https://meru.org/

Run it on a throwaway system, pick a codebase you’ve always wanted to fix something about but didn’t have the time. Like you wanted to do a major refactoring or do a library migration to a better maintained library. Or you want to rewrite part of a program in rust for performance/security improvements.

The hardest part for me is sometimes it is hard to write what I want in a prompt; but you don’t have to put everything into the prompt, you can make a code edit as an example and then say; look at this diff, it is doing X; look for and apply this some transformation across codebase Y

If you have a good codebase, AI will have good patterns to follow and will produce pretty good code; and you can quickly iterate on the results (maybe over new context windows) and get high quality code that looks very close, if not indistinguishable from the pre-existing code.

AI is a great editor; I can finally do all the refactors that I wanted to do that were much harder before; would have taken a long time.

AI is great at writing tooling, I love a good tool that gets the task at hand done; encodes a task that others will need to do. Couple that with a skill file and now a fuzzy tech debt migration can actually be completed across many teams at there pace.

I focus on the cheapest model/fastest model (been using Luna). I use pi and don’t try to multiplex my time, and stay in flow on a specific task till it is done. And I’m very happy with this, actually enjoy this more. Vim skills stay useful for editing the prompts/module structure/fixing slop code during review/ and review.

The volume of code is high so reading a diff is suboptimal for review; so I tend to review from local checkout using vim (LSP tooling important during review, go to def, etc).

I see almost zero reason for anyone to use anything else for they’re base system at this point.