Learn AI as engineering, not as a demo
Most AI tutorials stop at a prompt that worked once. The AI Academy takes you from LLM fundamentals through prompt engineering, RAG, agents and MCP to the parts that decide whether an AI feature survives production: evaluation, cost control and a fallback for when the model is wrong.
Fundamentals to production, in order
Start with how models actually behave, then retrieval, then agents, then the engineering discipline around them. Each stage assumes the last, so you build a real mental model instead of collecting tricks.
The parts tutorials skip
Evaluation harnesses, hallucination mitigation, cost per request and graceful degradation. These are the difference between a demo and a feature, and they are the spine of this academy.
Model-agnostic thinking
You will learn to build so the model choice can change — Anthropic, OpenAI, Google or an open model behind an interface — because coupling your product to one provider is a decision you will regret.
More in this group
Academies for the stacks we build with daily.
Cloud Academy
Deploy, scale and secure on the cloud without overspending.
React Academy
Learn React the way large, real apps are actually built.
Next.js Academy
App Router, rendering, SEO and deploys done properly.
DevOps Academy
CI/CD, containers, observability and shipping safely.
Product Engineering
Turn ideas into products people actually use and keep using.
Need this built, not just read about?
Send a paragraph about what you are trying to do. You will get a considered reply from an engineer — a shape, a rough timeline, and an honest view on whether we are the right fit.