RicDan
Joined 3 years ago
Joined 3 years ago
This is also my biggest gripe with AI. I.e. for specifications, no matter what hype machine I tried, it never fulfilled my criterias, which are: easily verifiable, concise, small specs. Hence I built https://github.com/RicardoMonteiroSimoes/Yamlet initially for claude code, but then decided to use extend it for pi.dev. I now have a dedicated docker image for pi.dev, that only contains Yamlet plugin, and whenever I work on spec I spin it up.
The end result is a .yaml file that easily works in git + git diff, so that I can then proceed with the technical specs-
I have always hated how we deal with feature flags; often times as a dev I implement it, but then business decides how the flags are used, which comes back to us having to set them. I want to make this something that can be used by both easily, and priced fairly - looking at how much others charge for a feature flag SaaS is insane.
Currently I'm in heavy testing by myself, as I am quite worried about issues (that's just my personality), but yeah. It started as a normal side project for me to train a bit, then I added a bit of agentic coding to it to also learn it, and now it's here.
I guess for mistral it's great marketing material.
Edit: Quite interested in the differences of local optimizations... that does allow for specific sensorship, but alas that's already possible in a more direct, reliable way.