LLMs are becoming more mature and accessible, and many teams are now integrating them into common business practices such as technical support bots, online real-time help, and other knowledge-based-related tasks.

However, the high cost of maintaining AI teams and operating AI pipelines is becoming apparent.

Maxime Armstrong and Yuhan Lo are software engineers at Daxter, which is an open source platform for orchestrating data and AI pipelines.

They join the show with Sean Falconer to talk about running cost-effective AI pipelines.

This episode is hosted by Sean Falconer. Check the show notes for more information on Sean's work and where to find him.

Yuan and Max, welcome to the show.

Thanks for having us. Yeah, I'm excited to have you here.

So why don't we start off with just a brief introduction?

Who are you and what do you do?

Yeah, my name's Yohan.

I joined Daxer four and a half years ago and now I lead developer success at Daxer.

And my team's goal is to ensure our users are happy with us and can get

their job done effectively through the tools we provide. Before Daxter, I am a tech lead at Yelp,

where I live part of the data platform team. I focused on product analytics and its automation.

Awesome. Same question over to you, Max.

Who are you?

What do you do?

Yeah, for sure.

I'm Max.

I'm a software engineer at Dexter.

So working with the developer success team with Yuan, making sure we provide tools that

help developers on board quickly with Dexter.

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