With all the hype around AI, I was thinking it is a good time to actually build something simple, that will explain the basic principles of AI systems and LLMs. There are so many notions out there, so many new things, and technology is advancing so rapidly that even senior engineers have a rough time staying up to date. In order to make this as simple as possible, I will begin with the simplest example of how to integrate an AI API into a .Net app, and then build on that adding more features that will make clear a lot of concepts like : RAG, embeddings, grounding, chunking, guardrails, .Net agents and so on. I will build this in a public github repository, each step on a particular branch. Step 1 – From an LLM Call to a Grounded Application Note, before you try to run the code below, make sure you go over to https://platform.openai.com/ and generate an API key. Before running the application, create an OpenAI API key and configure it using .NET User Secrets or another secure configuration mechanism. You can test with your key in the appSettings.json also but never commit API keys to source control….