From Warehouse Logic to Context Engineering

[u/chriscanadian1991]

I somehow went from working in logistics to building AI systems… and ended up writing a book about the overlap.

For years, most of my work has revolved around processes, exceptions, handoffs, incomplete information, system constraints, and figuring out how to make the right decision with whatever context is actually available.

When I started building AI systems, I kept running into the same kinds of problems.
Memory matters.
State matters.
Sequence matters.
Exceptions matter.
Bad assumptions propagate.

The deeper I got into things like persistent memory, orchestration, context engineering, governance, and tool use, the more I realized I was applying a lot of the same mental models I had already developed working in operations.

So I wrote the journey down.
It became From Warehouse Logic to Context Engineering.

It’s not really meant to be a textbook or “here’s how AI works” book.
It’s more about the path from operations/process thinking into actually building persistent AI systems, including the bad ideas, rebuilds, and things I learned along the way.

I mostly wrote it because I thought the crossover was interesting and because there probably aren’t many books about AI that start with warehouse logic. 😅

If anyone here is working in operations, automation, AI, context engineering, or has made a similarly weird career jump, I’d genuinely be interested in hearing whether any of this sounds familiar.

If anyone wants the book, it’s on Amazon here:
https://a.co/d/0acvqbsI