

Fable was “just ask and get it done” quality level, but really I don’t get THAT much bugs - about the same amount that I see irl developers do: get a new feature, find 5 problems, get them fixed, find one more, done. As a recommendation - try to alleviate the biggest problems that ai models have:
- overconfidence - skipping wrong stuff “because they have a note saved that it works” or losing the point where they stopped after a session broke, then making things up. Test Driven Development solves the majority of problems like that - when Claude writes tests first, then it’s not able to bullshit me that the job is done when “everything is red”
- even with large contexts, they run out and stuff gets lost. So if you’re not doing something really compact, make your ai document everything, document the feature they are working on now, make it then offload it to permanent doc when that piece is finished. When the ai will fuck up next time, you can tell it to “go read some docs” and most of the times it will work



Problem solving, from simple to hard. I did a lot of stuff on Codewars, and moved from trivial stuff to more complex in course of a few months. It’s not like I got really far, but for me it’s motivation problem, not a method problem