How I structured logs around Hindsight

“Why did it reject a perfect resume?” I dug into the logs and realized Hindsight had quietly rewritten the agent’s scoring logic based on one bad feedback loop. job sense ai “Why did it reject a perfect resume?” I dug into the logs and realized Hindsight had quietly rewritten the agent’s scoring logic based on one bad feedback loop. What I actually built This project is a job matching agent that reads resumes, scores candidates, and ranks them against job descriptions. Nothing fancy on the surface: parse resume → extract features → score → return top candidates. The interesting part is that the scoring logic isn’t fixed. I wired it up with Hindsight GitHub repository so the agent could learn from feedback—things like: “This candidate should have been ranked higher” “This profile is irrelevant despite keyword match” Instead of retraining a model, I let the agent adapt its behavior by replaying past decisions and corrections. How the system is structured At a high level, the code splits