CodeRabbit
@coderabbitai

CodeRabbit helps teams review, understand, govern, and trust agent-generated code: coderabbit.ai!

 San Francisco, CA
coderabbit.ai
Joined April 2023
2,017 Photos and videos
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Do you understand what you’re about to merge?

Agents can create a pull request in minutes. The PR can span many files, combining a new API, a database migration, and tests in a single change. Reviewing it means understanding how those pieces work

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Rethinking PR triage from first principles

AI coding tools and agents make it faster to produce code and open pull requests. As those requests accumulate, teams have to decide which changes need attention first. That starts with understanding

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Software factories can automate much of the path from intent to production. The review gate needs to scale with them: fast paths for routine changes, deeper review where mistakes are expensive, and a clear view of what’s shipping.
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A software factory needs a review gate it can trust

Software factories can turn intent into tested code with very little human intervention. Agents pick up queued work, write and test the implementation, respond to findings, and prepare it for release.

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The three hidden attention taxes derailing the agentic SDLC

Reviewing every change an agent generates is becoming impossible. Long-running agents produce larger and more frequent pull requests, and any tool, workflow, or person can now open a PR with almost no

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Article

Your AI Agent Has Amnesia

> Schedule disasters and system bugs arise because the left hand doesn't know what the right hand is doing – Fred Brooks in The Mythical Man-Month describing the IBM OS/360 Project’s coordination
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An (actually useful) framework for evaluating AI code review tools

Benchmarks promise clarity. They’re supposed to reduce a complex system to a score, compare competitors side by side, and let the numbers speak for themselves. But, in practice, they rarely do.
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