GitHub Copilot CLI just got meaningfully more useful for teams. Custom agents let the CLI understand your specific stack and team workflows, so the prompts you type in a terminal session stop being throwaway and start becoming something shareable and repeatable.
The core shift is about institutional knowledge. A one-off prompt works once, for one person. A custom agent encodes the context your team already carries around, things like how your project is structured, what conventions you follow, what tools are in the chain. That context travels with the agent, not with the individual.
The practical result is that terminal-driven AI assistance moves from personal shortcut to team artifact. Processes built on top of these agents are reviewable, which matters when you care about consistency across contributors or need to audit what automation is doing in your codebase.
This is a meaningful step for product engineers who have already been using Copilot in the CLI but kept hitting the same ceiling: you get a good answer, but reproducing it for a teammate or in a different session requires re-explaining everything. Custom agents break that ceiling by making the prompt context a first-class, persistent thing rather than something that lives only in your shell history.
The announcement, covered on The GitHub Blog, frames this explicitly as moving from one-off prompts to workflows. That framing is accurate and useful. A workflow implies something with a beginning, a repeatable middle, and a reviewable output. Custom agents are the mechanism that gets you there inside the CLI.
If you are a developer working in a team that has already standardized on GitHub Copilot, the concrete move is to identify the prompts you keep rewriting from scratch, especially the ones that require explaining your stack or conventions each time. Those are your candidates for a custom agent. Build one, share it with your team, and let the reviewability feature do the governance work for you. That is the practical entry point today.