BEKADANAI Engineering for .NET Developers
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AI ENGINEERING FOR .NET DEVELOPERS · IN PRODUCTION

Production AI engineering
for .NET developers

Build AI features that are measured, observable and safe — in C#.

Join the waitlist

Hear first when AI Engineering for .NET Developers opens, with early access and a launch discount.

See what you'll build
jobscout — illustrative output
$dotnet new webapi -n JobScout
$dotnet add package Microsoft.Extensions.AI
$dotnet run --project JobScout.AppHost
✓ api · postgres + pgvector · ollama
$dotnet test JobScout.Evals
# evals gate every release
$

What you'll build: JobScout

One job-search assistant, built up across the course

  1. 01STRUCTURED OUTPUT

    Job-posting normalizer

    Messy job posts in, typed C# records out.

  2. 02EMBEDDINGS + PGVECTOR

    Semantic job search

    Search postings by meaning, not just keywords.

  3. 03RAG

    Answers with sources

    Questions answered from the postings, with citations.

  4. 04AGENTS + TOOLS

    Career Assistant agent

    An agent that calls your C# methods as tools.

  5. 05HUMAN-IN-THE-LOOP

    Approval before any write

    Nothing changes until a human says yes.

  6. 06MCP

    MCP server

    JobScout search, exposed to other AI clients.

What you'll learn

Production patterns, in C#

  • Write provider-agnostic AI code with IChatClient (Microsoft.Extensions.AI)
  • Add middleware for logging, caching and telemetry
  • Get typed structured output instead of parsing text
  • Build semantic search with embeddings and pgvector
  • Answer questions with RAG and citations
  • Expose C# methods to the model as tools
  • Build agents and workflows with Microsoft Agent Framework
  • Add human-in-the-loop approval and idempotent side effects
  • Build and publish an MCP server in C#
  • Defend against prompt injection
  • Trace every model call with OpenTelemetry
  • Measure performance with BenchmarkDotNet
  • Gate CI on evals, so regressions fail the build

LOCAL-FIRSTEverything runs on free local models with Ollama, so you can follow along without paying for an API.

Who it's for

FOR YOU IF YOU ARE

  • C#/.NET backend developers who want to ship AI features to production
  • Developers who care about measuring, observing and securing what they ship

NOT FOR YOU IF YOU WANT

  • A beginner C# course: you should already be comfortable with C# and .NET
  • An ML or model-training course: you use models, you do not train them

The stack

Current .NET, end to end

  • .NET 10
  • Microsoft.Extensions.AI
  • Microsoft Agent Framework
  • MCP C# SDK
  • Ollama
  • PostgreSQL + pgvector
  • .NET Aspire
  • OpenTelemetry
  • BenchmarkDotNet
  • Blazor

ABOUT

Taught by Burak Emre Kadan

I've spent 12 years building .NET backends — most recently leading teams that design distributed systems on Azure. My day-to-day has been the unglamorous parts that keep production running: retries and circuit breakers, idempotent consumers, outbox patterns, tracing with OpenTelemetry, and decisions written down as ADRs.

That's the lens I bring to AI. An LLM call is just another unreliable dependency — it needs the same engineering discipline as everything else in your system. This course teaches exactly that, in C#.

MORE ABOUT ME
Experience
12 years in C# and .NET
Focus
Distributed systems, reliability, observability
Format
Self-paced video course with a working codebase

Roadmap

More .NET AI courses are in the works

  1. NOW

    AI Engineering for .NET Developers

    In production. Join the waitlist to hear the moment it opens.

  2. NEXT

    More .NET AI courses

    In the works. Newsletter subscribers hear about them first.

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