Thats… not my experience. Like, not at all. They very regularly get lost

They're not bound by the same limits but they're still bound by some limits, yeah?

I'm not an AI expert, so I don't honestly understand why LLM driven agents are as good as they are. But my impression is "trace every caller", most of the time, is still an approximation. Once the code has gotten convoluted enough, cases are going to get dropped.

Refactoring used to have a very real cost - it was substantial amounts of time that would have to be carved away from working on new features.

Now I can spot a potential refactor, fire off a prompt in an asynchronous coding agent (or on a worktree or whatever), then come back 20 minutes later and either accept it, poke it a bit, or abandon it. Costs me almost nothing.

As ever, no one is willing to allocate time for this, but (with unlimited work tokens) I can parallel path massive cleanup refactors all the time now.

I've yet to work at a place that bothered with much refactoring over adding the thirtieth conditional to new feature....

Your discipline only pays off if you already understand your code and/or established clear baseline for your standards before launching into a feature development mania. And it needs to be enforced every turn, or the firehose of code generation knocks the front door down easily.

I've always _wanted_ my code to be clean and easy to follow but life, deadlines, shifting-priorities, etc have stood in the way of that. Now I can finally realize my personal nirvana.

That said, I've had to steer models away from too-heavy of abstraction or similar because it made the code too hard to follow.

Often times it's not even that the code is bad but rather that it's overengineered. I see it happen so much that I'm tempted to actually go the other way on a toy project. Like what would Claude or Codex come up with if I told it I wanted an enterprise grade, globally scalable, compliant and auditable tic-tac-toe game.