Loop

Automating iterative refinement requires running complete algorithm cycles with human review between iterations to progressively approach an ideal state. This approach enforces loop modes to track iteration counts and maintain history for long-running targets.

Running multiple algorithm passes involves executing full cycles of observation, planning, building, and verification on a target configuration. It supports resume and status queries to handle progressive refinements that yield measurable gains over time.

Yes, iterative improvement cycles support resume and status features for long-running targets. The system tracks iteration counts and preserves iteration history, allowing you to pause and resume refinement workflows as needed.

Human-in-the-loop review is integrated directly between automated iteration cycles to ensure quality control. You can review the output of each algorithm pass before the system proceeds to the next refinement iteration.

Iterative improvement loops are needed when refining documents, code, or configurations where single-pass processing is insufficient. They are suitable for workflows requiring progressive refinements to achieve measurable quality gains.

Losing history between passes happens when the iterative refinement process lacks proper iteration tracking. Enforcing a dedicated loop mode ensures iteration counts are maintained and complete iteration history is preserved across all algorithm passes.