Connect Codegen to your Slack workspace to enable seamless communication between agents and your team.
Slack is the most fluid way to communicate with Codegen. Simply tag @codegen in any channel to collaborate directly and give it tasks that leverage all your other integrations. As an agent, Codegen can seamlessly work across platforms—from GitHub to Linear to your databases—all initiated from Slack. We recommend Slack as the lowest barrier entry point for all users.
The Slack integration enables seamless collaboration with Codegen directly within your workspace:
Chat with Codegen directly in channels - Interact naturally through @mentions and direct messages
Get real-time notifications - Stay updated on task progress and completion
Share code snippets and updates - Collaborate on code changes and development tasks
Collaborate on development tasks - Coordinate work across your entire development workflow
All of these capabilities are accessible through natural language interactions in your Slack workspace, allowing your team to leverage Codegen’s assistance without context switching between different platforms.
After installing the integration from the Slack Marketplace, configure the bot by inviting it to relevant channels and setting up triggers so Codegen knows when and how to respond.
Invite the Codegen bot: Type /invite @codegen in any channel where you want Codegen to participate.
(Optional) Create a dedicated channel: Some Codegen users find creating a channel like #codegen helpful for general agent interactions and to encourage experimentation.
View workspace members and email addresses (users:read.email) - Used to map Slack user accounts to Codegen accounts for proper authentication and permission management. This ensures that when a user interacts with Codegen via Slack, their actions are properly attributed to their Codegen account and repository permissions
Access shared files and attachments - To review and work with shared content like code snippets, images, and documents
Access basic channel information - To operate appropriately within different channel contexts
Third-Party LLM APIs: To provide its core functionality, Codegen shares message content with third-party Large Language Model (LLM) APIs, specifically OpenAI and Anthropic.
Data Retention: Outside of the LLM API interactions, message content is retained by Codegen solely for the purpose of displaying it within the Codegen user interface.
Metadata from Private Channels: When messages from private Slack channels are processed, Codegen does not expose private metadata, such as the original author’s name or username, in the Codegen web app. Private channel names are anonymized and displayed as “Private channel” to non-members.
User Permissions and Access Control:
Codegen’s actions on connected repositories are governed by the permissions of the user who initiated the interaction via Slack. The bot itself does not have independent permissions to repositories. Access to repositories and the ability to trigger actions are determined by the Codegen user’s authenticated account and their associated repository permissions. We recommend configuring channel access carefully during installation to ensure the Codegen integration for Slack is only present in channels where its use is appropriate.
Privacy Policy:
For complete details on how we collect, use, and protect your data, please review our Privacy Policy.
Codegen uses artificial intelligence to provide intelligent code assistance, automated development tasks, and natural language interactions. Our AI capabilities include:
Code Generation and Analysis: AI models analyze your codebase and generate appropriate code changes, bug fixes, and improvements
Natural Language Processing: AI interprets your requests in Slack and converts them into actionable development tasks
Context Understanding: AI maintains conversation context to provide relevant and coherent responses across interactions
AI Data Processing:
Message Analysis: Your Slack messages are processed by AI models to understand intent and generate appropriate responses
Code Context: When working with repositories, AI models analyze relevant code to provide accurate assistance
AI Limitations:
AI-generated code should be reviewed before deployment
Complex tasks may require human oversight and validation
AI responses are based on training data and may not always reflect the most current information
Codegen offers flexible pricing plans to accommodate teams of all sizes. The Slack integration is available across all plan tiers, with usage limits and features varying by plan.
For detailed pricing information and to choose the plan that best fits your team’s needs, visit our Pricing Page.