CodeRabbit helps teams review, understand, govern, and trust agent-generated code: coderabbit.ai!
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Agents can create PRs in minutes, but understanding them still takes work.
CodeRabbit Change Stack connects a PR's purpose, behavior, dependencies, and code so reviewers can really verify it before approving.
Do you understand what you're about to merge?
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Writing code is turning into the cheap part. Knowing which code should exist, which shouldn't, and why is where the value's heading, and Jev is the latest case of AI making those decisions instead of just producing output.
You still have to think like a programmer.
Just a few layers above the code!
Yesterday @coderabbitai didn't just host a hackathon, it was a Jevathon!
Tired of having to think like a robot? Our favorite hacker review was: "Think like a programmer again" with @allietheicon
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CodeRabbit retweeted
Our interns @xrhuang10, @_nikhilhooda and Utkarsh helped me organize this entire event, managing ppl, answering q's while somehow finding the time to hack themselves.
And then... independent judges picked them for 1st place 🏆
Couldn’t be more deserved. Absolute rockstars🤘👏🧡
1/ Yesterday we hosted @typesafeai at our @coderabbitai HQ for Jev's first ever hackathon!
160+ builders. ~4hrs of hacking. Expert judges, Incredible energy.
I also got to sit down with @allietheicon and talk about what Jev means for Coding, Software Development and the new paradigm shift you have to adapt when working with this new class of AI models.
She shared some really helpful tips and examples of how to best work with Jev - I'll try my best to summarize some of them in this thread⬇️
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CodeRabbit retweeted
1/ Yesterday we hosted @typesafeai at our @coderabbitai HQ for Jev's first ever hackathon!
160+ builders. ~4hrs of hacking. Expert judges, Incredible energy.
I also got to sit down with @allietheicon and talk about what Jev means for Coding, Software Development and the new paradigm shift you have to adapt when working with this new class of AI models.
She shared some really helpful tips and examples of how to best work with Jev - I'll try my best to summarize some of them in this thread⬇️
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Google Cloud wrote about how CodeRabbit is moving from AI code review into Agentic Change Management, and what we're building on Cloud Run, Cloud Storage and Gemini to get there.
Read the article here: cloud.google.com/blog/topics…
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Your agent worked all night. Do you merge what it wrote?
Francesco Bonacci (@francedot) of Cua (@trycua) wants his agents shipping while he sleeps, without waking up to a mess he has to clean up. The hard part is staying close enough to steer them.
On this episode of The Merge we get into how he closes the loop on agent tasks, what to do with low-quality AI-generated PRs, and why a proposed patch isn't a merge.
His take: more autonomy means review matters more, not less. You still need to be able to inspect the result and push back on it.
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This week in the CodeRabbit changelog 🐰
→ Share TypeScript review configs across repos
→ Handle metrics API retries with clearer retry guidance
Define review standards once. Reuse them across your team’s repositories.
See the full changelog: docs.coderabbit.ai/changelog
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TypeScript config docs: docs.coderabbit.ai/configura…
MCP Metrics docs:
docs.coderabbit.ai/api-refer…
Review Comment Metrics dovs:
docs.coderabbit.ai/api-refer…
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CodeRabbit is available in Claude Marketplace!
Apply a portion of your committed Anthropic spend to CodeRabbit, the same route we used for Vercel Sandbox and Workflows!
Read Anthropic's announcement:
claude.com/blog/how-coderabb…
You can now discover tools, agents and expert partners on Claude Marketplace. Use it to:
- Add connectors and plugins like Slack and Notion
- Buy agents and products from companies like Cursor and CrowdStrike
- Scale with service partners like Accenture and Deloitte
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Agents can create PRs in minutes, but understanding them still takes work.
CodeRabbit Change Stack connects a PR's purpose, behavior, dependencies, and code so reviewers can really verify it before approving.
Do you understand what you're about to merge?
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Beyond the benchmarks, what was Opus 5.5 like to work with?
Hendrik and Gowtham discuss an overnight coding run, the token tradeoffs, and why higher reasoning effort didn’t consistently catch more bugs.
We ran Opus 5.5 through CodeRabbit's review pipeline.
> On 80 known bug patterns it caught 51 vs 49 for our production mix.
> On 13 harder cases, 10 vs 5.
> It found a retry-count race in Cal.com that production missed.
The catch is ~50% more tokens, and 9 bugs our baseline caught that Opus 5.5 didn't.
Read our full Opus 5.5 model evaluation here: coderabbit.ai/blog/opus-5-5-…
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We ran Opus 5.5 through CodeRabbit's review pipeline.
> On 80 known bug patterns it caught 51 vs 49 for our production mix.
> On 13 harder cases, 10 vs 5.
> It found a retry-count race in Cal.com that production missed.
The catch is ~50% more tokens, and 9 bugs our baseline caught that Opus 5.5 didn't.
Read our full Opus 5.5 model evaluation here: coderabbit.ai/blog/opus-5-5-…
Introducing Claude Opus 5.5, the first model in our new Claude 5.5 family.
It performs at the level of Claude Fable 5.1 for most tasks, and costs 40% less to run than Opus 5.
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CodeRabbit retweeted
POV of me preaching the Rabbit to a bunch of smart people... 🐰🤓
Last night was fun! Thank you so much @MelGoesTech & @temporalio for co-hosting and @nyghtowl, @bdougieYO, Chris Brox and @lizziepika for sharing the stage.
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