Tutorials Prompt Engineering Tutorial

Multi-Agent Systems — Complete Guide

Multi-Agent Systems — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of Prompt Engineering Tutorial on Toolliyo Academy.

8 min read Updated 8/20/2026

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Prompt Engineering Tutorial · Lesson 53 of 100

Multi-Agent Systems

Prompts ✓ → Apps

Apps · 2 — RAG & agents · ~10 min · Module 6: AI Agents

What is this?

Multi-agent systems split work: planner agent, researcher agent, writer agent — coordinated by orchestrator or message bus.

Why should you care?

PromptVerse Research pipeline uses Researcher (RAG) + Writer + FactChecker agents sequentially.

See it live — copy this example

Copy the prompt into ChatGPT, Claude, or your LLM API playground and compare outputs.

orchestrator.dispatch("research", query)
  → researcher returns bullet notes + source_ids
  → writer drafts report from notes only
  → factchecker flags uncited sentences
  → orchestrator returns revised draft or escalate

What happened?

Researcher cannot write prose — only notes.
Writer sees notes not raw web.
FactChecker enforces citations before delivery.

Practice next

Define 3 agents with narrow roles.
Pass JSON handoffs between them.
Forbid writer from calling search.
Parallel researcher agents on sub-queries.
FactChecker as mandatory final gate.

Remember

Specialize agents. Structured handoffs. Orchestrator owns flow.

Analyst report

Weekly competitive brief.

Outcome: Three-agent pipeline delivers cited memo.

Interview prep for this lesson

Practice these questions aloud after reading—each links to a full structured answer.

Junior Detailed

Explain Concepts in the context of Prompt Engineering.

Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Concepts…

What are common mistakes teams make with LLMs when using Prompt Engineering?

Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define LLMs in p…

Senior Detailed

How would you debug a production issue related to RAG in a Prompt Engineering application?

Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define RAG in pl…

Junior Detailed

Describe a real-world scenario where Production mattered in a Prompt Engineering project.

Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Productio…

All course Q&A Practice exams

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