How to prepare a legacy codebase for an LLM feature
Use a reliability baseline and a focused architecture review to reduce deployment risk without treating an unverified Fragility Index as a product score.
News · Tomosu AI
One governance workflow for VS Code and Cursor
A shared policy starts with a common merge boundary, not an assumption that two IDE plugins behave identically.
MCP server or CI plugin? Where AI code governance checks belong
MCP can bring governance checks into an AI development workflow; CI remains the dependable merge boundary. Teams should decide what must happen in each place.
GPU scale puts production governance in the critical path
For enterprise AI deployments, reliability controls need to reach from code review into runtime operations; GPU capacity alone does not make systems safe to ship.
Turning Sentry runtime alerts into auto-updating IDE guardrails
Stop repeating AI code errors by converting Sentry runtime telemetry into active local guardrails in VS Code and Cursor.
Building an automated escalation pipeline with Datadog and PagerDuty
Connect Datadog SLO alerts, PagerDuty schedules, and Tomosu AI to handle routine incidents and protect engineer focus.
AI code governance digest: Benchmarking post-merge stability
Engineering leads face rising post-QA failures as synthetic code hits production, making standardized governance metrics essential for mainlining quality.
How to automate L1 and L2 incident resolution with runtime telemetry
Connect Sentry and Datadog signals to Tomosu AI to resolve tier-one and tier-two production incidents without paging senior engineers.
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.
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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