2026 cohort · Enrollment open · .NET 10 ready

Build AI systems that

The only course that goes from token to deploy: LLMs, RAG, Agents, Harness Engineering, MCP and observability, all with real code in .NET.

8modules
28hands-on lessons
9 h+of content
∞updates included
AgentRunner.cs
var client = new ChatClientBuilder(inner)
  .UseFunctionInvocation()
  .UseOpenTelemetry("NexusAI")
  .Build();
 
var ctx = Rag.Retrieve(query, top: 5);
var result = await runner.RunAsync(ctx, ct);
 
// ✓ 3 tools · 1.2k tokens · 840ms
// ✓ policy: safe · cost: $0.004
▶ "Order ORD-9981 is out for delivery."
Hybrid RAGrecall 94% · 38ms
Harness activesandbox · budget · evals
LLMsPrompt EngineeringRAGVector Search AgentsHarness EngineeringMCPTool Calling EvalsOpenTelemetryMicrosoft.Extensions.AI.NET 10 LLMsPrompt EngineeringRAGVector Search AgentsHarness EngineeringMCPTool Calling EvalsOpenTelemetryMicrosoft.Extensions.AI.NET 10
Method

Not another prompt course. This is engineering.

Every module ends with code you can ship on Monday. No endless slides, no theory disconnected from practice.

CORE

Harness Engineering as a discipline

The model is 20% of the product. The other 80% is the execution loop, tool routing, context management, permissions and telemetry. You will build a complete harness in C#, from executor to sandbox, and understand why it separates demos from products.

ExecutorTool routerContext managerPolicy layerEvals

RAG that doesn't hallucinate

Semantic chunking, hybrid search, re-ranking and faithfulness metrics.

Agents with tool use

From the basic loop to multi-agent patterns with Microsoft.Extensions.AI.

Native MCP

Model Context Protocol servers and clients with the official .NET SDK.

Full observability

Every call traced with OpenTelemetry: cost, latency and replay.

100% .NET 10 code

Real, testable, versioned examples. No pseudo-code.

Full curriculum

8 modules. 28 lessons. Zero filler.

From fundamentals to deploy, in dependency order. Each module unlocks the next.

01

AI & LLM Fundamentals

How a language model really works, no magic involved.

  • Tokens, embeddings and vector space
  • Attention and the Transformer architecture
  • Decoding: temperature, top-p and sampling
  • Limits, hallucinations and how to reason about them
4 lessons 69 min Beginner
02

Production Prompt Engineering

Prompts that work at scale, not just in the demo.

  • Anatomy of a system prompt
  • Structured reasoning and typed outputs
  • Evaluating and versioning prompts
3 lessons 54 min Beginner
03

RAG: Retrieval-Augmented Generation

Connect the model to your data with surgical precision.

  • Why RAG and not fine-tuning
  • Ingestion pipeline: chunking and embeddings
  • Hybrid retrieval and re-ranking
  • Advanced RAG: query rewriting, GraphRAG and agentic RAG
4 lessons 80 min Intermediate
04

Agents & Tool Use

From passive chat to autonomous task execution.

  • What an agent is (and is not)
  • Tool calling with Microsoft.Extensions.AI
  • Multi-agent patterns
3 lessons 59 min Intermediate
05

Harness Engineering

The infrastructure that makes agents reliable in production.

  • What a harness is and why the model is not enough
  • Building the executor in C#
  • Context management: compaction, memory and pruning
  • Permissions, sandboxing and human-in-the-loop
  • Agent evals and improvement loops
5 lessons 104 min Advanced
06

MCP: Model Context Protocol

The open standard for connecting models to any system.

  • Introduction to MCP
  • Building an MCP server in .NET
  • Consuming MCP servers and security
3 lessons 56 min Intermediate
07

Evals, Observability & Security

Measure, trace and protect AI systems.

  • LLM-as-judge and automatic metrics
  • Observability with OpenTelemetry
  • Prompt injection and defense in depth
3 lessons 58 min Advanced
08

Production with .NET 10

Architecture, cost and scale for real AI apps.

  • Reference architecture
  • Streaming, SSE and latency UX
  • Cost, caching and scale
3 lessons 54 min Advanced
0engineers trained
0average rating (out of 5)
0apply it within 30 days
0companies with students
Who has been here

Engineers who stopped building demos and started shipping.

★★★★★

The Harness module changed how I think about agents. Within two weeks I rewrote our company's executor with budgets, sandboxing and evals.

MC
Marina CostaStaff Engineer · fintech
★★★★★

Our RAG was at 60% precision. After hybrid search and re-ranking it passed 90. The course pays for itself in a single sprint.

RA
Rafael AndradeTech Lead · e-commerce
★★★★★

Finally AI content that speaks the language of .NET developers. MCP with the official SDK, OpenTelemetry, everything I use day to day.

JS
Juliana SouzaSolutions Architect · consulting
Pricing

One subscription. Everything included.

Cancel anytime. 14-day money-back guarantee, no questions asked.

Frequently asked questions

Everything you need to know.

Do I need to know .NET to take the course?
The examples are in C# with .NET 10, but the concepts (RAG, agents, harness, MCP) are language-agnostic. If you program in any modern language, you will follow along without trouble.
What is "Harness Engineering"?
It is the discipline of building everything around the model: the execution loop, tool routing, context management, permissions, sandboxing and telemetry. It is what makes an agent reliable in production, and it is the heart of the course.
Which AI providers are used?
We use the Microsoft.Extensions.AI abstraction, so the same code works with Anthropic, OpenAI, Azure, Ollama and others. You pick the provider through configuration.
How does the subscription work?
It is $19.90 per month, billed through our secure checkout. You get access to all modules immediately and can cancel whenever you want. Within the first 14 days we refund you in full if it is not for you.
Is there a certificate?
Yes. When you complete every lesson you receive a verifiable digital certificate.

The next generation of software is built with AI.
Be on the side that builds it.

Subscribe today and start the fundamentals module in under 2 minutes.

Subscribe for $19.90/month