Do you really need multi-agent orchestration, or is one agent enough?
Almost every agent tool now ships a multi-agent mode: a planner splits the task and hands pieces to several workers running in parallel, sometimes a big cloud model planning for smaller local ones. It sounds good on paper, but does it actually beat a single agent working through the task, and when is it worth the extra setup?
For most tasks one agent is enough, and it is easier to follow. Every extra agent adds a handoff, and every handoff is a place where context gets lost: the worker only knows what the planner wrote down, and the planner only knows what the worker reported back.
Splitting pays off when the pieces are truly independent: several unrelated bugs, separate files, research questions that do not depend on each other. Then parallel workers save time and each one keeps a small, clean context. If the pieces share state or must happen in order, one agent working step by step usually finishes sooner and breaks less.
A useful middle ground is a single main agent that hands out narrow, well-specified subtasks and reviews what comes back. You keep one place that holds the whole picture, and the helpers stay short-lived and focused.
Whatever you choose, write the plan down first. A list of tasks with the files each one touches makes it obvious which parts can run in parallel and which cannot.
Listings mentioned
- Dispatching parallel agents · skill by obraSends two or more independent tasks to separate agents at once, and only when they share no state or ordering.
- Subagent driven development · skill by obraOne main session works through a written plan and hands each task to a fresh subagent, with a review between tasks.
- Multi agent coordinator · agent by VoltAgentWrites the coordination plan for several agents: who talks to whom, the order of work, shared files and what happens on failure.
Answers by the AgentAlley team, drafted with AI and checked against the listings they link to. Not a real-person reply from the original thread.