reflector

Abstract

Reflective governance for recursive AI workflows

Recursive AI-augmented software engineering introduces development systems in which autonomous agents operate inside iterative feedback loops, generating, evaluating, and refining software artifacts at machine speed. Without explicit governance boundaries, these systems are prone to recursive optimization drift, complexity collapse, and misalignment with human-defined objectives.

Reflector defines four core mechanisms: scoped autonomous agents with bounded execution contexts, human-in-the-loop alignment checkpoints, recursive auditing systems, and milestone synchronization protocols that gate autonomous progression.