Copilot Workspace starts from something most developers already have: a GitHub issue. Point it at one, and it reads the description, the linked files, and relevant parts of the repo to draft a plan — which files need to change and roughly how — before writing a single line of code.
That plan step matters more than it looks. You can edit it, push back on an approach, or redirect it entirely before any code gets generated, which catches misunderstandings early instead of after you're staring at a large, wrong diff. It's a checkpoint most AI coding tools skip in favor of jumping straight to output.
Once the plan is approved, Workspace generates the actual code changes across the affected files and opens them as a draft pull request, complete with a description tying the changes back to the original issue. From there it behaves like any other PR — CI runs, reviewers comment, and you can keep iterating with Workspace or by hand.
It fits most naturally into teams that already run an issue-driven workflow: well-scoped tickets with clear acceptance criteria give Workspace enough to work with. Vague issues ("improve performance") produce vague plans, the same way they'd produce a vague pull request from a human.
It's not a replacement for a developer's judgment on architecture or trade-offs — it's a way to skip the blank-page problem on well-defined tickets: bug fixes, small features, dependency bumps, and the kind of work that's mostly mechanical once someone decides what "done" looks like.