Understanding AI project architecture update (7 Oct 2026): Core sequence is now 1) What is AI? 2) How does modern AI do what it does? (includes why AI improved so much as a sub-theme) 3) What can AI actually do? 4) Why does AI behave the way it does? 5) When does AI expand my thinking, and when does it replace it? 6) Can I trust AI? 7) What changes when a model becomes a system? 8) What changes inside organisations when AI becomes part of work? 9) What does AI cost, and who captures the value? 10) What changes at the level of an economy or country? 11) Where does this leave me? Optional: profession-specific use cases, access to knowledge vs expertise, technology leap vs investment bubble, small-business capability, AI as intermediary for knowledge/authority, how I currently work with AI, interpretability, consciousness, security/privacy/data rights, accountability, possible chronological history. Explicitly out of scope: government policy prescriptions and geopolitics. Next step in a fresh session: source mapping using the older handoff, a newer handoff, and both research reports.