harness-engineering

An AI harness defines the control system around an autonomous agent, governing what it may edit, how it receives feedback, and where it writes state. It prevents state drift and objective corruption during long-running autonomous loops.

Design a durable harness by defining surface classifications, implementing durable logs for state persistence, and setting up governance gates with explicit human approvals to control irreversible actions and prevent objective drift.

Surface classifications separate the agent from its environment by defining boundaries: Locked surfaces restrict changes, Editable surfaces allow modifications, Append-only surfaces log events sequentially, and Human-controlled surfaces require explicit approval.

You need governance gates and human approvals when running production-like agent sessions, research loops, or experiment pipelines where irreversible actions occur, ensuring PR preparation, review, and deployment follow strict audit trails.

Durable logs and threshold rubrics enable fast, deterministic loops by maintaining locked metrics and audit trails. This ensures the agent operates within defined boundaries and prevents state drift over long autonomous sessions.

Yes, harness engineering applies directly to research loops and experiment pipelines by providing mechanism registry support, novelty gates, and governance handoffs to manage durable state persistence and safe autonomous operations.