Learn to build agents that actually do the work.

Getting Started

What autonomous agents are, how this academy works, and how to think in loops.

Python

Simple Python from zero: names, lists, functions, files, JSON, errors, tests, and the loop every agent uses.

Mathematics

Simple math from zero: lists of numbers, scores, chance, entropy, and the formulas agents actually use.

Machine Learning

Simple ML from zero: examples, splits, loss, ranking, and the loop you use to judge an agent.

Neural Nets & Transformers

Simple transformers from zero: tokens, attention, decoding, and the stack every agent call runs.

Large Language Models

Simple LLMs from zero: chat APIs, tokens and cost, JSON actions, and when not to call a model.

Prompting

Simple prompting from zero: four parts, examples, tags, injection, evals, and the OS an agent actually reads.

Tools & Function Calling

Simple tools from zero: schema, dispatch, idempotency, sandboxes, MCP, and permissions your runtime actually enforces.

RAG & Memory

Simple RAG from zero: chunks, cosine, hybrid search, citations, agentic retrieve, and memory that is not one vector soup.

Agent Architectures

Simple agent loops from zero: six parts, ReAct, plan-and-execute, reflection, typed state, HITL, jobs, and when not to agent.

Multi-Agent Systems

Simple multi-agent from zero: split only when tools and checks diverge, typed handoffs, supervisors, debate, swarms, and how teams fail.

Evals & Safety

Simple evals from zero: golden properties, tool tests, judges you measure, traces you replay, injection allow-lists, and a spec that can say no.

Production Agents

Simple production from zero: gateway and jobs, traces you can operate, caps and queues, secrets, CI gates, and kill switches you have practiced.