Greg Isenberg and Vince Canger describe Buzz as a chat workspace that treats AI agents as first-class team members. Conversations, decisions and project history remain in a shared context layer, while the harness underneath an agent can switch among coding tools without discarding that history.
Vince Canger demonstrates how agents can work in separate Git worktrees, create repositories on a self-hosted relay, deploy an application and return links or screenshots to the channel. A project can also expose data through an API so an agent continuously brings operational results back into the same discussion where the team decides what to do next.
Greg Isenberg focuses on the interface as a way to reduce the gap between discussion and execution. Team members can identify a feature or problem in a channel, ask an agent to prototype it and review the result without manually moving context among chat, coding and deployment tools.
The current software is still early. Vince Canger reports that some recurring workflows are unreliable and that remote relay communication can feel slower than direct command-line work. The strongest near-term fit is therefore a small team that values shared context, open protocols and flexible model choice more than mature enterprise controls.
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