Tutorials ASP.NET Core with Agentic AI Tutorial

Semantic Kernel Basics — Complete Guide

Semantic Kernel Basics — 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 21 of 100

Semantic Kernel Basics

AI basicsAgents

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

What is this?

Semantic Kernel (SK) is Microsoft's SDK for prompts, plugins, planners, and memory in .NET. AgentNest builds Kernel instances per tenant with allowed plugins for CRM, ERP, and hospital domains.

Why should you care?

SK unifies OpenAI and Azure OpenAI behind Kernel and KernelPlugin collections so teams stop rewriting orchestration for each feature.

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/KernelFactory.cs
public static Kernel Create(IChatClient chat, CrmPlugin crm)
{
    var builder = Kernel.CreateBuilder();
    builder.Services.AddSingleton(chat);
    builder.Plugins.AddFromObject(crm, pluginName: "crm");
    return builder.Build();
}

What happened?

  • KernelFactory registers IChatClient and adds CrmPlugin as a named plugin.
  • Agents invoke kernel.InvokeAsync with function names like crm.GetAccount.

Practice next

  1. dotnet add package Microsoft.SemanticKernel.
  2. build CrmPlugin with [KernelFunction] methods.
  3. Build Kernel in DI via KernelFactory.Create.
  4. Add HospitalPlugin alongside CrmPlugin and test selective registration.
  5. Log plugin name on each InvokeAsync for audit.

Remember

Semantic Kernel wraps chat clients and plugins in one Kernel. AgentNest centralizes Kernel creation in a factory. Plugins expose tools as attributed C# methods.

Unified agent host

Three squads each wrote custom OpenAI wrappers.

Outcome: KernelFactory standardizes plugin hosting and cuts duplicate HTTP code.

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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