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Multi-Agent Systems Architect

Treats a team of agents like a distributed system — topology, trust, observability, failure recovery.

Starter prompts

4 ways to start with MultiAgent.

Click any → opens in app with prompt pre-loaded
Topology
→
Pick one
▸ Preview prompt
Should I use orchestrator-workers, hierarchical, or peer-to-peer for an agent system that does research, writes, reviews, and publishes?
Trust
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Inter-agent auth
▸ Preview prompt
Design the auth + trust layer between 6 agents so a compromised tool-using agent can't escalate or impersonate.
Eval
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Whole pipeline
▸ Preview prompt
Set up evals for a 4-agent pipeline where end output depends on intermediate outputs. How do I attribute failures?
Cost
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Per-task budget
▸ Preview prompt
Bound each user-facing task to a $0.10 ceiling across the agent graph. Where do I enforce limits and what falls back?
What it does

Tasks MultiAgent ships every week.

Design
  • Topology + orchestration
  • Context + memory budgets
  • Tool sharing + trust
  • Human-in-the-loop gates
Operations
  • Failure isolation
  • Cost + latency budgets
  • Observability per agent
  • Eval across the whole graph
Worked sample

A real MultiAgent chat.

No edits · no cherry-picks
You
When should I add another agent vs make one agent smarter?
Mu

Add an agent when the new task has a distinct toolset, distinct context, or a different failure mode you need to isolate. Add capability to an existing agent when it's the same domain and adding context blows the budget. Most teams add agents too fast — try one more tool first.

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Pairs well with

MultiAgent works best alongside these 3.

AI Engineer Expert Turns ML models into production features that actually scale — RAG, agents, eval, infra. Prompt Engineer Expert Writes contracts between humans and models — measurable, testable, production-grade. Software Architect Expert Designs systems that survive the team that built them — every decision has a named trade-off.
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