Comment by OleksandrC

The code written by agents generally seems to reflect what you (the human driver) asked for. If you discuss the approach and architecture first, asking the right questions in the process, and then let it implement - the result is quite on point with the frontier models. Might need some minor touch-ups if agent missed some common conventions or guessed the expectations wrong (but again, salvageable with follow-up prompts). And when it comes to line-by-line logic within functions, I would argue that today's models are LESS likely to make a mistake in there than humans - especially if you cross-review with another model (e.g. "write with Claude, review with GPT").

Humans write slop too, you know. Just saying.