AI Feedback Loops: Building Systems That Stay Correctable

TL;DR AI feedback loops do not improve a system merely by preserving more outputs. An unsupported explanation can return through retrieval as apparent evidence, even when model weights never change. Separate generated material from approved knowledge, identify which component a correction should change, and enforce permissions outside the model. Test withdrawal, retries, policy changes, and recove