[andai]

> What is the cost of verifying the generated artifact meets requirements vs. a directly produced artifact? This is mostly a function of the task and the user, but also the generative model.

So this is the fun one for programming.

I let AI agents do some programming on my codebases, but then I had to spend more time catching up with their changes.

So first I was bored waiting for them to finish, and then I was confused and frustrated making sense of the result.

Whereas, when I am asking AI small things like "edit this function so it does this instead", and accepting changes manually, my mental model stays synced the whole time. And I can stay active and in flow.

(Also for such fine grained tasks, small fast cheap models are actually superior because they allow realtime usage. Even small latency makes a big difference.)

[lukan]

Yes, the more you let agents loose, the less you are in control and the more time you spend later cleaning up their mess.

It is tempting letting them loose, after they delivered unexpectedly good results for a while, but for me it is not worth it. Manually approve and actual read. (And manually edit CLAUDE.md etc. if necessary. )

[dreadnip]

This is exactly why I don't like those "swarm" approaches with 8 Claude Code's running in parallel. Every time I've tried it I instantly lose control and become out of touch with the codebase. The quantity of the produced output is simply too fast & large to follow, so I tune out and it becomes a 100% vibe coded project.

[dominotw]

start with good prompts and good intentions , drift into sloppy prompt vibecoding ,finally "still not working" prompt in a loop.

this has been my story in every one of my personal projects.