Staging environment

HuggingFace 101: Safely Switching AI Models

Hosted by Jai Bhagat

Wed, Oct 21, 2026

4:00 PM UTC (30 minutes)

Virtual (Zoom)

Free to join

Invite your network

Go deeper with a course

Make Safer AI Decisions
Jai Bhagat and Nicole Mercede
View syllabus

What you'll learn

Define what must stay stable

Identify the outputs, workflows, and user expectations that need regression checks before a switch.

Compare models on your tasks

Design a small evaluation set that reflects real prompts instead of relying only on vendor benchmarks.

Roll out with guardrails

Plan a staged switch with monitoring, fallbacks, and clear criteria for rollback.

Why this topic matters

Changing models can lower cost, improve speed, or unlock a capability, but it can also change behavior in ways users notice. In this lightning lesson, we will inspect the data behind a model swap and decide what needs to stay stable before a team rolls it out.

You'll learn from

Jai Bhagat

Director of AI Education at A+ Active

Teaching is the love of my life. I've taught meditation classes at Madison Square Garden, taught systems at Parsons School of Design and now I livestream myself learning to write kernels and advanced programming for GPUs and AI workloads.

Jai believes that with love and imagination that anything is possible.

See all products from Jai

Sign up to join this lesson

By continuing, you agree to Maven's Terms and Privacy Policy.