Pedro M.

Today we’re releasing our biggest product yet… The first people search API that lets you nest and combine filters in virtually unlimited ways, so you can actually search the way you think. Here are some examples of what you could search for with the new API: - Find founders of fintech companies that were founded in or after 2024 who were software engineers at Brex, Ramp, PayPal, Revolut, or Stripe for at least two years. - Identify senior professionals with more than 10 years of experience who left Google, Meta, Amazon, Microsoft, or Apple and joined growth-stage companies (50-100 employees) in or after 2023. You could have done all of this with our previous APIs (or any other b2b data API) but you’d have to run multiple calls with different filters and use a combination of company and people enrichment APIs to get accurate results. That works if you’re happy exporting long lists and cleaning them manually. But if you’re building real workflows and products, your needs are probably different: - You want your first query to be the only query you run. - You need one clean list, not multiple lists and the headache of filtering out what you actually need. - You want your search logic to match the way you think, not the way the API limits you. - You want confidence that the search actually found everyone you care about. So we spent the last few months listening to customer pains and building a search that finds only the people you want. Here’s what’s different: 1. Increased the number of search filters 3x from 20 to 60: More filters including specific job titles at present or past companies, skills, specific start and end dates in present or past companies and more. 2. Real logic with nesting: Added AND/OR logic and nesting, so you can combine filters in any way to zero in on exactly the person you’re looking for. 3. Stronger operators: Use in / not_in to include or exclude sets, and greater than, less than or equal to operators on numeric & date fields (experience, headcount, start/end dates, etc). 4. Lower latency: The response time is down to less than 10 seconds, which is 90% less than our current Search API. 5. ~30× cheaper: Runs on our own database which is updated monthly making it significantly cheaper than our current Search API. This is one of the launches I’m most excited about because it is the first truly precise person search API for B2B in the market. If you want access to the API, drop a comment or DM me.

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Every once in a while the paradigm shift we're seeing with AI comes into sharp focus for me. Today was one of those moments when Pedro, one of our brilliant engineers, demoed the internationalization features he's been building. If you've every had to deal with internationalization you know how painful it can be. We had a non-trivial consumer-facing product translated into 3 languages in a week. Pedro subsequently built an entire translation management console that lets us auto-translate to any language (seen below is a non-validated first pass in Hangul) and then included a human-in-the-loop feature to effectively crowd source refinements. We're using AI for the translation but also as a coding assistant and UX designer to deploy features like this that once wouldn't have be worth the effort.

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OpenAI just launched Instant Checkout inside ChatGPT. Smart tech. But will anyone actually use it? Ask AI. Get a product. Pay. Done. All inside ChatGPT. Users don’t open ChatGPT to shop. So Instant Checkout may need a real shift in user behavior to become a killer feature. Otherwise, it risks being just another demo. Still, the potential is hard to ignore. If users adapt and adopt, this could be transformative: ↳ ChatGPT could become a commerce agent, not just an advisor ↳ Billions of shopping queries already run through it ↳ Merchants could get new distribution But there’s a trust gap. Agent trust will have its own user journey. Without that layer of trust, agent-led commerce cannot scale. We’ve seen commerce bots before. This one is smarter. But will people use it? Only time will tell... #AI #ChatGPT #AgentEconomy #Ecommerce #TrustLayer #ProductDesign

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🚀 Meet the First AI Platform for Incubators & Accelerators Most incubators still rely on forms and Excel sheets to review thousands of applications manually - wasting weeks and missing top startups in the noise. That changes today. ⚡ DeepFlows is the first AI-native platform built to automate: 🌐 Startup SOURCING (optional, from our global founder network) 🧠 AI-powered SELECTION (YC / a16z-style criteria) 📄 Auto-generated 1-pager teaser for every startup 🧩 Investor matching w/ 45k professionals to SUPPORT selected startups 🔄 Collaboration between teams (incubators, startups, investors) 💰 Revenue-sharing from non-selected startups In short → less admin, better selection, new revenue streams. We’re already live with programs in the U.S. and UAE - and expanding fast. 💡 If you run or work with an incubator or accelerator, we'd love to hear from you! #AI for #Incubators #Accelerators #VCStudios

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Just came back from 𝗦𝘁𝗿𝗶𝗽𝗲 𝗧𝗼𝘂𝗿 𝗡𝗲𝘄 𝗬𝗼𝗿𝗸 𝟮𝟬𝟮𝟱 - tons of takeaways on the future of payments, AI, and global money movement. 𝐓𝐨𝐩 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠𝐬: 🤖 AI-native commerce is here: purchases directly inside ChatGPT via the Agentic Commerce Protocol (ACP) + shared payment tokens. New channel, real conversion. 💹 Conversion compounding: Adaptive Pricing localizes prices globally (avg +17.8% cross-border revenue), Link wallet scale (200M+ users), and best-in-class BNPL via Klarna. 🍎 Apps without the 30% tax: Stripe Managed Payments ("MOR") + app-to-web checkout preserves conversion while slashing fees 🥷 Fraud fights back with AI: Stripe’s payments foundation model + Radar improved large-merchant attack detection to 97%, added free-trial abuse protection, off-Stripe risk scoring, and adaptive 3DS. 📈 Billing for AI-era products: Hybrid subscriptions + usage, real-time credit burn-down, and a Token Billing API that auto-adjusts to LLM cost swings. 🚀 Platforms leveling up: New AI-powered analytics, Stripe Verified controls, IC+ pricing, plus capital/issuing to unlock new revenue lines. 🌏 Money management rethought: Multi-currency balances by default, local account details globally, pay-by-email, instant virtual cards. 🪙 Stablecoins going mainstream: Recurring stablecoin payments, Bridge orchestration, and Open Issuance to launch your own stablecoin (keep the yield). Phantom’s “Cash” is a standout example. 📒 Big picture: AI agents, stablecoins, and programmable finance are reshaping how we sell, get paid, and manage money. The companies that adapt fastest will win. If you’re exploring any of the above (agentic commerce, app monetization beyond Apple fees, AI usage billing, or stablecoin strategy), happy to compare notes.

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When thinking about how to scale a company, I find it helpful to use a tool I call the Market Box. Like a normal box, the Market Box has 6 sides that define a footprint in a market. When a company starts out, the first challenge is to reach product-market fit. For product-market fit, you work on the product to make it fit a market, but which market? The 6 sides of a Market Box are:  1. Market breadth: addressed verticals 2. Market reach: addressed sectors 3. Go-to-market approach: e.g., direct or indirect, OEM, PLG, marketplace 4. Geographies:, e.g., London, UK, Europe 5. The problem you solve, e.g., payroll, payments 6. The market tier you address, e.g., Enterprise customers, SMB Each of these sides can be of different sizes or not there at all. For instance, a company may choose to focus on the UK (small Market Box side) or the entire world (no Market Box side). As you scale, you must enjoy Market Pull. Market Pull is when you grow without having to pay too much for your growth, e.g., you benefit from a superior product at the right price point, from partnerships, from integrations with growth products, from your reputation, etc. When product-market fit is achieved for the initial Market Box, this box often must have all 6 sides in place with relatively small sides. One measure of product-market fit is whether Market Pull is in place or how easy it is to acquire new customers (ROI from sales and market efforts, sales efficiency). When companies run into issues with scaling, seen by a too low sales efficiency; lack of Market Pull, it is very often because their Market Box is too big for them to enjoy the benefits of Market Pull. If this is the case you need to zoom in by making one of the Market Box sides smaller. After you regain Market Pull you can make the Market Box side bigger again or remove it completely. I call it to zoom out/zoom in when you make a Market Box side bigger/smaller. The shape of a Market Box for a European company is very different from a US company and this is exactly why it is much easier to scale in the US. For most markets in Europe, you have to zoom out relatively early, much earlier than in the US and every time you zoom out you risk losing Market Pull. When you compete against someone who successfully addresses a bigger Market Box than you, many times the best approach is to go deeper with the problem(s) you address. All of this is why it is so difficult to scale a company in Europe. One solution for Europe is to have more capital available to fund expanding Market Box sides 1, 2 3 and 4. Most of the VC and PE funds addressing this part of the scale up journey are relatively small and they cannot think big enough when they support companies. To address this either requires VC/PE market consolidation to make the funds bigger or more syndication between the funds such that they can pool resources and think much bigger when they have a winner on their hands.

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