Insights on AI agent governance, risk analysis, and shipping faster — safely.
AI coding agents are shipping code faster than ever, but without governance, speed becomes a liability. Learn why every team using AI agents needs a risk analysis layer and how to build one.
A step-by-step guide to installing MergeShield, running your first risk analysis, understanding scores, and configuring auto-merge for your GitHub repositories.
How does MergeShield change your team's code review workflow? A practical comparison of automated risk analysis versus traditional manual review — and why the best approach combines both.
Anthropic's multi-agent harness uses a generator and evaluator to improve code quality. But when both agents share the same model, they share the same blind spots. External evaluation changes everything.
Anthropic accidentally leaked Claude Code's full source. The code itself matters less than the unreleased feature flags: autonomous daemons, multi-agent coordination, and a stealth mode that strips AI attribution. Here's what it means for governance.
Undercover Mode strips the three signals most teams rely on to detect AI-generated code. Here's what actually works when attribution is gone.
A Cursor agent wiped 37GB by bypassing OS security policies. The forensic breakdown reveals four failure points every team using AI agents needs to fix.
Follow us for updates on AI agent governance