Tutorials ASP.NET Core with Agentic AI Tutorial

AI Analytics — Complete Guide

AI Analytics — 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 59 of 100

AI Analytics

AI basics ✓Agents

Agents · 2 — Build · ~10 min · Module 6: AI Security and Observability

What is this?

AI analytics measures adoption, quality, cost, and outcomes of copilot features. AgentNest tracks prompts per tenant, tool success rate, and human edit distance on CRM drafts.

Why should you care?

Product leaders justify GPU spend with usage dashboards; compliance wants proof hospital staff override unsafe suggestions.

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.Analytics/AiUsageRecorder.cs
public sealed class AiUsageRecorder(AgentNestDbContext db)
{
    public async Task RecordAsync(string tenantId, string feature, int tokens, bool thumbsUp, CancellationToken ct)
    {
        db.AiUsageDaily.Add(new AiUsageDaily
        {
            Day = DateOnly.FromDateTime(DateTime.UtcNow), TenantId = tenantId,
            Feature = feature, Tokens = tokens, PositiveFeedback = thumbsUp ? 1 : 0
        });
        await db.SaveChangesAsync(ct);
    }
}

What happened?

  • AiUsageRecorder aggregates daily tokens and feedback per feature — CRM draft, hospital triage, ERP explain.
  • Follow the steps below — typing the code yourself is the fastest way to learn.

Practice next

  1. Create AiUsageDaily table partitioned by month.
  2. Record usage in middleware after AI responses complete.
  3. Build Power BI dataset from SQL or export to Synapse.
  4. Add EditDistance metric comparing CRM draft to sent email.
  5. Alert when tenant token growth exceeds 200% week over week.

Remember

Aggregate tokens, feature, and feedback per tenant daily. Analytics inform cost allocation and quality improvements. Avoid storing raw prompt text in analytics DB.

Copilot ROI review

CFO asks which AgentNest modules justify Azure OpenAI invoice.

Outcome: AiUsageDaily shows CRM draft saves 12k tokens per rep per week with 78% positive feedback.

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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