I went from just coding manually, to using LLMs for "surgical edits", to "woah, AGI!", to "haha whoops, not even close", to just coding manually (my brain still works!), to "surgical edits" again.

My current approach is "ask for very small diffs" + "review them very carefully".

I'm not working a job though, I'm working on a multiplayer game.

Main findings: The frontier models can't reliably modify Pong without breaking it, so their skill appears to be quite domain-specific. (OK, to be fair, neither can I half the time!) This is probably because they are "time blind". I had one model try to test a game by running it at 0.1 frames per second and shoving each frame in the vision API...

If you leave any room for a misunderstanding, they will laser in on do it and do the stupidest thing possible. If you're not checking everything carefully, you will discover this later, and you will cry.

Formal proofs, oddly enough, do not improve the situation: they will simply prove mathematically that the absurd and pointless and backwards implementation is completely without defects. (It obviously does help within an implementation, though.)

They can't formally prove what the hell you meant when you told them to build something. That job remains frustratingly human!

Current dissatisfaction: (1) Harnesses are designed for super bloated codebases (i.e. designed to load as little context as possible) which make them pretty clunky for small repos and small edits. (I had a Surgical Edit Tool I need to bring back...), (2) Current LLMs are anal about verifying the most trivial change, even without prompting, even if it's impossible for them to verify it because they're blind so they start measuring pixel data in Python... Both of which eat up Speed and Cost, taking the work even further from Realtime/Interactive to Tedious/Sad.

AI Coding Without the Vibes