Trismegistus v3.33 - AI Expert Partner

Trismegistus v3.33 is an AMD ACT II AI Expert Partner demo. The build compares a prompt-only baseline route against an architecture-on route using the same model family and task shape. The architecture-on route adds Mirror Architecture / Stable-State Path discipline, source-backed memory retrieval, visible receipt context, and benchmark/novel-output gates. The demo shows the app running on the AMD-facing route with memory/RAG context visible in the browser, then explains the evidence ladder: baseline Gemma versus Mirror/Trismegistus recall, 500-turn target recall, quantum circuit-family routing, MQT receipts, and a new source-backed quantum candidate with variables, observables, controls, falsifier, and next experiment. The public claim is bounded: this is not a model-weight tuning claim or an official leaderboard claim. It is a same-route operating-layer demonstration showing how source memory, input cohesion, receipt discipline, and experiment gates can make a model more useful for expert workflows before additional fine-tuning.