Command the AI landscape — from foundation models to autonomous agents

If you're in a technical or product role right now, you already feel the pressure. Every week there's a new model release, a new framework, a new claim about what AI can or can't do — and the expectation from your organization is that you have answers. You're expected to evaluate vendors, challenge hype, make build-vs-buy calls, and communicate a coherent AI strategy to stakeholders at every level. That's a tall order when the field is moving this fast and most of the available content is either too shallow or written for researchers, not practitioners.

I built this school because I kept running into the same gap: smart, experienced technologists and product leaders who had assembled fragments of AI knowledge from articles, demos, and conference talks — but who lacked the structured, end-to-end mental model that would let them actually lead. They knew enough to be dangerous but not enough to be confident. This curriculum is designed to close that gap completely.

We start from the architecture up — not because you need to implement a transformer, but because understanding how these systems work gives you the diagnostic clarity to evaluate them honestly. From there we move through the full platform landscape — OpenAI, Anthropic, Google, and the open-source ecosystem — with a focus on comparative evaluation for real use cases, not benchmarks designed for press releases. Then we go deep on the thing that's genuinely changing the game right now: agentic AI. How agents reason, how they use tools, how memory systems extend what's possible, and how frameworks like LangChain, LangGraph, AutoGen, and CrewAI let you orchestrate all of it.

But technical fluency alone isn't enough. The back half of this school deals directly with strategy, risk, and leadership — because the highest-leverage decisions in AI aren't about model architecture, they're about knowing where to deploy AI to create durable value, how to govern it responsibly, and how to build a roadmap that your organization can actually execute. We cover data privacy, IP, alignment risks, regulatory considerations, and — crucially — how to communicate all of this clearly to the people making the big calls.

You'll leave this school with a complete, up-to-date map of the generative and agentic AI landscape, the ability to design a working agentic pipeline, and the strategic and communication tools to lead AI initiatives with credibility. This is the foundation I wish I'd had when the field first took off — and I'm genuinely excited to build it with you. Come in, get rigorous, and let's get to work.