No signup. Three complete lessons — the vocabulary, the method's first move, and the method applied to security. Real prose, real diagrams, real code. If they're worth your time, the full line is.
The method: generate → judge → gate → retry. LLM is the commodity; the harness is the moat.
~30 minutes end-to-end. If you can read Python, you're ready.
The four ideas every module assumes — an LLM call & a trace, RAG, the Python you need, and judge / gate / eval. No eval or ML background required; the jargon is taught from zero.
Read the primer → 0.1 · THE METHODThe first move of the whole method: point a discovery judge at your traces, get back a ranked failure taxonomy, and decide which failures deserve a gate. Read the real code here; the runnable lab ships with the course download.
Read lesson 0.1 → SEC.1 · THE METHOD, APPLIEDThe same method pointed at security: map an LLM app's attack surface to the OWASP-LLM Top 10 and spot the blind spots — the first move of the Securing LLM Apps track.
Read lesson SEC.1 →The full line is 8 tracks · 58 lessons · 57 runnable, offline labs · a research brief per track — a downloadable kit you own, not a stream. Explore the syllabus while launch details are finalized.
See the full syllabus →