Describe how your agents divide the work and the AI draws the orchestration — supervisors, specialists, shared state, and every handoff between them
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Describe your agent and the AI draws the loop — model, tools, memory, guardrails, and the humans and systems it touches
Design full-stack LLM applications with routing, retrieval, tooling, and safety layers
Design event-driven systems with AI. Visualize event producers, message brokers, consumers, and asynchronous communication
Common questions about ai multi-agent architecture generator
Yes, and the topology is the decision: supervisor patterns render as a hub with specialists, swarms as peers over shared state, pipelines as staged flows with gates. Generating two candidate topologies and comparing them is the fastest way to settle a design debate.
Shared memory, message channels, and per-agent private context render as distinct components, which surfaces the classic multi-agent failure — two agents silently overwriting shared state — before it ships.
Approval gates, escalation queues, and review checkpoints are drawn on the exact edges where they apply, so the compliance conversation ("where can a human stop this?") has a concrete answer.
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