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UPDATEGitHub2026-03-31

GitHub Copilot Now Creates Issues Directly from Slack Using Natural Language

Key Takeaways

  • ▸GitHub Copilot can now create structured GitHub Issues from natural language descriptions in Slack conversations
  • ▸The integration supports sub-issues with proper parent-child hierarchy, enabling teams to break down work in a single message
  • ▸Teams can iterate on issue details in Slack threads and set channel-level default repositories for automated issue creation
Source:
Hacker Newshttps://github.blog/changelog/2026-03-30-create-issues-from-slack-with-copilot/↗

Summary

GitHub has expanded its Copilot integration with Slack, enabling users to create GitHub Issues directly from Slack conversations using natural language. By mentioning @GitHub in any Slack channel and describing the work needed, the app automatically generates structured issues complete with titles, descriptions, assignees, labels, and milestones. The feature also supports creating hierarchical sub-issues from a single message, allowing teams to break down work without leaving their chat context.

The integration leverages GitHub Copilot's coding agent capabilities to streamline workflow management. Teams can now iterate on issue details within a Slack thread before final creation, and view created issues through an issue flex pane directly in Slack. Channel administrators can set default repositories using @GitHub settings, ensuring consistency across teams. The feature is available to all GitHub Copilot plan subscribers and requires the latest version of the GitHub app for Slack.

  • Feature is available across all Copilot plans and integrates seamlessly into existing team workflows where work is already being discussed

Editorial Opinion

This update meaningfully reduces friction in issue tracking workflows by bringing issue creation into the context where teams naturally discuss work. By eliminating the context-switch of leaving Slack to create issues manually, GitHub is making project management more fluid and collaborative. However, the success of this feature will depend on how accurately Copilot interprets natural language descriptions—ambiguous prompts could lead to poorly structured issues that require significant rework.

Natural Language Processing (NLP)AI AgentsPartnershipsProduct Launch

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