Comparison
Multi-Agent vs Plan-and-Execute
Multi-Agent and Plan-and-Execute are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Multi-Agent
Multi-Agent comes up when the question is fundamentally about agents & tools.
A planner agent + executor agents in Claude Code.
When you would reach for Plan-and-Execute
Tasks where the high-level structure is predictable but individual steps need autonomy.
A research agent: Sonnet produces a 7-step plan; Haiku executes each step; if step 4 fails, Sonnet re-plans from there.
Frequently asked
What is the difference between Multi-Agent and Plan-and-Execute?
Multi-Agent: A multi-agent system uses several LLM agents that talk to each other — a manager and workers, a debate, a pipeline — instead of a single agent doing everything. Plan-and-Execute: Plan-and-execute splits agent loops into a planning step (produce the full step list up front) and an execution step (run each step). Cheaper than per-step ReAct and easier to inspect.
When should I use Multi-Agent vs Plan-and-Execute?
Multi-Agent is the right concept when you are focused on agents & tools. Tasks where the high-level structure is predictable but individual steps need autonomy.
Are Multi-Agent and Plan-and-Execute the same thing?
No. Multi-Agent is agents & tools; Plan-and-Execute is agents & tools. They are related but address different parts of the AI stack.