GitHub Copilot introduces hooks for AI agent workflow governance

GitHub Copilot and Copilot Studio have introduced new capabilities for managing AI agent workflows. A new feature called ‘hooks’ has entered preview, allowing developers to implement governance and control mechanisms within the GitHub Copilot harness.

Unlike standard tools that an agent calls only when it deems them relevant, hooks are designed to trigger at specific points in an agent’s lifecycle. This allows for mandatory workflows that can modify prompts, provide additional context, or even deny tool calls. The six available event types include Start, User prompt submitted, Error, Pre tool use, and Post tool use.

Technical analysis of how Copilot generates dynamic workflows reveals a process involving a handshake between the native CLI runtime and the Copilot SDK. While the system can register executable multi-agent workflows from plain-English prompts, research into the runtime highlights a distinction between maintaining a log of actions and having a durable workflow capable of resuming after a process interruption.