Blog

AI agents write code fast, but who checks if the code does what it should? Acceptance criteria traceability creates a machine-verified chain from requirements to tests, closing the gap between what was specified and what was built.

Governance drift is the gap between what you told your AI agent to build and what it actually built. Learn how to detect and prevent it with drift scoring, session tracking, and automated PR checks.

AI-generated pull requests are larger, faster, and harder to review than human-written code. Learn the 5 critical checks and how automated governance can help your team keep up.

CLAUDE.md configures how Claude Code behaves in your project. Learn best practices for deny patterns, file budgets, lifecycle commands, and how to generate CLAUDE.md from governance state automatically.

Multiple AI coding agents working on the same codebase creates coordination challenges. Learn how session governance, drift detection, and feature traceability keep multi-agent development under control.

AI coding agents are powerful but unrestrained. Without scope limits, file budgets, and session accountability, they can rewrite your codebase, delete tests, and touch secrets. Here's how to add guardrails.

Step-by-step guide to setting up ExoProtocol governance checks on your GitHub pull requests. Catch ungoverned commits, drift, and scope violations automatically before merge.