I long for the day when someone can give advice based on their own personal experience without someone else being like “well that won’t work for literally everyone”
> deploy thousands of lines of code to production without you needing to change a single thing.
I’m not saying this is impossible. I’m saying it leads to poor quality products. Deploying thousands of lines of code isn’t necessarily a good thing. Often it’s not.
> You can write a very precise spec in the prompt. Use formal language, or use a little DSL you invent on the spot, or say "it should do X and Y and account for Z and also try to cover other things if you realize there are more", etc. There's a lot you can do.
At this point, why use an LLM at all? Why introduce a black box? We can perfectly and tractably convert formal languages into machine code.
Things are never simpler when black boxes are involved…
These tools, again, are undoubtedly useful and sometimes (albeit inconsistently) magic.
But they’re not a silver bullet for making software.
I tried vibe coding literally yesterday, as I do every week or so. I used avvante.vim and code companion. I tried with gemma3 and Claude.
It’s slow, boring,and I (someone with ADHD) lose all focus when the llm starts running.
The output is prototype quality always. It looks okay and mostly works correctly (granted I usually just make a todo list or a job board) but is obviously over complicated and bloated.
If you don’t care about quality or long term maintenance (like with a prototype or POC) then it’s fine.
you're talking about specifically using genetic programming to create new programs as opposed to gradient decend in LLMs to minimize a loss function, right?
How would you construct a genetic algorithm to produce natural language like LLMs do?
Forgive me if i'm misunderstanding, but in programming we have "tokens" which are minimal meaningful bits of code.
For natural languages it's harder. "Words" are not super meaningful on their own, i don't think. (at least not as much as a token) so how would you break down natural language for a genetic algorithm?
Either you're not relying as much on the AI as you think you are, or you're not really sure what "production quality" means.
It seems like you should know, so I'm going to bet that you're not entirely letting the AI drive.
Having the AI draft some code which you refine is a fine workflow. I didn't think it was before, but i've come around on that. I think it's also nice to have an LLM do a onceover to point out areas where I may have missed catching an error (like with JSON.parse in javascript or something.)
It's just not my cup of tea, personally. I've found that I'm faster writing code myself and treating an LLM as an assistant or rubber duck, but to each their own.
I'm referring to wholly AI generated code with no human input besides a prompt or "vibe coding." You literally can't put enough context into a prompt to have it write the exact code you'd need in every case. Your prompt would end up just being code at that point.
That's the whole point of writing code. Precise and exact instructions for a machine. You're not going to get that by adding a statistical natural language layer in the mix.
One might say blindly following hype is silly and cope too.
I’ve seen no indication that relying entirely on AI can produce quality software.
It can produce prototype quality code, just as it has since gpt-3.5. Advantages of technology is never considered. Security concerns are often missed. And, from what I’ve seen, the codebases are bloated.
For your avg crud app, much of that doesn’t matter. It starts mattering when you start having real business constraints, like server budgets or data compliance. If you don’t see that, then you don’t have enough real world experience yet. That’s all.
Remember how crypto was going to change everything? Or the metaverse?
We live in a period of extreme technological hype backed by insane company valuations.
Don’t get too fooled by market.
These tools are useful. They are here to stay. And they do not replace the entire field of programming nor the work that programmers do.
don't forget about the insane amount of marketing around AI code companies and how they put "vibe coding" in front of everyone's face all the time.
You tell someone something enough times and they'll belive it