Working on my 3rd production AI deployment. Everyone talks about "systems that learn from user feedback" but in practice I'm seeing:

Users correct errors

Errors get logged

Engineers review logs weekly

Engineers manually update model/prompts -

Repeat This is just "manual updates with extra steps," not a real flywheel.

Question: Has anyone actually built a fully automated learning loop where corrections → automatic improvements without engineering?

Or is "self-improving AI" still mostly marketing?

Open to 20-min calls to compare approaches. DM me.