Tutorials ASP.NET Core with Agentic AI Tutorial

AI Planners — Complete Guide

AI Planners — 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 26 of 100

AI Planners

AI basicsAgents

AI basics · 1 — Setup · ~6 min · Module 3: Semantic Kernel

What is this?

Planners let Semantic Kernel decompose a goal into a sequence of function calls automatically. AgentNest uses function-calling planners for exploratory ERP analytics where steps are not hard-coded.

Why should you care?

Ad-hoc analyze-this-quarter questions need dynamic plans; fixed pipelines fail when users change intent.

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/Planning/ErpPlannerAgent.cs
public sealed class ErpPlannerAgent(Kernel kernel)
{
    public async Task<string> RunAsync(string goal, CancellationToken ct)
    {
        var planner = new FunctionCallingStepwisePlanner();
        var plan = planner.CreatePlan(kernel, goal);
        var result = await plan.InvokeAsync(kernel, cancellationToken: ct);
        return result.GetValue<string>() ?? "";
    }
}

What happened?

  • FunctionCallingStepwisePlanner asks the model which GlPlugin tools to call next until the goal is satisfied.
  • Follow the steps below — typing the code yourself is the fastest way to learn.

Practice next

  1. Register GlPlugin and AnalyticsPlugin on the kernel.
  2. Wrap planner calls with MaxIterations guard.
  3. Log each planned step to AgentNest audit.
  4. Require user confirmation after plan preview JSON.
  5. Swap planner model to cheaper deployment for planning only.

Remember

Planners dynamically sequence kernel functions. Use for flexible ERP and analytics questions. Cap iterations and audit every planned step.

CFO ad-hoc analysis

Finance lead asks natural-language questions during board prep.

Outcome: ErpPlannerAgent chains balance and variance tools without a fixed diagram.

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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