We raised $143M to build the control layer for software change.Read more: We raised $143M to build the control layer for software change.
Agentic Learning Center
Code explainability for AI-generated PRs: A reviewer's guide
When an agent writes the PR, 'ask the author' stops being a reliable review tool. Use this practical workflow to review intent, blast radius, error paths, and evidence before merge.
What is Agentic Change Management?
Agentic Change Management is how teams validate, prioritize, explain, and monitor software changes when AI agents write code. Learn how it works.
AI security code review: Improve code security before merge
AI security code review helps teams inspect risky pull-request changes, explain code security findings, and improve security before merge.
How to build a Slack bot that reviews your code
Learn three practical ways to bring code review into Slack, from GitHub notifications to a custom Slack bot and CodeRabbit Agent for Slack.
What does an agentic SDLC actually look like end-to-end?
See what an agentic SDLC looks like across planning, code generation, review, testing, deployment, and operations.
Building a quality gate that works for AI-generated code
Learn how to build a credible quality gate for AI-generated code using independence, agnosticism, discernment, and explainability.
How to get AI code review alerts in Slack
Compare four ways to route AI code review alerts into Slack without turning review channels into noisy notification feeds.
How to keep AI code review consistent across coding agents
Learn how to keep one review standard across Codex, Claude Code, Cursor, other coding agents, and human-written pull requests.
Why explainability is the new observability layer for pull requests in the agentic SDLC
Learn why large agent-generated pull requests need explainability, not just file-by-file diffs, so reviewers can understand change intent before merge.