zlacker

>>tablet+(OP)
The argument that I've heard against LLMs for code is that they create bugs that, by design, are very difficult to spot.

The LLM has one job, to make code that looks plausible. That's it. There's no logic gone into writing that bit of code. So the bugs often won't be like those a programmer makes. Instead, they can introduce a whole new class of bug that's way harder to debug.

>>jszymb+JM
This is a misunderstanding. Modern LLMs are trained with RL to actually write good programs. They aren't just spewing tokens out.

>>mindwo+TN
No, YOU misunderstand. This isn't a thing RL can fix

  https://news.ycombinator.com/item?id=44163194

  https://news.ycombinator.com/item?id=44068943

It doesn't optimize "good programs". It interprets "humans interpretation of good programs." More accurately, "it optimizes what low paid over worked humans believe are good programs." Are you hiring your best and brightest to code review the LLMs?

Even if you do, it still optimizes tricking them. It will also optimize writing good programs, but you act like that's a well defined and measurable thing.

>>godels+0S
I don't know if any of this applies to the arguments in my article, but most of the point of it is that progress in code production from LLMs is not a consequence of better models (or fine tuning or whatever), but rather on a shift in how LLMs are used, in agent loops with access to ground truth about whether things compile and pass automatic acceptance. And I'm not claiming that closed-loop agents reliably produce mergeable code, only that they've broken through a threshold where they produce enough mergeable code that they significantly accelerate development.

>>tptace+471
> I don't know if any of this applies to the arguments in my article, but most of the point of it is that progress in code production from LLMs is not a consequence of better models (or fine tuning or whatever), but rather on a shift in how LLMs are used, in agent loops with access to ground truth about whether things compile and pass automatic acceptance.

I very strongly disagree with this and think this reflects a misunderstanding of model capabilities. This sort of agentic loop with access to ground truth model has been tried in one form or another ever since GPT-3 came out. For four years they didn't work. Models would very quickly veer into incoherence no matter what tooling you gave them.

Only in the last year or so have models gotten capable enough to maintain coherence over long enough time scales that these loops work. And future model releases will tighten up these loops even more and scale them out to longer time horizons.

This is all to say that progress in code production has been essentially driven by progress in model capabilities, and agent loops are a side effect of that rather than the main driving force.