Tutorials ASP.NET Core with Agentic AI 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 ASP.NET Core with Agentic AI Tutorial on Toolliyo Academy.

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ASP.NET Core with Agentic AI Tutorial · Lesson 36 of 100

Multi-Agent Systems

AI basicsAgents

AI basics · 1 — Setup · ~6 min · Module 4: AI Agents and Multi-Agent Systems

What is this?

Multi-agent systems run several agents concurrently or hierarchically toward one goal. AgentNest analytics runs DataFetcherAgent, StatsAgent, and NarratorAgent under a supervisor.

Why should you care?

Complex hospital pathways combine triage, billing, and scheduling agents — one monolith agent hallucinates cross-domain rules.

See it live — copy this example

Paste into an ASP.NET Core 8+ / AgentNest project, then run with dotnet run (set your API keys in user-secrets).

// AgentNest.Agents/Supervisors/AnalyticsSupervisor.cs
public sealed class AnalyticsSupervisor(
    DataFetcherAgent fetcher, StatsAgent stats, NarratorAgent narrator)
{
    public async Task<DashboardBrief> ProduceAsync(Guid tenantId, DateOnly week, CancellationToken ct)
    {
        var rows = await fetcher.LoadWeeklyMetricsAsync(tenantId, week, ct);
        var figures = await stats.ComputeAsync(rows, ct);
        var text = await narrator.ExplainAsync(figures, ct);
        return new DashboardBrief(figures, text);
    }
}

What happened?

  • AnalyticsSupervisor sequences fetch, compute, narrate agents.
  • Each agent stays domain-focused; supervisor owns orchestration only.

Practice next

  1. build supervisor class per multi-agent feature.
  2. Avoid circular agent calls — enforce DAG in code review.
  3. Load-test parallel fetcher agents with throttled DB pool.
  4. Run fetcher and cache warmup agents in parallel.
  5. Add fallback narrator using template text if LLM fails.

Remember

Supervisors coordinate specialized AgentNest agents. Keep agent responsibilities single-domain. Prevent circular delegation in architecture reviews.

Weekly executive brief

CEO wants metrics plus narrative every Monday from AgentNest analytics.

Outcome: AnalyticsSupervisor pipeline delivers figures and GPT explanation reliably.

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 ASP.NET Core with Agentic AI.
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…
Mid Detailed
What are common mistakes teams make with LLMs when using ASP.NET Core with Agentic AI?
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 ASP.NET Core with Agentic AI 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 ASP.NET Core with Agentic AI 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…
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ASP.NET Core with Agentic AI Tutorial
Course syllabus

ASP.NET Core with Agentic AI Tutorial

Module 1: AI and Agentic AI Foundations
Module 2: ASP.NET Core AI Fundamentals
Module 3: Semantic Kernel
Module 4: AI Agents and Multi-Agent Systems
Module 5: RAG and Vector Databases
Module 6: AI Security and Observability
Module 7: Cloud-Native AI and DevOps
Module 8: AI SaaS and Enterprise Systems
Module 9: AI System Design and Architecture
Module 10: Enterprise AI Projects
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