Tutorials ASP.NET Core with Agentic AI Tutorial

AI Memory — Complete Guide

AI Memory — 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 25 of 100

AI Memory

AI basicsAgents

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

What is this?

AI memory stores conversation history, user preferences, or retrieved facts across turns. AgentNest uses SK ChatHistory plus optional vector memory for long CRM relationships.

Why should you care?

ERP assistants referencing prior invoices need persisted thread state, not stateless POST bodies.

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/Memory/ThreadMemoryStore.cs
public sealed class ThreadMemoryStore(IDistributedCache cache)
{
    public async Task<ChatHistory> LoadAsync(string threadId, CancellationToken ct)
    {
        var json = await cache.GetStringAsync($"thread:{threadId}", ct);
        return json is null ? new ChatHistory() : JsonSerializer.Deserialize<ChatHistory>(json)!;
    }
    public Task SaveAsync(string threadId, ChatHistory history, CancellationToken ct) =>
        cache.SetStringAsync($"thread:{threadId}", JsonSerializer.Serialize(history),
            new DistributedCacheEntryOptions { SlidingExpiration = TimeSpan.FromHours(8) }, ct);
}

What happened?

  • ThreadMemoryStore persists SK ChatHistory in Redis with sliding expiration for active deal conversations.
  • Follow the steps below — typing the code yourself is the fastest way to learn.

Practice next

  1. Add StackExchangeRedis cache in Program.cs.
  2. Generate threadId per user conversation in API.
  3. Load history before agent call, append assistant reply, save.
  4. Encrypt serialized history with IDataProtector per tenant.
  5. Add memory summary job when messages exceed 40.

Remember

Persist ChatHistory externally for multi-turn AgentNest chat. Use sliding expiration aligned with session policy. Summarize or truncate old turns proactively.

Long CRM deal threads

AEs chat about the same enterprise deal for two weeks.

Outcome: ThreadMemoryStore restores context; summarization keeps tokens under budget.

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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