Last week, @bernhardsson (Founder & CEO, @modal) announced a $750M Series D. I sat down with him the prior week to discuss a ton of stuff about the business. We got into: -why open-source models made fine-tuning a lot less necessary -how Modal's team grew 4x in a year and could hit ~700 people next year -why the frontier labs have the same business model as music artists and much, much, more… Enjoy! Timestamps: 0:00 What Modal does 1:25 From @Spotify to building @modal 4:19 Founding before the generative AI boom 7:43 First customers and fundraising 10:00 Building for inference and autoscaling 13:21 Where Modal gets GPU capacity 15:39 Renting vs. owning infrastructure 19:45 The risk of GPU prices falling 24:18 Is AI demand infinite? 28:25 What Modal can learn from neoclouds 30:26 GPUs as an asset class 31:55 Modal’s products: functions and sandboxes 36:03 The case for smaller training workloads 41:21 How agent sandboxes are changing 46:48 @AnthropicAI and sandbox security 49:29 Using agents to test security 52:51 Developer experience in the age of agents 57:45 What Modal’s forward-deployed engineers do 59:55 Modal’s approach to product management 1:03:29 Optional code reviews and engineering culture 1:05:56 Cloud, on-prem and bring-your-own-cloud 1:09:25 Capacity, fundraising and growth 1:13:07 Scaling the team 1:17:28 Erik’s tweets: ephemeral sandboxes 1:18:31 The problem with rectangular GPU contracts 1:21:20 Inference providers vs. model builders 1:23:25 Where models improve next

Services are the future. Exactly 1 month ago, @LeoMehr launched @tryramp's services motion. Why? They have structural advantages: → 𝐃𝐚𝐭𝐚: 70k customers. $200B+ in annual payments, years of vendor data, millions of transactions and bills monthly. → 𝐌𝐨𝐧𝐞𝐲-𝐦𝐨𝐯𝐞𝐦𝐞𝐧𝐭 𝐩𝐫𝐢𝐦𝐢𝐭𝐢𝐯𝐞𝐬 𝐚𝐧𝐝 𝐩𝐚𝐫𝐭𝐧𝐞𝐫𝐬𝐡𝐢𝐩𝐬: Global money movement rails, partnerships with banks, Visa, Stripe, etc. → 𝐀𝐧 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐥𝐚𝐲𝐞𝐫 𝐨𝐧 𝐭𝐨𝐩: fraud detection from hundreds of millions of expenses, PO-to-invoice matching, state-of-the-art OCR, and fine-tuned models for accounting coding, spend routing, policy review, etc. Last week, I sat down with @LeoMehr to talk about this and much, much more. Some of my favorite parts (link to full episode in comments):

Forward Deployed Engineering is the most critical ingredient for Enterprise AI adoption. It’s why the most important companies on the planet are investing so heavily into it. That’s why we put together the Forward Deployed track at this year’s AI Engineer World’s Fair on Tuesday, June 30. Learn about the current state of the industry and where its headed from the people and companies leading the charge. Everything it REALLY takes to deploy agents in production and transition our economy to the new world order Don’t miss it :) (more details and link in comments) ↓