Build a Production RAG System
Give an AI your own documents and get answers with citations you can check. The retrieval system behind every serious AI product, built properly.
What you will learn
- Explain why uploading files into a chat stops working, and what replaces it
- Describe what actually happens between your file and your answer, step by step
- Install a working AI chat on your own computer and connect a provider
- Ingest real documents, including the awkward ones that break naive pipelines
- Chunk and label content, which is where answer quality is won or lost
- Understand embeddings well enough to predict what they cost
- Diagnose a useless answer and know whether retrieval or the prompt is at fault
- Return the right passage rather than a plausible sounding blend
- Produce answers with citations, so the output can be trusted and checked
- Automate a knowledge base that keeps growing without you feeding it
Curriculum
- Welcome Back
- Why Uploading Your Files Stops Working
- What You Are Going to Build
Requirements
- Comfort installing an app and running a couple of commands
- An AI provider account and a few dollars of credit
- Documents of your own worth asking questions about
- No machine learning background
About this course
Everyone tries the same thing first. Paste a document into a chat, ask about it, and it works. Then you add ten more documents and it stops working, because there is a limit to how much text fits in a single message.
Retrieval is the answer, and it is the quiet foundation under almost every AI product a business pays for. Instead of sending everything, you find the few paragraphs that matter and send only those.
This course covers it end to end, without the maths. What a chunk is and why the size decides your answer quality. How a question finds the right passage. What embeddings cost, in real numbers. Why an answer comes back useless and how to tell whether retrieval or the prompt caused it.
You work on a real app rather than a notebook, on your own machine, with your own documents. The final test is a question no generic chatbot can answer, because the answer only exists in a file you own.
Citations are treated as a requirement rather than a bonus. An answer nobody can verify is a liability in any business setting, and the course finishes on turning the system into something people pay for.
Who this course is for
- Developers who have hit the limit of pasting documents into a prompt
- Anyone building an AI product where a wrong answer has consequences
- Consultants and agencies whose clients keep asking for a chatbot trained on our documents
- People who want the foundation under most real AI products, not another prompt guide
Stop shipping demos.
This class comes with the rest of the library, every future class, and the same architecture I ship to paying clients. Start with 14 days free, then one payment. Never a subscription.