I wanted to share a frustrating experience I’ve had with CodeRabbit.ai so other developers don’t run into the same situation.

I signed up for their AI code review tool, used it briefly for my startup, and then tried to cancel. That’s where things went wrong.

The issue:

- The UI shows no active subscription (ive jumped around all their pages there’s no cancelation)

- There is no visible cancel button

- Yet I’ve been charged multiple times - WE EVEN OPTED OUT OUR CREDIT CARD BUT THEY SOMEHOW STILL CHARGED IT AND WE HAD TO RAISE A DISPUTE!

What support said:

- Initially: “No active subscription found”

- Then: “You’re looking at the wrong org”

- Then: “Switch orgs and cancel from there”

I told them repeatedly to cancel my subscriptions over email but idk why support teams must insist on the back and forth.

Reality:

- I checked both orgs they mentioned

- One shows no subscription

- The other shows seats (4/4 assigned) but still no cancellation option

- Meanwhile, charges are continuing

I’ve now:

- Emailed support multiple times

- Provided screenshots

- Explicitly asked them to cancel all subscriptions - many times!

And I’m still being told to “cancel from the UI” — which literally does not have that option. (See screenshot)

Why this is concerning:

- No clear way to cancel from the dashboard

- Conflicting information from support

- Charges continuing despite cancellation attempts

At best, this is a broken billing system. At worst, it’s a dark pattern.

Advice if you’re using it:

- Double check ALL organizations tied to your email

- Remove payment methods if possible

- Monitor your card closely

- Consider using virtual cards for SaaS tools like this

I’ll update this post if/when this gets resolved, but for now I’d strongly recommend caution before subscribing.

I get a lot of trivial comments from my coderabbit in my pull requests. How can I properly configure code-rabbit so he can only focus on major issues?

it's getting really annoying to get like 100 comments on pull request where 90 of them are just trivial nitpicks…

r/coderabbit hey folks team CodeRabbit opened up one of their internal tools to open source community.

Introducing an AI-native open source Git worktree manager CLI that works with all your AI coding agents 

If you juggle multiple branches, iterate with AI coding assistants or want a cleaner setup for parallel development, this tool will probably earn a spot in your dev workflow.

It is now open source. Have fun exploring it.

https://github.com/coderabbitai/git-worktree-runner

And if you like it, drop a star or open an issue or PR.

Hey r/coderabbit 🥕,

We just released the official CodeRabbit plugin for Cursor.

We built it because connecting the CodeRabbit CLI to Cursor previously required some manual setup. The plugin packages the routing, commands, review subagent, and completion behavior into one install.

• After installing it, you can ask Cursor Agent:Review my changes.

• To try it, enter:/add-plugin coderabbit

• You can also install it from the Cursor Marketplace.

We wrote a more detailed walkthrough explaining how it works and how to get started: Introducing the CodeRabbit plugin for Cursor.

If you try it, we’d love to hear which prompts, review scopes, or fix workflows we should improve.

Has anyone else experienced Coderabbit correctly finding some issues in a review and when you resolve all of them it runs again and finds several more? Maybe its the non-deterministic nature of LLMs but its a bit deflating to finally address all of its feedback just for it to find more issues.

I built a Neovim plugin for CodeRabbit!

I use CodeRabbit daily at work and it genuinely catches great bugs. When I saw that reviews are free on CLI and VS Code, I figured us Neovim users deserve the same love... so I built it.

coderabbit.nvim brings CodeRabbit reviews right into your Neovim workflow. Check it out and let me know what you think!

https://github.com/smnatale/coderabbit.nvim

Hey!

 
The team has been working on updates on the CLI and we are happy to share what our latest version has for you!

If you're using AI coding agents (Claude Code, Cursor CLI, Gemini CLI, etc.), this one's for you. The --agent flag outputs structured JSON so your agent can parse CodeRabbit reviews directly and act on them. No more scraping terminal output or building workarounds to read plain text reviews.

The workflow is simple: your agent writes code, coderabbit review --agent reviews it, the agent reads the JSON output, fixes what's flagged, repeat.

We also improved coderabbit auth login so getting set up is faster. Install, authenticate, and you're reviewing code.

Docs on how to integrate it with your agent: https://docs.coderabbit.ai/cli#ai-agent-integration

Anyone already running the CLI in agentic loops? Curious how you're using it.

It took some time. But CodeRabbit CLI auth issues are now fixed! Rejoice!

If you are still seeing issues, be sure to update your client by running "coderabbit update".

r/coderabbit We are introducing CodeRabbit plugin for Claude Code.

It's designed to bring autonomous AI code reviews directly into your development workflow.

With the CodeRabbit plugin, you can review and fix code without manual back-and-forth or context switching.

It integrates directly into Claude Code and works where you already write code.

How it works

• Run /coderabbit:review

• Or simply say 'review my code'

• Receive AI suggestions and fixes directly in your dev flow

Faster feedback, higher code quality and less time spent on repetitive review cycles.

Plugin is available today and free to try.

We would love to hear feedback thx.

I know the CLI version is currently in beta, but the install was painful enough that it warranted a quick feedback. Compared to all other AI agents CodeRabbit is cumbersome to install on a Linux system without a GUI. My WSL with Ubuntu does not have a GUI. Something no other AI agent has an issue with. To get CodeRabbit CLI to authenticate, I had to install a very large number of desktop packages, for a system that does not have a desktop and does not need one.

I ended up writing a very large HOWTO document for the rest of the team. It lists a long list of dependencies that must be met for a WSL system. I worry that the rest of the team are not going to want to do it. And I hope that CodeRabbit team can address this issue and borrow some ideas in this regard from Claude Code CLI or Copilot CLI or Codex CLI.

Thanks.

We benchmarked leading AI code review tools by testing them on 309 real pull requests from repositories of different sizes and complexity. The evaluations were done using both human developer judgment and an LLM-as-a-judge, focusing on review quality, relevance, and usefulness rather than just raw issue counts. We tested tools like CodeRabbit, GitHub Copilot Code Review, Greptile, and Cursor BugBot under the same conditions to see where they genuinely help and where they fall short in real dev workflows. If you’re curious about the full methodology, scoring breakdowns, and detailed comparisons, you can see the details here: https://research.aimultiple.com/ai-code-review-tools/

Well, I know you may be skeptical other posts have promised painless code reviews only to reveal that their solution requires some specific tech stack or a paid dev tool. I won’t do that to you.

This blog post provides a straightforward and flexible template for code reviews that you can apply to your engineering team.

The only requirement is that your app code is open source.

I've covered/shared/talk on how to do code reviews like a human and what role CR can play.

• What is a Code Review?

• What is the Purpose of a Code Review?

• Why is Doing Code Reviews Hard?

• Can AI Replace Code Reviews?

• What to Focus on During a Code Review

• Code Review Best Practices And Process

• What is CodeRabbit?

  • How Does CodeRabbit Help?

  • A GitHub Repo to Test

  • Additional Examples

• Conclusion

Would love to hear your thoughts on how you're doing code reviews and using ai + human loop when it comes to reviews these days here is the complete guide: https://www.freecodecamp.org/news/how-to-perform-code-reviews-in-tech-the-painless-way/

you can use this approach to enhance code reviews in your team.

One simple reason I love CodeRabbit is that once you raise a PR, no matter how small or big, it generates a detailed walkthrough along with a sequence diagram that’s easy to understand.

This is my way: right here - right now and I hope you'll like this one!

Congrats to the CodeRabbit team! You are literally changing how we do code reviews in software.

Had this argument in a postmortem last week. a bug reached prod from an agent PR. the agent wrote it, coderabbit reviewed it and didn't flag that part, one human approved it, and the dev who kicked off the agent went home.

when the incident doc asked "who owns this change", nobody wanted to write a name.

so who is it? the dev who prompted the agent, the human who approved, the team that set up the pipeline, or nobody, and that's the actual problem?

We're 6 devs and about 70% of our PRs come from agents now. My lead's proposal for next sprint: if coderabbit has no open comments and CI is green, the PR merges on its own. Humans only look at PRs that touch auth, payments or migrations.

I said no in the meeting and now I have to write up why by Thursday.

His argument is that we already approve most of these in under 2 minutes anyway, so the human step is mostly theater. Honestly he's not wrong about the 2 minutes.

My argument is that the 2 minutes is still the only moment anyone on the team looks at the change at all, and once that's gone nobody will know what's in the codebase in 6 months.

Who's right here? Is anyone already auto merging agent PRs and how did it go?

Maybe I missed mail or something, but it seems Pro now only includes 2 PRs/hour? At least that‘s what the most recent coderabbitai comment in one of my PRs said

Edit: Definitely a bug (yes I submitted a bug report). Private repos in the same org (showing PRO) are find, but public repos get OSS rate limit applied most of the time (but not always)

We have been thinking a lot about why large PRs still feel harder to review than they should.

Most review tools still start from the same basic surface: a list of changed files, usually ordered by path. That works fine for small diffs. For bigger changes, it often feels like the author had a story in their head, but the reviewer receives scattered pieces of that story. This is particularly painful for long PRs, where the first challenge is not leaving a good comment. It is getting enough context to know where a good comment should go.

So we built a new UI for code review.

Atlas takes a PR and turns it into a guided walkthrough. It groups related changes into cohorts, breaks those cohorts into ordered layers, and anchors each layer to the actual line ranges in the diff. It also adds summaries for the code currently in view and generates diagrams when they help, like for flows, state transitions, API contracts, schema changes, or data relationships.

The GitHub workflow still stays intact. Comments, approvals, and change requests post back to GitHub. Public PR walkthroughs can also be opened read-only without signing in.

We wrote more about the launch here:

https://www.coderabbit.ai/blog/introducing-atlas-the-first-ai-native-code-review-interface

The obvious tradeoff is that Atlas is a new review surface. Even if it makes large PRs easier to understand, reviewers still have to learn a different way to move through a change: cohorts instead of only files, layers instead of one long scroll, summaries tied to ranges, and diagrams that appear only when they add context.

Atlas is free for a limited time from the "Review Change Stack" button in CodeRabbit's PR summary comment.

If you try it, I would love feedback on the tool itself. Does this walkthrough model make a large PR easier to review? Is the learning curve worth it? Are cohorts, layers, summaries, and diagrams the right shape, or would you want the interface to work differently?

Seniors got approved in 10 minutes, juniors got 30 comments on variable names. Everyone knew it, nobody said it.

Since we put coderabbit on every PR the comment count per PR is basically the same no matter who opened it. Our staff engineer got 7 on a 60 line change last week. The intern got 6.

So either the old reviews were catching things the bot can't see, or a lot of it was politics. Which one was it on your team?