AI agents and tool calling in .NET: the loop, written by hand
An AI agent is a model calling your tools in a loop until the task is done. Here is that loop in plain C#, with the limits and human checks that keep it safe.
#ai-engineering
MCP explained: build a Model Context Protocol server in C#
What the Model Context Protocol is, how tools, resources and prompts differ, and a complete MCP server in C# with the official SDK that the AI agent and other AI apps can call.
RAG in .NET: answer questions from your own documents with an LLM
Retrieval-augmented generation explained for backend developers, chunking, retrieval and grounded answers with citations, plus a runnable C# example you can extend.
LLM API basics for .NET developers: tokens, context and structured output
Tokens, the context window, system prompts, structured JSON output and stop reasons, the five things to understand before building anything on an LLM, with runnable C#.
An AI engineering roadmap for .NET developers: from first API call to agents
A practical order for learning AI engineering as a backend developer, LLM APIs, RAG, MCP, agents and evals, with what to build at each step.