A hands-on lab where learners configure LiteLLM as a local reverse proxy that intelligently routes requests between multiple LLM backends — a general model for simple prompts, a coding model and a reasoning model for complex ones — instead of hard-coding a single model into an application.

Run Hermes Agent as an on-call operations team for a storefront outage. Fan out parallel investigators, adjudicate a risky change with a Mixture-of-Agents board, execute the fix under a goal contract with machine-verified proof, and review the agent run afterward.

Why does a large language model write one token at a time, and how can a small drafter make it faster without changing the answer? Explore a real recorded run on an NVIDIA L40S through bets, interactive blocks and a head-to-head race. No GPU reservation needed: start anytime, finish in about 30 minutes.