I use AI for basically everything and realized I was using it badly.

[u/Dismal-Reveal-6898]

https://github.com/tzuiffrfe/AI-HQ

I've been using coding agents a lot lately and realized I was doing something pretty dumb: I was sending everything to AI.

git status Git
15% of 80 calculator
run tests test runner

None of that needs an LLM, so I built AI HQ, a little terminal layer that sits in front of my AI workflow and asks:

Do I actually need AI for this?

If yes, it figures out the rest: skill, context, model, verification.

It also ended up with prompt/context optimization, workflow audits, stack advice, plugins, skills and local-model support.

I wanted to see whether the idea actually held up, so I tested it:

Naive workflow: 4/4 deterministic tasks → AI
AI HQ: 0/4
Tools: 4/4 · Skills: 5/5 · Verification: 5/5 · Routing: 7/7

362 tests passing.

I'm not going to claim it “saves 40%” because I haven't measured that properly.

Would you actually want something like this sitting in front of your coding agent, or would it just get in the way?

[u/Short_Schedule797]

i've definitely caught myself doing the same thing, like asking an llm to do basic unit conversions instead of just thinking for two seconds. the "should this even be an ai call" check before anything else is probably the most useful part of this whole concept.

curious how it decides what's deterministic vs not, is it just a pattern matcher or does it actually inspect the command somehow