John Collison

@bscholl Hot tub

Filming the inaugural episode of Boom Turbine Tuesdays. Trivia question: what’s that part behind us?

.@Collision is bullish on two types of people: high-agency individuals and double majors. "There are two categories of people I would be super bullish on right now and I think will do incredibly well over the next 10-20 years. First, high-agency people. The people at Stripe who have been talking to customers and know exactly what we should do. It's the people who have that pep in their step and want to go make Stripe better. They are so much more empowered thanks to AI." "The second is double majors. I think if you understand software and understand finance, or if you understand software and understand marketing, you now can go massively improve the entire marketing funnel for your company. Now, one person can do what would have taken 20 people dredging through all these systems." "Charlie Munger talked about the importance of being multidisciplinary and multidisciplinary thinking. He thinks getting a functional understanding of many disciplines is not that hard. You can just go read the books now or you can talk to your AI about it. I think multidisciplinary thinkers are going to do incredibly well."

At Stripe Sessions, we showed how we think agentic commerce will often happen behind the scenes in the course of producing other final products. Here, we show our Claude Code using MPP and @tempo to buy a dataset from @alpha_vantage in the process of generating a research report for me on AI energy usage.

We've been thinking a lot at Stripe about the Coasean lens on AI: - The obvious near-term effect is reduced transaction costs within companies: shared context, systems of record, aligned incentives etc. - But inter-company transaction costs also reduce sharply: agents are great at discovery, make it trivially easy to integrate; make contracting much more straightforward; agent-to-agent commerce. - On net, we think second effect bigger in medium term: fewer people per firm, more output per firm, just more firms, and more coordination happening through market-like mechanisms

Your honour, I think this should be allowed.

I spoke to @EdLudlow at @business from Stripe Sessions about how the economy is replatforming around AI. bloomberg.com/news/videos/20…

We just announced a large raft of improvements at @Stripe Sessions. My meta reflections: • It feels that the entire economy is replatforming right now. • Many charts at Stripe are inflecting in quite dramatic ways. What GitHub recently reported for commits we are seeing in economic activity (such as new company formations). • It is increasingly clear that agents will be responsible for most transactions in the not overly distant future. • Stripe was always developer-centric, but AI is making developer-centricity strategic in a new way: agents are even hungrier for good DX than developers themselves are. • Things that we’re launching are increasingly network products at heart. (Instant transfers between Stripe businesses, new kinds of fraud prevention with Stripe Radar, stablecoin payouts to anyone with Link.) "How can we turn Stripe's economies of scale into user benefits?" is increasingly the relevant question. • Between Privy, Bridge, Tempo, and Stripe’s core capabilities, we’re now doing a lot in stablecoins/crypto, and companies like DoorDash, Ramp, Meta, and Klarna are using our crypto stack to deploy meaningful new functionality in production. “But where’s the production use?” is rapidly becoming stale when applied to crypto. • After more than a decade of building, we seem to have hit some kind of critical mass of core platform capabilities such that building new things now feels easier and faster than before. (AI also helps.) We announced Stripe Treasury last year (originally called Financial Accounts); since then, we’ve added multi-currency support, global payouts, card issuance and rewards, and a bunch of other sophisticated functionality. By the end of this year, Treasury will support 15 more currencies and be available to businesses in 160 countries. On the launches themselves, a small selection that I thought were cool, though this is really just a subset: • The @Link AI wallet. Point your agent to github.com/stripe/link-cli and ask it to make purchases on your behalf with secure single-use tokens. (To test it, I asked Claude Code to buy a small gift for me yesterday. It purchased HTTPZine on Gumroad.) • New payment methods for Link, including Pix (largest payment method in Brazil) and UPI (largest payment method in India). We’re also adding stablecoin support to Link (which I think will be huge if we execute well). • We’re adding a lot of new Machine Payments Protocol functionality, including micropayment and recurring payment support. • We announced Checkout studio: a sophisticated dashboard for managing your checkout flow, including things like transaction replays and A/B tests. Today this tends to require a lot of fussy edits to production code. • Adaptive Pricing (which automatically localizes the price and currency that customers see) now supports subscriptions. We’ve seen pretty huge (4–5%) conversion rate improvements after enabling it — customers really like paying in their home currency. • New Stripe Terminal reader (the T600) with a customer-facing screen that can run native apps, plus support for 15 new international markets for Stripe Terminal. • General availability for Stripe Managed Payments, our merchant of record solution. (Natively handles tax, disputes, fraud.) Maybe sounds a bit arcane, but it’s one of those iykyk products. It saves a lot of schlep. • Fraud is a *much* bigger priority for customers than it was 2 years ago (AI makes fraud easier + unlike software, tokens can be resold), so we’ve been extending Stripe Radar to support things beyond payments fraud: free trial abuse, multi-account abuse, pay-as-you-go abuse. Early results are extremely positive. We also announced Stripe Signals — new scoring APIs for customers, businesses, and other objects, not just payments on and off Stripe. • Usage-based billing is also becoming the de facto business model of the AI era, and we launched a bunch of new pricing models in @getMetronome and features like low-balance alerts, automatic credit top-ups, and multidimensional pricing structures. • We showed streaming payments built on @Tempo and Metronome — track usage and get paid the instant value is delivered. Hard to predict, but I think this could be big. (Why wouldn’t you want to get paid as costs are incurred?) • We added automatic US tax filing in Stripe Tax. • We announced Stripe Database -- a hosted PostgreSQL database with all of your Stripe data, updated in real time. Read-only to start but we’ll make it read-write. • Stripe Workflows are now GA. • We showed Stripe Console, a full agentic execution environment built directly into the Stripe Dashboard. It’ll happily write code and use tools to answer your questions. • We previewed custom objects: model your business data directly in Stripe, with custom objects, typed fields, and relationships. • As mentioned above, Stripe Treasury accounts will support storage in 15 currencies by the end of the year. And instant/free(!) transfers between US Stripe businesses. • You can use a Stripe card with your Treasury balance and get 2% cash back on purchases. • We’re massively expanding our Global Payouts coverage -- soon 100 countries with fiat rails and 160 with stablecoins. • Atlas companies can now raise money directly within Stripe. • We launched the platform growth studio, which uses Stripe’s network data to generate specific recommendations for optimization/growth. • We announced the Stripe Managed Risk API — platforms can outsource risk handling to Stripe while maintaining full UI/UX control. • Connected accounts now benefit from networked onboarding, which hugely increases conversion rates. • We’re launching Treasury for Platforms. Connected accounts can get spend cards with just a few lines of code. (Plus cash rewards, cash acceptance, check acceptance, real-time payments…) • We announced Issuing for agents: easily create cards for agents. But that’s really just a subset of a subset. (See stripe.com/roadmap for more.) The Stripe team is cooking! And if you’re interested in building the economic infrastructure for this new world, we’re hiring.

Stripe really cooked with Link CLI. Look at how easily I can get my OpenClaw agent to buy me some coffee beans.

Announced today: @Meta is adding support for stablecoin payouts to creators via @Link wallets, powered by @Stripe and settled on Tempo. Rolling out in Colombia and the Philippines, expanding to 160+ markets.

Starting today, agents can now be Cloudflare customers. They can create a Cloudflare account, start a paid subscription, register a domain, and get back an API token to deploy code right away. cfl.re/4sY0Uxn

Increasingly, the best part of using Stripe is the millions of other companies using Stripe. How we use the network improve the product has been a big focus this year. Here are some of the networked ships from Stripe Sessions this week: Fraud. Radar is trained on signals from across Stripe, which now just sees most internet users and most payments. If a bad actor signs up for your product, we've generally already seen their device fingerprint, their email, or their card behavior—on someone else's business. For one AI company, 80% of the bad actors Radar caught had sailed right through their prior anti-fraud provider. As Stripe grows, the better every business on Stripe is protected. Link started as a way to save your payment details and has grown into a network of more than 250 million consumers. Link now stores stablecoins, powers agent wallets, and drives a 5% conversion lift for returning customers. Whenever a user signs up with Link on one business, every other Stripe business benefits the next time that customer checks out. Money movement. It turns out that Stripe businesses pay each other 4.8 million times a day. So we built instant, free transfers between Stripe Treasury accounts. Intelligence. 1.6% of global GDP now runs through Stripe; over 70 trillion data points last year. We've historically used that data to power our own products (Radar, authorization optimization). But now we’re putting it directly in your hands with Stripe Signals. Send us a customer, a transaction, a business—on or off Stripe—and we return a real-time risk score and explanation. Here's everything we announced this morning: stripe.com/blog/everythin….

Introducing Link agent wallet. Let your agents spend on your behalf. Your payment credentials are never exposed. You approve every purchase. link.com/agents

For our last Cheeky Pint episode this season, @evanspiegel joins me to discuss the "crucible moment" at Snap. We cover the shift from smartphones to AR glasses, why he thinks VR is antisocial, how creative culture at Snap works, and why Norway is Snapchat-obsessed.

Tomorrow on Cheeky Pint: @evanspiegel on Snap's evolution from smartphones to spectacles.

Spotify: open.spotify.com/episode/5j8Hu1… Apple Podcasts: podcasts.apple.com/us/podcast/the… YouTube: youtu.be/VwvrZphtg2I Substack: open.substack.com/pub/cheekypint…

Whenever I catch up with @t_xu of @DoorDash, I enjoy how encyclopaedic his knowledge of the restaurant industry is. In this episode we get into the economic forces driving the industry, along with a demo of Dot, their foray into autonomous delivery. 00:00:25 Why did DoorDash win? 00:10:50 China 00:17:10 Restaurant trends 00:27:59 Loyalty 00:30:40 Stripe Issuing 00:44:09 Delivery modalities 00:51:11 Fraud 00:58:32 New products 01:13:26 Dot

Tomorrow on Cheeky Pint: @t_xu of @DoorDash

Spotify: open.spotify.com/episode/7vMJKS… Apple Podcasts: podcasts.apple.com/us/podcast/the… YouTube: youtu.be/zA1zdqIYER4 Substack: open.substack.com/pub/cheekypint…

Mati Staniszewski and his team at @ElevenLabs have built amazing text-to-speech and speech-to-text models, and are now expanding into voice agents. In this episode of Cheeky Pint, I asked why one of the longest-promised UIs in computing ("Open the pod bay doors, HAL" was 1968!) has been so slow in arriving. Along with lots of details on how voice AI actually works at a technical level. 00:00:27 How audio models work 00:08:52 ElevenLabs business model 00:17:50 The conversational Turing Test 00:21:01 Link by Stripe 00:26:02 Cascaded vs speech-to-speech 00:31:53 Universal translation 00:51:41 Designing an AI-native org