Builder
How models really work, and building with them: APIs, automation, agents.
1 module · 7 lessons · about 1 hour · 6 more coming soon
How large language models work
Tokens, embeddings, attention, context windows, temperature and training: what is actually happening when a model answers you.
Training, fine-tuning and retrieval
Pre-training, fine-tuning and retrieval-augmented generation (RAG): which one solves which problem, and what each really costs.
Working with AI APIs
Keys, models, tokens and costs, rate limits and caching: calling a model from your own code or no-code tool, safely.
Automation and no-code workflows
Building real workflows in Zapier, Make and n8n, with AI steps that summarise, classify and draft, and humans where they belong.
Agents and tool use
What makes an agent, tool calling, MCP, agent loops and guardrails: building AI that takes actions, and keeping it on a short lead.
Evaluating AI systems
Evals, benchmarks and their limits, test sets and human review: how to know whether an AI system is good enough to ship.
AI security
Prompt injection, data leakage, jailbreaks and supply-chain risk: the new attack surface, from the defender's side.
