The Agents Economy Backbone - with Emily Glassberg Sands, Head of Data & AI at Stripe
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What does Emily’s role as Head of Data & AI at Stripe actually involve?
Hey everyone, welcome to the Laden Space Podcast. This is Alessio, founder of Kernel Labs, and I'm joined by Swix, editor of
Ladin Space. Hello, hello. We're back in the studio with Emily Sands from Stripe. Welcome.
Thank you.
So Emily, you're head of data and AI at Stripe. That's a that's a big title. Uh what does that actually mean in practice?
So Stripe is building financial infrastructure for the Internet. We started out as payments infrastructure, and now we are helping businesses solve a whole range of problems. How do they accept recurring payments like subscriptions? How do they do usage billing, revenue recognition, tax, money movements, accept stable coins, and more? And when you think about what we're looking at, we're looking at on the order of 1.3%. Of global GDP. About $1.4 trillion a year is processed on Stripe. And so that obviously creates a very unique opportunity to use that data to understand both what's happening in the economy, what do our users need, but also feed it back into the product to power better payments experiences.
So cut down on fraud, drive the right authorization, better customer-facing experiences. Optimizing the checkout suite and more. So anyway, our our data in AI org is just really focused on helping Stripe make effective use of our data. And that starts sort of all the way at the foundation layers, right? Like what's the data platform? How do we do data engineering? What are our ML infrastructure, AI infrastructure, and then all the way up to the applied layer? We also have a fun little group. It's actually quite small, it's just two dozen people, but um we call it the experiment. Projects team. Um And it's not data specific, but the premise is experimentation can and should and does happen everywhere. But there are often these sort of cross-stripe opportunities that are being pulled out of us by our users, just given the pace at which the world is changing, that aren't natural or easy to jump on within any one product vertical today.
These are just quite senior, quite seasoned engineers who run at those opportunities and and zero to one them and get them off the ground. So our agenda commerce work came out of that. Um token billing, which we can talk about uh in a bit, also came out of that. And and that's just a fun sort of side angle um within our group that's that's proven very high leverage.
Yeah, I I like the frames framing that, you know, Stripe's mission is build financial infrastructure for the internet and y your subset of that is build f economic infrastructure for AI. And that's that's a that's a pretty ambitious
goal. Um, you've been a Stripe four years. At what point did AI become a title level thing? Because I mean you were obviously using machine learning for like fraud detection and everything, like
we started investing in AI or LLM specific experiences, basically when GPT 3.5 hit the scene. We were like, okay, we need everybody to be able to have um high-quality, safe, easy access to LLMs, not just for their own, you know, day-to-day work usage, but actually to build, you know, production grade experiences. So that that that's sort of What was that early twenty like January 2023 or late 2022? We we started reasoning about, okay, like, you know, it's not just ML infrastructure, it's also AI infrastructure. It's not just ML applications, it's also AI applications. But then it was really only in the last year and a half or so that we said, hey, I mean, we had like transformers and whatever before, but only in the last year and a half or so that we were like, hey, we actually need to have our own domain-specific foundation model.
And actually we Can move from these single task point solution ML models to you know, uh a much richer, denser payments embeddings that can then power the the various downstream applications. So so I think it was an evolution for us. And you know, I think we could still debate like what's ML and what's AI in the industry at large. But you're right that we're more than a decade into using ML at Stripe, you know, way back in the early days for not just radar, which I think people
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Chapters
8 chapters
1
What does Emily’s role as Head of Data & AI at Stripe actually involve?
0:04–12:53
2
How does Stripe use domain‑specific foundation models and payments embeddings to fight fraud?
12:53–25:56
3
What is the Agentic Commerce Protocol (ACP) and why is it a game‑changer for AI‑driven commerce?
25:56–37:27
4
How does token billing work and why does outcome‑based pricing matter for AI companies?
37:27–50:23
5
Why are AI companies growing faster, more globally, and what does that mean for the AI economy?
50:23–1:00:38
6
How is the social contract around AI shifting and why do brand and design matter in AI products?
1:00:38–1:13:15
7
Will AI’s impact on productivity show up in GDP and how might it reshape economic growth?
1:13:15–1:25:09
8
What talent is Stripe looking for and how can engineers help build the future of AI infrastructure?
1:25:09–1:37:02
Speakers
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