Application Infrastructure for AI Builders: Protocols, Architecture, Operations

Self-driving cars, the fridge that reorders your groceries, Netflix at peak hour, the bank app you trust with your money. They look nothing alike, but underneath they run on the same handful of technologies: the same protocols, the same way of moving a request across the world and back, the same decisions about what to store, what to cache, and what to do when something fails. None of it is new, and almost none of it is taught. What if you could learn the layer that all of it rests on, well enough to build on it yourself and know exactly where it will hold?

Who is the course for

This is for people who build and have begun to feel the limits of what they understand. You write code, or you direct the people and tools that do, and you can get something working without being able to say why it holds, what it will cost, or how it behaves once more than a handful of people rely on it. You do not need to be a career engineer to belong here. You need to build things that other people depend on, and to have decided that not understanding the layer underneath has become a problem worth fixing.

What we work on

The course lives in the gap between something that runs on your laptop and something that runs in the world. That is where most of the difficulty is. A system that worked on Friday slows to a crawl on Monday, and the cause is somewhere in the layer you never had to look at. The cost of running it turns out to be several times what you expected. Someone asks whether it is secure and you cannot give an honest answer. These are common problems, and learning to see them coming is most of what separates someone who can ship from someone who can be trusted with what they shipped.

To get there, you spend time at the level where these things are decided: the terminal, the protocols, the path a request takes as it succeeds or fails. DNS, HTTP, caching, queues, authentication, the load balancer that keeps you online. We treat these as the working vocabulary of someone who can look at a system and tell where it will break, not as trivia to memorise.

We use AI throughout, for building and for thinking through architecture. The aim is not to work around it, but to understand the foundations well enough to direct it, and to catch it when it is wrong.