Multi-agent systems split hard work across cooperating specialist agents.
DefinitionWhat it means
A multi-agent system decomposes a task across several specialized agents, for example a planner, a researcher, and a coder, that communicate through messages, shared memory, or a supervising orchestrator agent, rather than relying on one general-purpose agent to do everything.
Why it mattersWhy you should care
Splitting responsibilities improves reliability and lets each agent use a narrower, cheaper, or more specialized model, but it introduces new failure modes such as coordination overhead, conflicting sub-goals, and higher latency and cost, all of which product teams must weigh against a simpler single-agent design before adopting the pattern.
At a glanceSee it
Real multi-agent work is a verify-and-retry loop rather than a straight line — a checker bounces weak drafts back until they pass, and a retry cap escalates a stuck worker instead of looping forever.
Choosing a coordination topology is itself a decision — driven by whether subtasks are independent and whether answers need cross-checking before they ship.
Where you see itIn the wild
- Frameworks like AutoGen and CrewAI built specifically for agent teams.
- Production support and coding assistants that route sub-tasks to specialist agents.
- Design debates on when multi-agent design beats a single strong agent.
What changedWhat changed here
- Claude Code relaunches Projects to manage multiple AI agents in the cloud
Claude Code relaunched Projects, letting you run multiple agents under one roof with shared memory, goals, and a file/artifact library, coordinated by a 'coordinator' with parallel threads. That's a concrete shift in how you'd structure multi-agent coding work — shared context instead of isolated sessions — and worth testing before you build your own orchestration layer.
- Claude Code Gets Major Update: AI Sessions Can Now Communicate Autonomously, Marking a Key Step in Multi-Agent Collaboration
Claude Code now lets AI sessions communicate autonomously, a concrete step toward multi-agent collaboration for builders.
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