The short answer: use Duo Loop for a focused change, Agent Swarm when you want tests, code and review in the background, and Orchestrator when a goal is too big for one agent and should be split into parallel tasks.
What is a multi-agent coding workflow?
It is a setup where several AI coding agents work on the same goal with different roles, and at least one of them checks another’s work before the result reaches you. The point is not speed alone: it is that a second agent — and your tests — catch mistakes a single agent would ship.
Duo Loop — two agents, side by side
Best for: one feature or bug fix you want to watch.
Two real terminals open next to each other. The checker writes tests from your goal; the writer codes until they pass; then the checker reviews the diff and either approves it or sends feedback. The loop repeats up to the number of rounds you set.
Choose it when you want to see every step and step in if needed. Read the Duo Loop docs.
Agent Swarm — three roles in the background
Best for: a well-defined task you want done without babysitting.
Three roles run in the background, optionally inside an isolated Git worktree so your working tree stays untouched:
- a verifier writes the tests,
- a builder codes until they pass,
- an auditor reviews the diff.
orchestrate mesh "Add a JWT refresh token to user login" \
--builder claude --verifier agy --auditor claude \
--verify-cmd "npm test" --max-rounds 3Orchestrator — split a big goal across parallel workers
Best for: migrations, refactors and features that touch many parts of a codebase.
A planner splits the goal into a task graph. Workers run each task in parallel, each in its own worktree with its own tests. The pieces are merged, tested together, and a reviewer approves the result before it is applied to your working tree or opened as a pull request.
orchestrate orchestra "Move the REST API endpoints to a GraphQL schema" \
--planner claude --workers claude,agy,codex --reviewer claude \
--parallel 3 --max-rounds 2Quick comparison
| Duo Loop | Agent Swarm | Orchestrator | |
|---|---|---|---|
| Agents | 2 | 3 roles | planner + N workers + reviewer |
| Runs | in view, side by side | in the background | in parallel |
| Isolation | your working tree | optional Git worktree | one worktree per task |
| Best for | a focused change | a defined task, hands-off | a large goal |
And team chat?
If you would rather talk than configure, Vulgr’s team chat does a lighter version of the same thing: mention two or more agents in one message and they discuss it, the result is verified with your local tests, and you get one synthesis. See Team chat.