continuous-agent-loop

To prevent an autonomous agent loop from churning infinitely, implement defined recovery actions and quality gates. These mechanisms ensure progress, validate outputs, and gracefully handle failure modes like repeated retries and cost drift.

The best strategies for continuous code refactoring involve orchestrating sequential or CI/PR loop types. These autonomous loops integrate evaluation harnesses to ensure code quality and execute defined recovery actions when errors occur during processing.

An evaluation harness works within an autonomous agent loop by acting as a quality gate. It automatically assesses agent outputs against defined criteria, ensuring progress and triggering recovery mechanisms if the agent encounters repeated failures.

Yes, you can use autonomous agent loops for RFC decomposition and exploratory generation. The loop orchestration supports various strategies including sequential processing, CI/PR control, and exploratory generation to manage different continuous workflows.

An autonomous agent loop experiences cost drift due to repeated retries and uncontrolled processing cycles. You fix it by implementing defined recovery actions and quality gates that interrupt failure modes and ensure controlled progress.