Core mechanics
LLM Inference
Participants experience how token-by-token prediction becomes polished language.
Cross-functionalHealthcare
The technical depth track
Go deeper than the decision. See how the system behaves underneath it.
The live experience is about decision rights: where AI should automate, augment, assist, or escalate. These scenarios are the appendix behind that story, each one an optional deep dive into a specific behavior of the system, from data and training to safety, retrieval, and orchestration.
Data and behavior
LLM Training
Show how data, repetition, and feedback shape system behavior over time.
Cross-functionalEnterprise
Input design
Prompt Engineering
Prompting becomes a lesson in structure, constraints, and task framing.
HealthcareEnterprise
High-stakes workflows
AI Safety
Plausible output can sound polished and still be dangerous.
HealthcareCross-functional
Decision oversight
Human-in-the-Loop
Make visible how review changes both trust and responsibility.
HealthcareEnterprise
Context retrieval
RAG
See what changes when a model is grounded in outside information.
EnterpriseCross-functional
Autonomy
AI Agents
Understand why autonomy raises the stakes for structure, observability, and safety.
EnterpriseCross-functional
System coordination
Multi-Agent Orchestration
Show how coordination, not just capability, determines the quality of complex systems.
EnterpriseCross-functional
Data governance
Data Readiness
A model is only as good as the data it learns from.
HealthcareEnterprise
Monitoring and oversight
Performance Audit
Systematic failures only become visible in aggregate.
EnterpriseCross-functional