service / likes
ElevenLabs
“I don't know how big self-serve is, but as a user, I like to be able to fiddle with ElevenLabs and not have to go talk to sales.”
Public evidence record
Co-founder · Stripe
Books, apps, and tools
service / likes
“I don't know how big self-serve is, but as a user, I like to be able to fiddle with ElevenLabs and not have to go talk to sales.”
book / likes
“One of my favorite books about accounting is the End of Accounting, which talks about how GAAP is basically poorly suited to this day and age.”
Claim ledger
79 transcript-backed records
01 / recommendation
“You should get more connections on LinkedIn so that there is content in your feed and your view is that you should separate out the people you want to interact with and having stuff to do in the app.”
02 / evaluation
“In the context of building hardware, one thing I hear from people who do it is that it's harder in the US because of the supplychain dynamics.”
03 / preference
“You have been much more of a believer in the AR form factor than almost anyone I know for a very long time. What gave you the conviction that this is the right form factor?”
04 / preference
“You don't use Android, you build your own OS for it.”
05 / evaluation
“Like Netflix is actually a competitor because it's also a thing that you could do with your time.”
06 / prediction
“There's been a general trend, I think, of businesses directly monetizing, like having their equivalent of direct revenue be more relevant with AI because the inference costs are real.”
07 / evaluation
“As I think about Snap, one of the things you've done well is you've kept it cool, and you've avoided the "ick" of it feeling like it's too big, which again, sometimes social networks run into.”
08 / belief
“As I think about the funding rounds you mentioned being hard, one of the investors I know who has consistently had the most steadfast belief about DoorDash is Michael Abramson, who was at Sequoia back in the day.”
09 / evaluation
“I'm just curious what you think of that viewpoint that we're doing reservations all wrong, which was, I think, one of the founding insights of Tock.”
10 / evaluation
“I think people maybe thought that big chains were going to do it more, where you're right, the billboard effect for an actual retail presence is hard to compete with, where you get this very cheap customer acquisition from the fact that people know your name from the high street or maybe have been to you, and as a ghost kitchen, you need to make up for that awareness gap.”
11 / evaluation
“I think he said, "You have to do the math and work out that the economics of this business do work," and they do, therefore, a more compelling product experience will win.”
12 / preference
“I think about one of the beliefs that informed their products most strongly was that no-shows are terrible for restaurants, and a restaurant reservation should be like a flight reservation, where you don't just get to decide you're not going to go to the restaurant.”
13 / preference
“Two topics that are on the minds of all our customers today are, yes, stablecoins and then AI, specifically with respect to changing buying, agentic commerce. On stablecoins, I think maybe DoorDash is not where I would start.”
14 / evaluation
“Then there's the really old-school restaurant where the owner might greet you and might comp your dessert or something, but it's very sporadic and very dependent on the owner being there because as you say, when the new waiter or waitress is there, they don't know you.”
15 / prediction
“There's the fact that high-end restaurants can't make any money these days because no one drinks.”
16 / evaluation
“As I think back to 2013 and those early days, the iPhone and the apps that were made possible by the iPhone was the defining tech trend of the era.”
17 / evaluation
“As I think through AI applications for DoorDash, one thing I'm struck by is that the LLMs are pretty good recommenders, just by tossing things into context.”
18 / belief
“I think people have an intuition around big LLMs where there are these very expensive training runs, and yes, they depreciate quickly, but there's so much usage that all of the models trained to date have paid off their training runs and then some.”
19 / belief
“I think we've mostly moved away from just raw parameter count, but I think the leading edge LLMs are in the hundreds of billions of parameters.”
20 / preference
“I don't know how big self-serve is, but as a user, I like to be able to fiddle with ElevenLabs and not have to go talk to sales.”
21 / preference
“Maybe you want to have a subscription with some unlimited tiers, but I don't know if you had the experience of you're using Claude, and you're typing away your queries, and eventually you hit some rate limit, and it's like, "Sorry, you've hit your usage limit," and you want to be able to do the thing that you can do with Claude Code, which is just pay per API.”
22 / preference
“Then on Gemini and ChatGPT and those apps, I want to use the voice mode, but I don't know about you, it just doesn't work.”
23 / evaluation
“It's one thing with SaaS where you get these vertical-specific providers, but I would imagine one of the biggest risks for you guys in being intermediated is if there is, like in this example, a closed captioning service that is on a two-versions-old version of ElevenLabs and hasn't upgraded. That's a problem because you want people to be using the latest and greatest model that you've developed, and you'll be deploying new capabilities every week.”
24 / belief
“I think what Elad is getting at is a feeling where I saw a tweet go by that someone was saying, "What you have to realize to explain what's currently going on in the Valley is that every tech executive has severe AI psychosis right now, and is spending a huge amount of time writing code and talking to AI and things like that.”
25 / belief
“I think Waymo is a good example of this question I have, which is Google does cut projects, and there's various things you've tried where you said, "We're actually not going to fund this part of X all the way, or we're going to retire this product.”
26 / belief
“I think the root of your question is, if you think of Search as a prompt that is not longer than one line, returning a bunch of different ranked results, as opposed to just telling you the right answer or something.”
27 / prediction
“As I think about the AI race in 2026, one thing that strikes me is Google has for so long had speed as the place it tries to differentiate.”
28 / uncertainty
“If you actually talk about all these rules, I don't know about SOC 2 in particular, but for example, a lot of compliance regimes have this notion of doer and approver being separate for something.”
29 / evaluation
“I've heard more absurd founding myths. I think you could just go for it.”
30 / evaluation
“Yeah, I think what you're saying is there's a strategy component to how should we be doing things, and then there's an hourly labor component to compliance, which is like, "Oh, we did 10 times as many sales.”
31 / evaluation
“The joking reference that everyone makes is they talk about competition from Claude Code for software products is, "You're not just going to vibe code your X in a weekend." But obviously, something like SOC 2 is actually the kind of thing that a Lens or coding agents are good at working with because there's just so much training data out there, and it's a codified set of rules.”
32 / evaluation
“Again, it naively feels like you will have a similar effect with compliance as we had with IT, where the profession very much stays around. It actually gets more skilled rather than… I think the stuff we do in IT is harder than the basic IT, the 10-person company would have done.”
33 / prediction
“It feels like the data you have of anonymized prior audits is an incredibly powerful network effect that cannot be replicated because it doesn't exist in the public interest.”
34 / evaluation
“What's going on there? As in, we think society cares, society should care. It's valuable to not lose this data, and yet it does not seem to impair what investors deem to be the terminal value of the company.”
35 / preference
“Compiling that rule book into the steps that are actually actionable for me, because I am not a farm, and so all the farm parts of the rule book don't apply to me.”
36 / evaluation
“That's generally… Obviously, there's lots of sexy stories of people who dropped out of college to start something. That's generally a bad time because you talk to university students, often, their ideas for companies are pretty half-baked.”
37 / prediction
“The other thing that feels like it's changing in this ecosystem is that the costs of having data breaches are going up because Europe, in particular, is getting very strict about notifications.”
38 / prediction
“I feel like you could have an opinion on this because we have filled out a lot of security questionnaires at Stripe, and I think we'd be very happy if the machines could take over from here.”
39 / evaluation
“LLMs are good at text or tokens, specifically, and obviously perform best at domains that have some single corpus of text they can work on, like coding, where it's very helpful that everything was just textual already.”
40 / uncertainty
“You see one of those flatbed trucks with just a bunch of stuff piled in it, and you're driving behind it? I don't know.”
41 / evaluation
“I think of a simple view of end-to-end being pixels go in, and car actions come out, which may be a bit of an oversimplification.”
42 / prediction
“What will that convergence look like? Because we're going to eat it from both sides.”
43 / belief
“Sure, but that could just be like a handy thing, whereas again, I think with social media, the candidates are different, the debates are different.”
44 / belief
“I think CEOs of public companies would say it is not always possible to choose to ignore it.”
45 / belief
“Where, I think people don't think so much about this dynamic, but for a sports bookie, the best possible punter is someone who is kind of unsophisticated, bets on, like, their home soccer team's game.”
46 / belief
“I think what Matt's getting at is like, who is a market maker on Kalshi? There's all these Jane Street conspiracy theory memes.”
47 / evaluation
“There is also, when you're an exchange like this, you have to spin up market making. And in the end, the New York Stock Exchange doesn't have to think too much about market making because just the economic incentive is there.”
48 / evaluation
“Of course, now we're building that because it's much more relevant in the agentic world.”
49 / belief
“Software engineering, I think we clearly are seeing a lot of AI productivity gains.”
50 / belief
“I think Nikita Bier tweeted recently that all of eng, product, and design at Twitter is 50 people.”
51 / belief
“I agree with you. I'm excited for not having to look at the screen for as many things for a variety of reasons.”
52 / belief
“We talked about this a bit in our annual letter in the context of agentic commerce, where, again, I think people are trying to pitch too much of the end state of fully autonomous, the robots just choosing a few.”
53 / evaluation
“Obviously, good companies did this before AI, continuous process improvement, and it feels like that is the best thing to do.”
54 / belief
“I agree. It's very blurry. It's so interesting. You were on the Twitter board during the super interesting takeover battle with Elon Musk.”
55 / belief
“I think a lot of the economy is actually white-collar knowledge work, not coding.”
56 / belief
“Similarly, I think Patrick has wanted for the longest time in Stripe is the ability to just SSH into your Stripe account.”
57 / recommendation
“We can give you an address that you can give to your customers, and they can mail checks to it, and we will turn it into digital money, and the fact that a bunch of atoms and an envelope going through the postal system were involved, you can forget about those details.”
58 / evaluation
“I think what you're doing is allowing for some manner of air support to just be much more cost-effective and available to more officers.”
59 / prediction
“I think you tend to see structurally in these smaller… I mean, it's a large market in total, but where there's a finite universe of buyers, the distributional advantages are very powerful.”
60 / belief
“I was curious about the tape actually means. It feels like… When I think about AI predictions, one thing I'm really struck by is how, still in 2026, every time you open a chat window, it's contextless.”
61 / belief
“I think I remember that being quite like the classic manufacturing throughput problem.”
62 / evaluation
“I don't know if they've talked about this stuff publicly, but you know that their internal metrics similarly show that the faster the product page loads, the more people buy it.”
63 / prediction
“Exactly, the repair thing, it feels like, can be solved, because also, I think part of the bet, part of Elon's claim, is that we will just be so power-limited that you have no option but to go to space.”
64 / commitment
“I will posit that many networks have been upgraded in place, but somehow the loose network of businesses paying each other via PDF invoices has proven very resistant to in-place upgrades.”
65 / belief
“Within a business, human time is incredibly expensive. I think the lean companies got this right and eliminated the bottlenecks there.”
66 / evaluation
“Yes. So you've talked a lot over the years about aggregation theory and really popularized this idea where pre-internet, often power would live with the supply, whereas on the internet, because of the different marginal cost dynamics and things like that, power will rest with the demand aggregators.”
67 / evaluation
“I see. So I mean famously, yeah, the restaurant economy and places like Taipei would have been really good, but it's gotten worse because people are eating in more with Uber Eats and stuff like that.”
68 / belief
“I think some skepticism is triggered by people pitching a very far end state with a lot of agentic autonomy.”
69 / belief
“We're already seeing it and like in the early usage of the ChatGPT buying experience, I think that's one of those super cool features.”
70 / belief
“I agree there’s kind of a knee-jerk skepticism of ads. Look, I'm a YouTube Premium subscriber.”
71 / belief
“I found that book much better than his other one that everyone reads, Stranger in a Strange Land.”
72 / belief
“Whereas actually, I think when you look at it, Tesla’s had a very consistent and internally promoted executive bench over the past few years.”
73 / evaluation
“One of my favorite books about accounting is the End of Accounting, which talks about how GAAP is basically poorly suited to this day and age.”
74 / evaluation
“Veggies as well. I think the local stuff will be better than the long supply-chain stuff.”
75 / evaluation
“How do you get people using the product and then how do you make it better when you’re using the product? And when we started Stripe, we were very much building stripe in a single-player mode where you have your Stripe account and the fact that other people use Stripe is, well, they didn’t at the time.”
76 / preference
“Yeah, I think maybe also, you’ve probably picked up on this dispositionally, we’re just not naturally drawn to pre-announcing products before they’re anywhere close to—we like to do a thing and hopefully we get it right.”
77 / prediction
“No, I think we will make a lot of progress there. It feels like many things are coming together.”
78 / evaluation
“I think there’s a general view that the economics of US agriculture are really hard and it’s challenged from a labor point of view.”
79 / prediction
“” But when people have money in crypto, they will store it in Coinbase, or in Binance, or what have you. And so our view is that for whatever job is being done, there will be a whole bunch of other counterparties that we are going to integrate with and work with.”