Teaching
AI systems engineering, taught as evidence work.
This page collects public-safe learning surfaces from the AI Systems
Engineering Handbook and related talks. The goal is to help students and
builders move from model demos to architecture, governance, security,
validation, and delivery evidence.
June 2026 Students, builders, course designers, and technical mentors
A public-safe accelerator that converts enterprise AI potential into reviewable system evidence: architecture, governance, security, validation, and customer-delivery readiness.
Enterprise AI delivery is proven by a system package with architecture, governance, deployment, security, validation, and customer-delivery evidence, not by a model demo alone.
Teaching surfaces
June 2026 Engineers, learners, and enterprise AI teams
A modular tutorial system for enterprise AI: foundations, infrastructure, LLM applications, RAG, AI Gateway, agent governance, voice AI, security, delivery, and AI-assisted engineering.
13 modules, master knowledge base, templates, references, and validation scripts.June 2026 Course designers and technical mentors
Day packages for AI Gateway, Agent Governance, and model-serving curriculum, including vLLM/SGLang, inference lifecycle, KV cache, prefill/decode, and governance boundaries.
Teacher packets and accelerator course materials published in the handbook repo.May-June 2026 Medical-device and regulated-AI teams
Slide, audio, transcript, and test-question support around AI software medical-device cybersecurity, FDA 524B, threat modeling, SBOM, Zero Trust, and Patch SLA.
CYBERSEC talk delivered; CDE teaching handoff prepared.