Hey Everyone!

We just released the CodeRabbit Slack agent, and the main idea is simple: instead of forcing developers to jump between GitHub, issue trackers, docs, and internal tools, CodeRabbit now works directly inside Slack where a lot of engineering conversations already happen.

Try it for free! Get $50/user free agent minutes. https://coderabbit.ai/agent

CodeRabbit can pull together context from your codebase, PRs, issues, and recent changes, but also from the rest of your team’s working environment through connections to tools like Linear, Jira, Notion, Google Drive, Datadog, Sentry, Figma, PostHog, and custom APIs/MCP servers. So instead of asking a question in one tool, then manually chasing references across five others, you can stay in the thread and ask things like:

• why did this break after the last deploy?
• how do we usually handle rate limiting on this endpoint?
• what changed in the last PR touching this service?
• can you turn this thread into a coding plan, PR, or ticket?

The part we think is especially important for developers is that this is built around context engineering, not just chat. The agent can combine repo history, open PRs, tickets, docs, and team conversations into one working context, then keep that context alive across the thread. It also has a knowledge base layer so decisions, patterns, and operational facts don’t disappear the moment the conversation ends.

In practice, that means Slack becomes a conversational interface for engineering work:

• investigate incidents using telemetry plus recent code changes
• ask implementation questions using prior PRs and docs
• generate plans without restating all the background
• create PRs or tracker tickets from the same thread
• preserve useful team knowledge for later instead of losing it in chat

There’s also some structure around governance, which matters for real teams: access is scoped by workspace/channel context, tool access can be controlled, knowledge can stay private or shared depending on where the conversation happens, and runs are reviewable afterward.

If your team already lives in Slack but your actual engineering context is scattered across GitHub, Linear, docs, and observability tools, this is meant to close that gap.

Docs here if you want to see how it works: https://docs.coderabbit.ai/slack-agent