Chat

The chat interface is where you collaborate with your AI agent. Everyone in your workspace can participate in any implementation's chat, making it easy for your team to review progress, ask questions, and provide feedback.

Sending messages

Type your message and click the send button to send it to the agent. The agent will respond and continue working based on your input.

You can send messages even while the agent is still working. Your messages will be queued and picked up automatically when the agent finishes its current task.

Stopping the agent

If the agent is heading in the wrong direction or doing something you don't want, click the Stop button in the chat input area to halt its current work. You can then send a new message to redirect the agent.

Viewing the agent log

To see exactly what the agent did, expand the Show Work dropdown next to the agent's name in the chat. This shows a detailed log of the agent's work, including tool calls and intermediate steps.

Uploading files

Chat supports several ways to share files with your agent:

• Drag and drop files directly onto the chat area
• Paste images from your clipboard (Cmd/Ctrl+V)
• Click the attachment button to browse and select files

Supported file types include:

• Images: JPEG, PNG, GIF, WebP, BMP, HEIC, SVG, TIFF
• Videos: MP4, MOV, WebM, AVI, MPEG, WMV, FLV, 3GP
• Documents: PDF, Markdown, plain text
• Code files: JavaScript, TypeScript, Python, Ruby, Go, Rust, and many more
• Data files: JSON, YAML, CSV, XML

Images can be up to 10 MB, documents up to 25 MB, and videos up to 100 MB.

Tips for getting the most from your agent

Ask for artifacts

Request screenshots, diagrams, or other visual outputs to document progress. Agents can share these directly in chat without committing them to the repo. See Artifacts for more details.

Iterate from Slack and GitHub

Continue conversations from Slack by replying in the same thread, or from GitHub by commenting on PRs. Your feedback flows back to the agent automatically, and the agent will notify you once it's done.

Use MCP Playwright for in-app testing

If Playwright is enabled for your project, ask the agent to test code changes directly in the browser and take screenshots. This lets the agent verify UI changes work correctly without you having to run the app yourself.

Take advantage of Sentry integration

With Sentry MCP enabled, agents can directly query your Sentry account to understand what errors are happening in production. Agents can view actual production errors and their surrounding context, helping them write better fixes.

Comment on specific lines of code

When reviewing the diff, click the + on any line to add a comment. Your comment is pasted in the agent chat with full context about the code you're referencing, making it easy to request precise changes.