The GitHub Copilot desktop app orchestrating parallel AI agents changes what autonomous development looks like

A standalone native desktop client that orchestrates multiple AI agents in parallel using Git Worktrees for isolated sessions is a development environment that has no direct predecessor. Each agent working in its own isolated branch, running simultaneously on different parts of a codebase, with results mergeable when reviewed is production-quality parallel development automation.

The MCP integration allowing Copilot to securely interact with external enterprise tools like Jira and Datadog within the same workflow is the enterprise pipeline integration that makes the agent useful for real project management contexts rather than isolated coding tasks.

The ability for agents to spin up their own GitHub Actions for automated testing, pushing code and self-correcting based on test results is the closed-loop development cycle that changes the human role from writing code to reviewing and directing agents.

For teams already running Copilot extensively: has anyone started using the parallel agent features in production workflows and what has the quality of the merged output been like?