📚 From PDF Overload to AI Clarity: Building an AI RAG Assistant
Introduction
If you’ve ever tried to dig a single obscure fact out of a massive technical manual, you’ll know the frustration 😩: you know it’s in there somewhere, you just can’t remember the exact wording, cmdlet name, or property that will get you there.
For me, this pain point came from Office 365 for IT Pros — a constantly updated, encyclopaedic PDF covering Microsoft cloud administration. It’s a superb resource… but not exactly quick to search when you can’t remember the magic keyword.
Often I know exactly what I want to achieve — say, add copies of sent emails to the sender’s mailbox when using a shared mailbox — but I can’t quite recall the right cmdlet or property to Ctrl+F my way to the answer.
That’s when I thought: what if I could take this PDF (and others in my archive), drop them into a centralised app, and use AI as the conductor and translator 🎼🤖 to retrieve the exact piece of information I need — just by asking naturally in plain English.
This project also doubled as a test bed for Claude Code, which I’d been using since recently completing a GenAI Bootcamp 🚀.
I wanted to see how it fared when building something from scratch in an IDE, rather than in a chat window.
👉 In this post, I’ll give a very high level overview of the four iterations (v1–v4) - what worked, what failed, and what I learned along the way.