Automating pull request gating with CodeRabbit and Tomosu AI
Pair diff-level code reviews with reliability scoring to block fragile changes before they hit production environments.
News · Tomosu AI
AI code risk tools: Static analyzers, PR bots, or governance layers
A practitioner breakdown of static linters, automated PR reviewers, and full-lifecycle governance platforms for machine-generated code.
AI code governance monthly digest: Closing the loop from runtime to IDE
A look at how engineering teams are shifting from post-merge observability to closed-loop reliability checks across the development lifecycle.
How to build an evidence trail for AI code changes before pre-merge
A step-by-step guide to installing local editor guardrails, scoring code changes with the Production Reliability Index, and generating audit-ready merge trails.
Building a reliable media stack with Cursor, Tomosu AI, and Sentry
A practical guide to connecting local editor checks, pre-merge pull request gating, and runtime observability into a continuous feedback loop.
How to catch fragile database code before pre-merge review
Learn how to install Tomosu AI in your editor, score pull requests with the Production Reliability Index, and fix unbounded queries before merge.
AI code governance digest: Shifts in IDE checks and pre-merge gating
A monthly look at how AI code governance tooling is moving upstream into editors, adopting score-based gates, and connecting runtime telemetry.
Evaluating options for AI code governance across the SDLC
Engineering teams face distinct tradeoffs when pairing static linters, test suites, or full-loop AI governance layers against generated code.
How to gate AI-generated code with production reliability scoring
A step-by-step guide to configuring editor plugins, pull request gates, and runtime learning loops with Tomosu AI.
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