just made for fun, we are self funded.
I sometimes code light swift scripts in vim without autocomplete. Not saying everybody should, but it’s fun to me, and convenient.
> This is almost always a consequence of relying too much on ChatGPT and vibe coding tools.
How do you know it's not because they are to put it bluntly stupid or lazy?
How do you know it's not because they are to put it bluntly stupid or lazy?
[flagged]
I'm Per from Scrimba (YC S20), the code-learning platform.
There's been a lot of talk lately about whether AI tools are causing skill atrophy amongst developers. We get a front-row seat to this, and we see more and more students struggle with basic concepts, and building apps on their own. This is almost always a consequence of relying too much on ChatGPT and vibe coding tools.
So we built a small side project: https://devatrophy.com
It's a test of your core web dev knowledge — no handholding, no back rubs, no AI autocomplete. Just you, your brain, and 10 questions. There are three levels (Noobie, Le Chad, Hardcore), and the questions cover HTML, CSS, JavaScript, databases, and Node.
You’ll get a score at the end, plus a downloadable certificate for bragging rights (or public shaming).
Would love for you to try it and tell us what you think. And would be curious to hear if you're feeling any signs of "dev atrophy" yourself, or in your team?
PS: Ironically we decided to produce it by vibe coding on V0. Oh the irony.