# Agentic-AI

LangChain shares how they built an eval system for Deep Agents: not by piling on more tests, but by using targeted evals that measure exactly what matters in production. From data sources to metrics design to actually running evals — the full methodology.

Meta engineer Summer Yue let OpenClaw manage her inbox until context compaction dropped the wait-for-approval rule and triggered mass deletion. The lesson: safety constraints cannot live in chat history; they need infrastructure like proxy filter chains.

Anthropic ships Claude Code auto mode, a model-based classifier between manual approvals and skip-all-permissions. The post explains its architecture, threat model, two-stage classifier, and the honest 17% false negative rate.