Episode #60: The Operator's Roadmap for AI in 2026 - Lily Luo

Two ops leaders compare notes on building production-ready AI

Hey everyone, I hope you’re having a great start to 2026.

It’s been a minute since I’ve recorded—I’ve been going deep on AI topics, which has really become a central focus of my professional world. I even started a new Substack called AI Builders if you want to see what I’ve been thinking about. A recent post there is what sparked the idea for this podcast chat with Lily.

The operator's roadmap for AI in 2026

I also wanted to record this episode because I think we’re at a real inflection point. AI has evolved from an interesting app to converse with into a tool that can take on meaningful work, both what we do day-to-day and the work of teams we support in corporate environments. That’s a big shift.

Here’s the thing: most AI content out there isn’t geared toward people like me. It’s aimed at researchers or GTM engineers focused narrowly on outbound automation. It’s not for system builders and operators who need to bring AI into complicated corporate environments—with cloud tools, security restrictions, knowledge that can’t live locally, and a whole bunch of constraints that someone building in a vacuum doesn’t face.

There’s a real opportunity right now to help define those best practices. And I want to be part of that conversation.

So for this episode, I’m joined by Lily Luo, a systems and operations leader who’s been on a parallel path, rolling out impressive projects and thinking deeply about what all this means. She’s also the author of Applied AI for MOPS, where she is dropping a ton of knowledge from the field:

We’re going to talk about what happened in 2025, what it really means, and what you should be thinking about in the year ahead.

Hope you enjoy the discussion.