
GitHub has expanded its Copilot coding agent capabilities to Slack and Microsoft Teams, enabling the AI to ingest context from chat files, images, and message history. The update allows agents to create GitHub issues directly from conversations while maintaining traceability links back to the source discussion. Technical improvements include better handling of interrupted tasks, model switching within sessions, and more reliable reconnection behavior for long-running operations. The feature is currently in public preview for organizations on GitHub Copilot Business and Enterprise plans.
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© GitHub ChangelogGitHub Copilot now validates enterprise managed settings directly in the UI, catching malformed JSON and invalid team mappings before they break policy enforcement. This shifts validation from a silent failure mode to an explicit feedback loop, saving admins from debugging why their AI controls aren't applying. By pointing to specific files and JSON paths, it reduces the friction of managing .github-private repositories at scale. It’s a pragmatic fix for a common enterprise pain point rather than a new capability.
© GitHub ChangelogThis release stabilizes Claude Code by fixing a cascade of session-breaking errors that previously caused silent data loss or API drops. The most significant fix addresses resumed conversations re-sending messages in altered forms, which was corrupting reasoning traces and breaking extended thinking workflows. It also resolves persistent login refresh loops and managed setting parsing failures that plagued enterprise deployments. While the changelog is dense with UI tweaks like scrollbar fixes and vim mode corrections, the core value lies in restoring reliability for long-running agent sessions.
This release quietly solves a major pain point for enterprise AI workflows by adding gateway hint headers, allowing LLM gateways to correctly group requests per user prompt instead of treating them as isolated events. The new managed settings for availableModelsMatch and deniedModels give organizations precise control over model access, blocking specific versions even when broader allowances exist. Beyond governance, the update stabilizes the plugin ecosystem with rigorous validation checks that prevent silent failures from broken or misconfigured extensions. These changes shift Claude Code from a developer tool to a manageable enterprise component.
GitHub finally exposes the hidden latency in pull request workflows through its Copilot usage metrics API. By breaking down merge times into median and p90 durations for ready-to-first-review, first-to-final review, and final-to-merge stages, teams can pinpoint exactly where bottlenecks occur. This granular visibility distinguishes between waiting for initial attention versus lingering in approval queues, allowing for targeted process fixes rather than guessing. Since it ignores bot reviews, the data reflects genuine human collaboration speed, offering a clear signal on team efficiency.