The Best of 2024 (so far) with Sarah Guo and Elad Gil

**Conviction** (0:07)
Hi, listeners, welcome back to NoPriors.
We're halfway through 2024, so we're doing a mid-year best of episode, where we go back to some of our favorite moments from episodes so far, and catch you up on everything that's been going on in AI, from the state of the art in research to hyperscalers and upstarts. We'll list all the episodes featured, so you can go back and relisten to the whole conversation. To kick it off, we're gonna hear a little bit from Emily Glassberg Sands, who's the head of information at Stripe. We talked a lot about how AI can help small businesses make a big impact in the economy. Here, she talks about the intersection of FinTech and AI.

**Elad Gil** (0:45)
When you think forward on the directions that the overall financial services industry is going, and let's put Stripe aside for a second, because I think Stripe is obviously a core company to sort of the internet economy, and it touches so many different pieces of FinTech and things like that, but where do you think outside of Stripe the biggest white space for FinTech's employing AI is? Like from a startup perspective or even an incumbent perspective, where do you think this sort of technology will have the biggest impact?

**Emily Glassberg Sands** (1:13)
It's a great question. I don't know exactly what others will do. I think having a really robust understanding of identity, who businesses are, what they're selling, has always been important. I think often in industry, we think it's important for marketing or sales or sort of go-to-market motions. It's also super important in FinTech.
Yeah, it's important for credit lending decisions, but it's also important for supportability decisions and understanding where the business does or does not meet the requirements of a given card network or a given BIN sponsor.
And so I think that identity piece, like who is this merchant? Are they who they say they are?
But also, what's their business? What are they selling? And how does that map to this pretty complicated regulatory environment is a really interesting and hard problem that lots of folks are solving in their own ways, but is likely an opportunity. I think there's almost certainly an opportunity to, whether Stripe does it or somebody else does it, to make sort of financial integrations way more seamless. Stripe has a whole suite of no-code products, so you can use payment links or no-code invoicing. But how does one actually build a really robust specific to the user integration without needing a substantial number of payments engineers or any complicated developer work? LLMs are proving that they can be very good at writing code. We have a couple cases, actually, where we're already seeing it work, but as the decisions get more and more complicated, I think there's still a lot of work to do to build the right integration and to build it well in an automated way. And then I think, as I mentioned before, some of this layer on top of the payments data of like, okay, you could build solutions that make payments work better, but payments actually allows you to really deeply understand and improve the business is pretty fascinating. And you'd have to think about like, is it a startup that does that? Or is it an incumbent that does that? And what's the business model?
What's the business model there? But, you know, if I think about the case of Stripe, you know, sort of Stripe has the opportunity to be beneficent, right? Incentives are super aligned. The more Stripe can help its users, businesses grow, the more Stripe grows and the more the economy grows. And so whether it's Stripe or someone else using financial data to help businesses be more successful, to grow the pie, to grow the GDP, I think is really powerful.

**Conviction** (4:22)
Up next, we have a clip from our conversation with friend and formidable founder, Dylan Field, whose company is using AI to change the design process and bridge the gap between design and development. We talk about how bringing AI into the creative process changes the creative job.

**Elad Gil** (4:39)
Basically, you're moving from a human to human and a human collaboration company to a human to AI collaboration company over time in some sense, because what you're describing seems like a really interesting way to have co-pilots augment humanity or augment creativity. Are there other ways that you've thought about the substantiation of that sort of creativity augmentation or how AI really interacts with human creative potential?

**Dylan Field** (5:05)
Well, these are just examples of things that I have seen or thought about that I think could be cool in the creative space, because you asked about. But I think in the design context, one thing that really matters a lot is the iterative loop and being able to keep going back and forth to an agent and give more instructions over time. If you just kind of go to first principles here, there's so much that you're not able to communicate via a prompt. Like if you think about great design, it often captures something about the culture, the ethos of the moment.