Context Engine

Converting code quality feedback into RL-based continuous improvement. Covers OTEL-instrumented churn metrics, 21-day survival rewards, vectorized RL policies via Stable Baselines3/Pufferlib, and canary deployment safeguards.

Independent technical assessment of OpenClaw 2026.3.7 context engine plugin claims, OOLONG benchmark methodology, and Lossless-Claw performance assertions with confidence-level annotations.

Systematic audit of ASI-Evolve's evolutionary search framework against Anthropic's 2026 agentic best practices. Proposes integration architecture mapping evolutionary components to Claude production patterns, hybrid RL+Evolution pipeline, and safety governance for self-improving systems.

OTEL-based observability framework translating code churn into RL reward signals. Covers telemetry model, Gymnasium-compatible RL environment, multi-agent policy learning, and deployment safety guardrails.