Comment by tenacious_tuna

> Lots of tips on how to do this out there but one thing I do is have it try, throw away everything it it did, and try again with a completely restated question

This is the thing that worries me about AI/LLMs and how people "profess they're actually really useful when you use them right": the cliff to figuring out if they're useful is vertical.

"You’ve still come out ahead even if you take over fully."

I just finished a weeklong saga of redoing a bunch of Claude's work because instead of figuring out how to properly codegen some files it just manually updated them and ignored a bunch of failing tests.

With another human I can ask, "Hey, wtf were you thinking when you did [x]?" and peer into their mind-state. With Claude, it's time to stir the linear algebra again. How can I tell when I'm near a local or global maxima when all the prevailing advice is "I dunno man, just `git reset --hard origin/master` and start again but like, with different words I guess."

We have studies that show people feel like they're more productive using AI while they're actually getting less done [1], and "throw away everything it did and try again" based on :sparkle: vibes :sparkle: is the state of the art on how to "actually" use this stuff, I just feel more and more skeptical.

[1]: https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o...