For coaches & teachers
Everything to teach the AI-Agents track: three ready-to-present decks with coach notes, three Google Colab notebooks where students build real agents, and a printable energizer for every session.
Level 1.5 turns the Agents roadmap (10 deep dives) into a taught workshop. It bridges Level 1 · Foundations and Level 2 · Build agents (Weeks 2–5). See all levels on the coach home.
The track at a glance
.ipynb, then in Colab → File → Upload notebook.One-page cue sheet per session — running clock, prep checklist, block-by-block cues: open the Facilitator Run-Sheets.
Human Calculator → Human LLM — students act as a calculator (same answer every time), then as an LLM (a different plausible answer each time). The fastest way to make "AI predicts likely words, it doesn't compute one truth" click. Great before Session 1.
What is an agent · the LLM engine · the agent loop → build one
Tools & actions · prompting · memory (embeddings)
Architectures · building · testing · safety (prompt injection)
Two deeper build labs for Stations 7 & 8 — the same agent (a REST API call + an MCP call to solve a problem), one visual, one in code. Great as a stretch, a bonus session, or a bridge to Level 2.
Drag-and-drop · Agent + API Request + MCP Tools · zero code
Python · ADK agent + REST API tool + MCP toolset · free on Gemini
Tip · Running the room
The ideas are the setup; the agent they build is the payoff. Keep theory tight, run the energizer to reset energy, then give the longest possible stretch in Colab. Pair students up so no one is stuck on a setup or tool error.
Self-study students can read the Level 1.5 roadmap & deep dives first, then come build. Part of learn.millionroots.com.