Tutorials ASP.NET Core with Agentic AI Tutorial

Autonomous Agents — Complete Guide

Autonomous Agents — 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 32 of 100

Autonomous Agents

AI basicsAgents

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

What is this?

Autonomous agents loop with minimal human input until a stop condition — max steps, goal met, or timeout. AgentNest limits autonomy on write actions; read-only CRM research can loop more freely.

Why should you care?

Fully autonomous ERP posting is liability; controlled autonomy for research drafts balances speed and control.

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/Autonomy/ResearchLoopAgent.cs
public sealed class ResearchLoopAgent(IChatClient chat, CrmPlugin crm)
{
    public async Task<ResearchReport> RunAsync(Guid accountId, CancellationToken ct)
    {
        var report = new ResearchReport();
        for (var step = 0; step < 5; step++)
        {
            var facts = await crm.FetchLatestNewsAsync(accountId, ct);
            report.Notes.Add(facts);
            if (facts.Contains("ENOUGH")) break;
        }
        report.Summary = (await chat.GetResponseAsync([report.Notes.Last()], cancellationToken: ct)).Text;
        return report;
    }
}

What happened?

  • ResearchLoopAgent caps at five iterations and breaks on ENOUGH marker.
  • Write tools are absent — autonomy is read-only.

Practice next

  1. Define MaxSteps constant per agent class.
  2. Use CancelAfter for wall-clock limits.
  3. Block autonomous loops on POST/PUT kernel functions.
  4. Surface remaining steps to the UI progress bar.
  5. Replace fixed polling with event-driven CRM webhooks.

Remember

Cap steps and time on autonomous AgentNest loops. Restrict autonomy to read-only tools by default. Pair write autonomy with human approval workflows.

Account research bot

SDRs want overnight CRM news gathering before QBRs.

Outcome: ResearchLoopAgent runs read-only within five steps; summaries wait for rep review.

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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