Conclusion

An agent improvement loop offers a path toward continual improvement without reducing the problem to prompt tuning alone. The full loop matters: traces capture behavior, human feedback adds judgment, evals preserve what the system should do, HALO turns the evidence into ranked harness changes, and Codex can implement the next pass.

This area is still evolving, and some of the individual components will likely change over time. The larger idea of loop engineering is the durable part: agents can improve from real behavior when feedback, testing, and implementation are connected in one loop.