I broke down exactly how to evaluate LLM & RAG systems in production.

Recorded a 50+ minute masterclass [LIVE]:

Watch here for free youtube.com/watch?v=hcJ…

This is the same playbook I use when shipping production AI apps. And it's extremely simple to learn.

If you're tired of generic benchmarks and demo projects....

This is for you.

Here’s what you’ll walk away with:

→ How to monitor LLM/agent traces and add prompt versioning

→ A quick way to sanity-check RAG ingestion before tuning retrieval

→ How to compute RAG retrieval metrics with LLM judges on real eval datasets

→ How to score the end-to-end AI agent and track experiments over time

→ When (and how) to use LLM-as-Judge responsibly

→ Setting up a lightweight feedback loop to build better datasets fast

100+ people joined live when I presented this at Open Data Science Conference (ODSC) East Boston.

And the reviews were 🔥:

⭐ “One of the best hands-on of the virtual BootCamp.”

⭐ “Your session was one of the best of the entire conference.”

This playbook is battle-tested.

And now it's yours for free.

👉 Watch here: youtube.com/watch?v=hcJ…