The Analyst's Stack
Automation and AI for Investigators
If you check the same sources by hand every week and still hear about things late, this series is for you. It shows how to make a machine do the looking, so you find out in 15 minutes instead of next Tuesday and spend your attention on what a thing means.
The idea that holds it together: every collection system I have built, and every one I have taken apart, is the same 6 stages in a row. Collect, normalize, store, analyze, alert, present. Once you can see them, an unfamiliar tool stops being a mystery. You are working out which stages it covers and which it leaves to you.
There are 22 posts, of 2 kinds.
The guide — 10 teaching posts. Five foundations lay out those stages and where AI genuinely earns a place inside them. Five methods cover the parts people get wrong: running models on your own machine, reaching sources that block you, measuring whether an AI step works, automating without writing code, and storing what you collect so you can search it.
The showcase — 12 short posts, one per working system. Why it was built, what it solves, how it fits together, and what it cannot do.
Start with part 1, even if you have never written a line of code. The hard part of this work is knowing which source is worth watching, and you are already good at that.
Not AI, not robots. Six stages that every collection system turns out to be a version of — and the 4 cases where the right answer is to do it by hand.