Coding is not solved

hanifbbz

Author here: thanks whoever shared this here. I love the brutal criticism and critical thinking of this community. I'm also fully aware of the emotions this stirs. If it makes you feel better, I'm not here to change anyone's workflow but I'm fed up with paying full price for degrading service. Just last week Github went down due to a stupid retrial error. We also had AI agents going rogue and hacking companies and governments. I use AI (specifically LLMs) every day since they came out 4 years ago. I also build AI-powered products. This is not about being anti-AI. I'm just fed up with slop being pushed as progress. Get your sh*t together. That's all. If anyone has counter-arguments or cares to make me smarter, I'm all ears.

N_Lens

"Coding is solved" will eternally remain 6 mo away, as long as the investors keep pumping in money.

federicobrancas

coding is solved, software engineering not.

vatsachak

Coding is not solved but this article hasn't accounted for opus 5.5 yet. Long term planning in LLMs has not been solved.

antonmks

GitHub Copilot is now written entirely in Rust, with AI agents doing most of the porting work. The migration cost about $120,000 in AI token usage plus about three weeks of a developer's time. The effort updated the runtime module-by-module until the job was completed, spanning over 135 releases across a 14.5-week time period. 430,000 lines of TypeScript were converted into 800,000 lines of Rust.

j45

Coding might not be solved out of the box with these providers, but there are increasingly setups and harnesses that do have a great deal of it solved.

askonomm

What I've found is that AI allows lazy and incompetent developers to be more lazy and more incompetent. This then has the effect that product quality suffers more, faster. As a result of the sheer amount of code now being pushed out, code reviews, a thing that previously somewhat prevented lazy and incompetent developers from pushing out horrible code, is effectively dead in the water since no human can actually review such amounts of code realistically anymore. Some companies have adopted AI to review code, which, well ... you have AI make code, AI review code ... I hope you can see the stupidity here if you expect to see any deterministic results at all. I guess time will tell if the consumer will adapt to the lower quality of products, allowing companies to justify the existence of lazy and incompetent developers, or if the consumer will push back, forcing companies to increase the quality of their developers. Note: I use AI every day and it is entirely possible to create high quality software with it, so long as you are not lazy and incompetent.

bushido

It's very interesting. I'm very enthusiastic about AI and coding, But I find myself agreeing with the author. Coding is not solved. Instead, I think what's closer to solved and what we're in the process of solving is product development. Story: A while ago, I had a few programmers who were really, really fast almost always missed the mark on the assignment wrong. I loved having them on projects because in the time my senior precise engineers could deliver a MVP, the fast engineers would build the wrong thing, collect feedback, reiterate, build the wrong thing, collect feedback, eventually inching closer and closer to a product people would pay for, and it would almost always get delivered faster than my seniors. I feel AI does the same thing.

grim_io

For a non-ai article, this sure has a lot of bullet point lists combined with check marks. I don't like the feeling being judged and tested by the author (missing number 5 point in the list).

hibikir

> You cannot be responsible for what you can’t control either. That understanding is key to reasoning about system behavior and fixing it when the AI inevitably fails. This is not a good premise. All over law, you will find people made responsible for what they don't control and they kind of own. Unleash a dog that harms a child, or just have it in an environment where it can escape, and see what happens. There is such things as unpredictable situations where one might not be held responsible, as a problem might occur well past reasonable guidelines. So of course you can be held accountable for what an AI that uou supposedly cannot quite control does, or for the AI-written code you deliver. Treat it like the releasing a wolf pack, or selling an unsafe toy that can maim children. There's precedent everywhere.

jstummbillig

> AI cannot be held accountable. It cannot suffer any consequences. The worst thing you can do to AI is to unplug it. And although it mimics human emotions (due to training data), it couldn’t care less. AI doesn’t die either. It cannot suffer a prison sentence or fines. You cannot punish AI, therefore it can never be held accountable. Dear lord. Is that supposed to reflect the average thoughts and motivation of a person you want to hire? Or that of their employer?

IshKebab

Yeah this guy's arguments are bunk. He goes on about how LLMs are nondeterministic... as if humans aren't! Doesn't matter what you think about AI, "it isn't perfect" is clearly a nonsense reason not to object to it.

gradus_ad

The process of writing code is the process of clarifying your own thought and being forced to answer questions that may not have been obvious before. To the extent that AI makes assumptions, it introduces bugs and incorrect code, maybe not from the perspective of the code in isolation, but from the broader context it lives in. To the extent it doesn't make assumptions and asks you, well that assumes it knows what should and shouldn't be assumed and that's not necessarily something AI can know a priori.

vmg12

Not a fan of the article even though I somewhat agree with the title depending on your definition of coding. AI can write CRUD API endpoints almost perfectly now. It can also write quicksort, a heap, whatever much quicker than I can. It really sucks at designing types and apis though and when it creates types and apis it doesn't think or plan for the future way the system will evolve (even if it's known up front how the system will evolve). I suspect this will remain a problem for the models for a long time. All the things that the models are currently good at are the low hanging fruit of reinforcement learning for coding. Think about the kind of reinforcement learning environment that needs to be created to train a model to become good at building and designing large scale software end to end. It would be a slog because you need to build the large scale software up front and then break it down to train the model to construct it in a systematic manner that allows for the software to evolve. And then you need enough of these training environments for it to generalize. I think they will eventually figure it out though but it may take a while.

efficax

Reading the code does not mean you understand the code. One lesson that experience in software gave me: I never understood the code. You think it works a certain way, until you find out that it doesn't. What LLMs make possible is for me to say: find out all the ways this thing works. Analyze the different ways we can run this software, build a fuzzer, build property tests, and run this software in every scenario possible. Log full traces. Log all the outputs. Now, analyze each scenario for bugs. You can't do that by hand. If we are committed to it, if we put the resources towards it and dedicate the time to it (and we could do this just by saying: it will take half as long as it used to take!), software built by llms in healthcare, finance, automotive, defense, power plans, aviation, manufacturing can all be made MORE reliable and better with LLMs... without ever reading a single line of code. The LLMS are very good at logic, by the way. Anyway all of this reads like someone who is not actually using LLMs to build software or hasn't tried them in a while. I felt the same way in 2025. I've written 100s of thousands of lines of difficult code. You, the person reading this, has probably interacted with software I've written. For a time you would've interacted with it every time you made a debit card transaction in the united states, for example. I understand code, and care about quality, and that's why I'm all in on LLMs for code.

Sevii

"Most software that requires hiring and paying software engineers has low risk tolerance" The problem is that this statement simply isn't true. Most software engineers do not work on low risk tolerance code.

rkozik1989

The problem with LLMs is that: popularity of an answer != correctness. That concept might work a lot of the time but you will definitely run into situations where that'll never produce a correct or working response. To actually learn something you need an environment/playground to apply what you think you know and observe the results. Without that you're not really learning, you're jus regurgitating what people want to hear.

giovannibonetti

> Most software that requires hiring and paying software engineers has low risk tolerance: I think a few of the industries listed like defense and aviation have low risk tolerance. However, from my (somewhat brief) experience of working in two health techs for a couple of years, I strongly disagree that healthcare has low risk tolerance for tech. Granted, they make run-of-the-mill CRMs, but I was baffled at how tolerable it is to have egregious user experience that makes users waste multiple hours per month with clerical work that is very painful because the UIs are very slow and buggy.

rgoulter

> People who claim “LLMs can write decent code” don’t understand how code works. It's not clear to me if the claim is: (1) "If you used an LLM to generate code, and the code works, you're wrong if you think the code is okay" or (2) "If you used an LLM to generate code, you reviewed the code and found it to be of decent quality, then you're wrong". > If you’re toying around, LLMs do a great job. That’s why some of the most aggressive proponents of the “coding is solved” narrative have nothing to show for it. I also don't get the "LLM proponents have nothing to show for it" statement. It's really quite common now to see on HN all sorts of LLM-assisted programming projects. The quality varies from slop where little thought was put into it, to high quality results where LLM coding assistance was able to let talented developers produce things they otherwise wouldn't have time to do. I'd say it's obvious that LLM coding agents can be very useful for a lot of programming related tasks. EDIT: That is to say, LLMs are obviously useful for use cases above/beyond toying around. It's not a dichotomy between "I'm never touching an AI" and "thoughtlessly accepting everything the LLM outputs".

metalspot

The audacity of publishing self-promotional AI slop clickbait claiming that AI can't code and everyone who doesn't agree with your asinine assertions is incompetent is bold. Respect the hustle I guess. But to anyone even vaguely thinking of taking this seriously, go look at what antirez, dhh, jared sumner, mark brooker, and many other real engineers who have ship real things are doing and saying. Most of these people have spent their entire lives contributing to open source, and they have proved their skill shipping working software and scale for decades. They are really trying to help people by showing and telling them exactly how AI works and how to use it to make better software.