[agentultra]

Wild idea: just write code.

I know. It’s an unbelievable concept in this AI era. Write code? Isn’t that what dinosaurs did?

If you expect that a human will need to read and maintain that code you might as well write it for them. You’ll get annoyed by having to read overly-verbose copy-pasted code. So will they. So write the code yourself and bringo: you’ll fix things yourself and write things in a way that makes sense for other humans to maintain.

Or you can come up with a convoluted web of markdown files to try and coax your agents and loops to understand what future human maintainers will expect the code to look like.

I’m not sure what path will be easier in the long run. Anyone inherit a loop-based agent-driven code base yet and have to try to understand it?

[tzone]

I think people have outdated ideas on AI code quality. Latest ones (i.e. ones after Claude Opus 4.8) are a game changer. They now write better code than a lot of engineers. They are also able to understand much larger overall context and make less mistakes then most engineers would make.

Difference between something like Opus 4.8 and even 4.5 is massive, not even talking about difference between Opus 4.8 and Sonnet or Composer.

What i see online is that a lot of people are using cheaper models, stuff like sonnet or cursor composer or even latest cursor grok. But they aren't the same thing as using the best models. The difference in quality and correctness is huge.

[agentultra]

I always have to ask people, correct with respect to what?

The reason being that most software developers aren’t very good at specifying systems precisely enough that they can confidently determine whether their program does what they think it does.

We don’t need to specify systems to the rigour of mathematical proofs every time, of course. The point is that spoken language isn’t precise enough to measure correctness against.

When you suggest that the difference in correctness is huge, I can’t really understand what you mean. Correct with respect to how you think good software should be written? Correct with respect to informal specifications written in prose? How?

I know that the frontier models have large contexts and can compress a lot more tokens from their training sets. But how does that make it able to read your mind and make formal what is ambiguous or informal?

[bodash]

It’s not crazy. I always add a simple message to my prompts: “leave 20% solutions empty and I’ll implement them myself”.

It work wonders for me.