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Production Multi-Agent System

Advanced

3–4 weeks · 6 milestones

Build a supervisor-worker multi-agent system where a coordinator agent delegates subtasks to specialist agents (researcher, coder, writer) with shared memory.

Difficulty

Advanced

Duration

3–4 weeks

Milestones

6 steps

Interview Qs

4 questions

🛠 Tech stack

PythonLangGraph or customClaude / OpenAI APIRedis (shared memory)FastAPINext.jsDocker

✅ Prerequisites

  • Built a basic agent
  • Advanced Python
  • System design basics

Step-by-step milestones

1

Design agent topology

Define supervisor, specialist agents, and communication protocol.

2

Implement supervisor

Router that decomposes tasks and delegates.

3

Implement specialist agents

Researcher, coder, writer with appropriate tools.

4

Shared memory layer

Use Redis for cross-agent state.

5

Human-in-the-loop

Add approval checkpoints for risky actions.

6

Monitoring + debugging

Visualize agent communication and task flow.

Skills you'll build

Multi-agentAgent orchestrationShared memoryTool useProduction deployment

📝 Interview questions you'll face

  • 1.How do you prevent agents from contradicting each other?
  • 2.How do you handle a specialist agent failing?
  • 3.How do you design agent communication protocols?
  • 4.What are the token cost implications of multi-agent systems?

🌟 Portfolio guidance

Build it for a real use case (e.g. AI research assistant, code review system). Diagram the agent topology and include a demo video.

📚 Learn the concepts first