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Articles on .NET

Modern C# and .NET: Minimal API, RAG, streaming, function calling and agent orchestration.

LLM chat memory in ASP.NET Core: IChatReducer and MongoDB — Cool Solution
.NET

LLM chat memory in ASP.NET Core: IChatReducer and MongoDB

HTTP APIs are stateless, LLM chats are not: every turn needs to see the story so far. Resending *everything* on each message blows up ==tokens and the context window==. In this tutorial I build a .NET 9 Minimal API where **MongoDB keeps the full transcript** and the model only receives the view reduced by a **IChatReducer** from *Microsoft.Extensions.AI*: the last N messages, or an LLM-generated summary. Fully local with Ollama, and measurable on every single reply.

15 min read
RAG vs Agentic RAG: when retrieval is no longer enough — Cool Solution
.NET

RAG vs Agentic RAG: when retrieval is no longer enough

**Classic RAG** retrieves once and answers with the chunks it found. **Agentic RAG** exposes three tools to the LLM — *search*, *evaluate*, *refine* — which the model can use to iterate within a configured limit. I built them ==side by side in .NET 9==: same dataset, same questions, two endpoints. With code, traces and an operational benchmark.

16 min read
LLM observability in .NET: traces, tokens and cost with OpenTelemetry and the Aspire dashboard — Cool Solution
.NET

LLM observability in .NET: traces, tokens and cost with OpenTelemetry and the Aspire dashboard

An endpoint that calls an LLM is **a black box**: you don't know how long it waited, how many tokens it burned, what it cost. In this tutorial I instrument a ==.NET 10 Minimal API== with *OpenTelemetry* and *Microsoft.Extensions.AI*: spans that follow the *GenAI semantic conventions*, token and latency metrics, a hand-written **cost counter**, all visible in the **Aspire dashboard** running in Docker next to *Ollama*.

21 min read
LLM evaluation in .NET: testing response quality with Microsoft.Extensions.AI.Evaluation — Cool Solution
.NET

LLM evaluation in .NET: testing response quality with Microsoft.Extensions.AI.Evaluation

How **LLM evaluation** works in .NET: unit tests verify code, but ==a model's response is not deterministic== and must be *judged*, not compared. With *Microsoft.Extensions.AI.Evaluation* I build an ==xunit suite== that scores the *relevance*, *coherence* and *groundedness* of an assistant's answers, with a **local judge via Ollama**, disk-based caching and an ==HTML report== ready for CI.

18 min read
Hybrid search in .NET with Qdrant, BM25 and Ollama — Cool Solution
.NET

Hybrid search in .NET with Qdrant, BM25 and Ollama

==Hybrid search== in .NET: **dense** vectors and **BM25** keywords fused into *one ranking* with **Reciprocal Rank Fusion**. One Qdrant collection with *two named vectors*, local embeddings via *Ollama* and *Microsoft.Extensions.AI*, and a **Minimal API** that compares the three modes — *dense*, *keyword*, *hybrid* — over the same knowledge base. Then the level-up: a **RAG** endpoint that sends the retrieved documents to a local LLM, a **semantic cache** of the answers on Qdrant, **Redis** for output caching and **MongoDB** with a generic repository and pagination. Bonus: the AI provider becomes an *appsettings* switch — Ollama or any **OpenAI-compatible** endpoint — plus a hard look at **Microsoft Agent Framework**.

38 min read
Semantic caching for LLMs in .NET with Redis and Ollama — Cool Solution
.NET

Semantic caching for LLMs in .NET with Redis and Ollama

==Semantic caching== for **LLMs** in .NET: a *two-layer* cache that answers **repeated** and *reworded* questions without re-running the model. Exact match with *UseDistributedCache*, a *semantic* layer with embeddings and vector search on **Redis 8**, in a **Minimal API** with *Microsoft.Extensions.AI* and *Ollama*.

27 min read
Structured output in .NET: typed JSON from an LLM with Microsoft.Extensions.AI — Cool Solution
.NET

Structured output in .NET: typed JSON from an LLM with Microsoft.Extensions.AI

Structured output with *Microsoft.Extensions.AI*: why asking for JSON "please" in the prompt isn't enough, how a record C# becomes a *JSON Schema* that constrains the model, and a ==tutorial Minimal API .NET== where a local LLM with *Ollama* triages help desk tickets returning ==typed objects==, then saved to *MongoDB*.

19 min read
AI Agent Orchestration: patterns, frameworks and an ASP.NET Core example — Cool Solution
.NET

AI Agent Orchestration: patterns, frameworks and an ASP.NET Core example

==AI agent orchestration== is the pattern that in 2026 is replacing the single agent for complex tasks. Here I walk through the **4 patterns** (hierarchical, collaborative, competitive, hybrid), the **frameworks** that matter — from *LangGraph* and *CrewAI* to the *Microsoft Agent Framework* — and a **hands-on ASP.NET Core example** that orchestrates four specialised agents in a few lines.

13 min read
MCP transport protocols: stdio, HTTP and authentication in C# .NET — Cool Solution
.NET

MCP transport protocols: stdio, HTTP and authentication in C# .NET

==MCP transport protocols== explained in depth: **stdio** for local servers and **Streamable HTTP** for remote ones, with a note on the deprecated *HTTP+SSE*. When to pick *one over the other*, how **authentication** works (OAuth 2.1), and two **C# .NET** examples with *Microsoft Agent Framework* and *Microsoft.Extensions.AI*: one stdio without auth (Filesystem) and one HTTP with auth (GitHub).

24 min read