> Anthropic has never advocated for a ban on open-weights models.

This is not an unqualified never. The very next sentence makes a qualified statement: "Open-weights models that don’t have dangerous capabilities are a public good". That prompts the question, what about ones which do have "dangerous capabilities"? Are they not a public good? If not, then should they be banned? Who gets to decide on the definitions of these terms?

But then you're back at the question from the OP of "why not?" Is it lack of good examples in the training data? Is there something of code "goodness" that goes beyond phenomenon that are measurable? Is it that LLMs lack in the ability to organize and think abstractly?

I don't know if it's a question of how many features to feed to the model, either. Of course, overwhelm the context with too many features and it will get confused. But that's where the memory management idea that G. Huntley talks about is helpful. You're trying to steer the model within its memory limits towards a certain goal.

The problem is getting it to produce "good" code. Formalizing what that means is the task of the programmer. How do you steer a model towards always, or more often, producing good code so that you don't have to do rework? That's the same problem as with a junior engineer, but the way you do it is different. Right now we're trying to do it with mountains of prompts — which sort of works but has diminishing returns — and with onerous code reviews. We've seen this get better over time, but I think some more mechanical methods will help as we figure out how best to steer the models.

I feel like the explanation does nothing to actually elucidate why models can't do it. Is it an inherent weakness of LLMs? Training processes? The typical "this is crap" that we constantly hear? It goes on to write about RL and how there's no penalty for bad design. But that sort of side-steps the question and makes you ask: "why not do RL and make a penalty for bad design?" Of course the models aren't good at it ... they're not good at anything until you've tuned them and put them in a harness that rewards good edits and throws away (improves) bad edits. That doesn't explain why "models can't do software maintainability." The real question is why harnesses can't do software maintainability, and how to build a system that can do it. (I suppose that's the purpose of the ad at the bottom of the page.)