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AI has changed software engineering more in the last 3 years than it has changed in the previous 30. What’s needed is not a debate about whether it’s going away—instead it’s a serious discussion about its future: What are the new primitives, techniques, and best practices for software engineering...

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Dan Shipper 📧

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SaaS isn’t dead, it just needs to become agent-native. Linear (Linear) is a great example of how: They pivoted the product to be used by both humans and agents, and that has made them one of the premier software tools in the agent-native era. I had Linear’s cofounder and CEO Karri Saarinen on Every 📧's AI & I to talk about how a product management tool for human software developers became an agent-native tool—and how Linear’s trajectory reveals a bright future for SaaS businesses: - Speed means decisions matter more, not less. AI makes it easy to have an idea and build it without considering whether its existence is justified. When ChatGPT was released, SaaS companies were launching their own chatbots left, right, and center. Instead of jumping on the bandwagon, Linear stopped to consider whether the application was useful. (It wasn’t.) - Just because the technology has changed doesn’t mean your mission should. Karri attributes Linear’s success to never losing sight of what matters: helping teams develop great software. Instead of chasing trends, Linear focused on understanding how AI was impacting its customers’ workflows—and updating its product accordingly. - Agents are now first-class users. Linear never tried to change what it was or did well; it just expanded the user base. Companies can now kick off agents inside Linear, manage them, and track what they're working on alongside the humans on the team, which explains why Codex, Coinbase, and Brex all run their agents on Linear. This is a must watch for anyone interested in how an agent-native SaaS company operates. Watch below! Timestamps: Introduction and how Every first discovered Linear: 00:00:39 Why Linear waited to ship AI features instead of rushing to chatbots: 00:02:00 Linear's agent platform and becoming the system that guides AI agents: 00:05:06 Why "SaaS is dead" is a simplistic narrative: 00:07:42 How Linear adopted AI coding tools internally: 00:12:18 AI's impact on product building workflows—speed versus thoughtfulness: 00:17:45 The value of conceptual work and thinking before shipping: 00:22:18 How AI is reshaping Linear's product strategy: 00:29:30 Demo: Linear's agent skills, shared context, and code review workflow: 00:37:18 The future of product development and the enduring role of human judgment: 00:47:48

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In the future, you’ll be able to accomplish a goal by just giving Claude an outcome and a budget. That’s the direction Anthropic is building in with its new Managed Agents features, announced at this week’s Code with Claude developer event. The basic idea: Claude, wrapped in a computer in the cloud, that you can spin up, scale, and manage as needed. Anthropic is taking on the infrastructure that kills most agent products, and making sure that it scales to meet the needs of agents running 24/7. On this week’s AI & I from Every 📧, I talk with Angela Jiang (Angela Jiang), head of product for the Claude platform, and Katelyn Lesse (Katelyn Lesse), head of engineering for the Claude platform, about what Anthropic is building and what it takes to make agents reliable in production. We get into: - Why the "build a generic harness, hot-swap any model behind it" playbook is already outdated. Angela points to eval data on Memory where the same task across different harnesses performed drastically differently. - The infrastructure wall every team hits in production—and why Katelyn thinks “my sandbox died and took the agent with it” is the real reason internal agents don't ship. - Why Anthropic is so bullish on using file systems and skills within Claude, including Angela's argument that those early design choices can compound for years. This is a must-watch for anyone trying to take an agent past the demo and into production. Watch below! Timestamps: How the Claude platform evolved from API to agents: 00:01:48 The primitives that make up Claude Managed Agents: 00:04:09 Why the harness and the model are becoming a single unit: 00:10:37 The infrastructure wall that kills most agent projects in production: 00:18:49 Why team agents need a different shape than individual productivity tools: 00:24:49 How Anthropic's legal team uses an agent to review marketing copy: 00:26:36 Using multi-agent orchestration for advisor strategies, adversarial pairs, and swarms: 00:34:24 How to measure agent success with outcome and budget as the end state: 00:35:50 What the platform looks like a year from now, when Claude writes its own harness: 00:39:11
43:20

In the future, you’ll be able to accomplish a goal by just giving Claude an outcome and a budget. That’s the direction Anthropic is building in with its new Managed Agents features, announced at this week’s Code with Claude developer event. The basic idea: Claude, wrapped in a computer in the cloud, that you can spin up, scale, and manage as needed. Anthropic is taking on the infrastructure that kills most agent products, and making sure that it scales to meet the needs of agents running 24/7. On this week’s AI & I from Every 📧, I talk with Angela Jiang (Angela Jiang), head of product for the Claude platform, and Katelyn Lesse (Katelyn Lesse), head of engineering for the Claude platform, about what Anthropic is building and what it takes to make agents reliable in production. We get into: - Why the "build a generic harness, hot-swap any model behind it" playbook is already outdated. Angela points to eval data on Memory where the same task across different harnesses performed drastically differently. - The infrastructure wall every team hits in production—and why Katelyn thinks “my sandbox died and took the agent with it” is the real reason internal agents don't ship. - Why Anthropic is so bullish on using file systems and skills within Claude, including Angela's argument that those early design choices can compound for years. This is a must-watch for anyone trying to take an agent past the demo and into production. Watch below! Timestamps: How the Claude platform evolved from API to agents: 00:01:48 The primitives that make up Claude Managed Agents: 00:04:09 Why the harness and the model are becoming a single unit: 00:10:37 The infrastructure wall that kills most agent projects in production: 00:18:49 Why team agents need a different shape than individual productivity tools: 00:24:49 How Anthropic's legal team uses an agent to review marketing copy: 00:26:36 Using multi-agent orchestration for advisor strategies, adversarial pairs, and swarms: 00:34:24 How to measure agent success with outcome and budget as the end state: 00:35:50 What the platform looks like a year from now, when Claude writes its own harness: 00:39:11

Dan Shipper

66,862 Aufrufe ‱ vor 4 Monaten

One line from Prasanna Sankar has stayed with me: "You're not helping AI anymore. You're getting in the way by being in the way." That's exactly why he's building Vorflux Not another AI coding assistant. His vision is an autonomous AI software engineer that can build software with minimal human involvement. Coming from someone who was India's #1 competitive programmer, helped build Rippling into a $15B company, and once turned down Facebook's $100M acquisition offer, it's a perspective worth paying attention to. In this conversation, we go deep on: ‱ Why AI has already surpassed humans at software engineering. ‱ Why tools like Cursor and Claude Code are only the beginning—and how Vorflux is thinking differently. ‱ Why the engineer of the future becomes a "builder." ‱ The story behind building Rippling and starting over from scratch. ‱ Why he turned down Facebook's $100M acquisition offer. ‱ Why he believes we're moving toward zero-employee companies. ‱ What humans will be uniquely valuable for in an AI-first world. One of the most thought-provoking conversations I've had on AI and the future of software. Full conversation is now live on the 1947 Rise Podcast. Link in comments Prasanna S Vorflux
1:21

One line from Prasanna Sankar has stayed with me: "You're not helping AI anymore. You're getting in the way by being in the way." That's exactly why he's building Vorflux Not another AI coding assistant. His vision is an autonomous AI software engineer that can build software with minimal human involvement. Coming from someone who was India's #1 competitive programmer, helped build Rippling into a $15B company, and once turned down Facebook's $100M acquisition offer, it's a perspective worth paying attention to. In this conversation, we go deep on: ‱ Why AI has already surpassed humans at software engineering. ‱ Why tools like Cursor and Claude Code are only the beginning—and how Vorflux is thinking differently. ‱ Why the engineer of the future becomes a "builder." ‱ The story behind building Rippling and starting over from scratch. ‱ Why he turned down Facebook's $100M acquisition offer. ‱ Why he believes we're moving toward zero-employee companies. ‱ What humans will be uniquely valuable for in an AI-first world. One of the most thought-provoking conversations I've had on AI and the future of software. Full conversation is now live on the 1947 Rise Podcast. Link in comments Prasanna S Vorflux

Shiva Singh Sangwan

72,199 Aufrufe ‱ vor 1 Monat

Maths savant turned Cognition founder Scott Wu joins me to discuss their AI software engineer, acquiring Windsurf over a weekend, the Moneyball-ification of everything, math contests with Alexandr Wang in 6th grade, the future of independent coding tools, and why he thinks we already have AGI. Subscribe on Spotify, Apple Podcasts, and YouTube for future Cheeky Pint episodes. Timestamps: 00:00 Intro 01:13 Early life and maths competitions 03:47 Addepar job as a high schooler 05:43 Where are all the young founders? 08:45 Moneyball-ification of everything 11:42 Cognition’s AI software engineer, Devin 15:46 Essential and accidental complexity 17:59 How Devin works with enterprises 19:48 IDE productivity 21:56 Nihilist computer use argument 25:55 Benchmarking Devin 27:15 Market structure 30:32 Agent economy 37:21 Cognition’s team of founders 39:31 Jevons paradox and software 42:00 When will we see AI UIs? 45:52 “I think we have AGI” 47:03 Windsurf deal 52:37 M&A in AI 54:21 Cognition’s culture 55:48 Learning as a CEO 57:12 Scott’s information diet
59:36

Maths savant turned Cognition founder Scott Wu joins me to discuss their AI software engineer, acquiring Windsurf over a weekend, the Moneyball-ification of everything, math contests with Alexandr Wang in 6th grade, the future of independent coding tools, and why he thinks we already have AGI. Subscribe on Spotify, Apple Podcasts, and YouTube for future Cheeky Pint episodes. Timestamps: 00:00 Intro 01:13 Early life and maths competitions 03:47 Addepar job as a high schooler 05:43 Where are all the young founders? 08:45 Moneyball-ification of everything 11:42 Cognition’s AI software engineer, Devin 15:46 Essential and accidental complexity 17:59 How Devin works with enterprises 19:48 IDE productivity 21:56 Nihilist computer use argument 25:55 Benchmarking Devin 27:15 Market structure 30:32 Agent economy 37:21 Cognition’s team of founders 39:31 Jevons paradox and software 42:00 When will we see AI UIs? 45:52 “I think we have AGI” 47:03 Windsurf deal 52:37 M&A in AI 54:21 Cognition’s culture 55:48 Learning as a CEO 57:12 Scott’s information diet

John Collison

346,157 Aufrufe ‱ vor 1 Jahr

In the first episode of our new series Full Stack, Conductor CEO and co-founder Charlie Holtz takes us into the details of how he sets up his workflow for coding and managing AI agents. 00:00 – Building Conductor With Conductor 01:05 – Managing a Team of Coding Agents 02:39 – Do You Still Write Code? 04:17 – Charlie's AI Stack and Setup 05:48 – “Slop-free” Zones 07:25 – Don’t Let the AI Be Your Architect 09:15 – The Future of Cloud Workspaces 10:40 – Claude vs Codex 12:01 – Tokenmaxxing 14:17 – The Future of Human–AI Collaboration 15:07 – "Code Is Becoming Sawdust"
16:34

In the first episode of our new series Full Stack, Conductor CEO and co-founder Charlie Holtz takes us into the details of how he sets up his workflow for coding and managing AI agents. 00:00 – Building Conductor With Conductor 01:05 – Managing a Team of Coding Agents 02:39 – Do You Still Write Code? 04:17 – Charlie's AI Stack and Setup 05:48 – “Slop-free” Zones 07:25 – Don’t Let the AI Be Your Architect 09:15 – The Future of Cloud Workspaces 10:40 – Claude vs Codex 12:01 – Tokenmaxxing 14:17 – The Future of Human–AI Collaboration 15:07 – "Code Is Becoming Sawdust"

Y Combinator

156,937 Aufrufe ‱ vor 3 Monaten

BREAKING: Devin now writes ~95% of Devin's code Scott Wu (Scott Wu), CEO of Cognition says the abundance era of AI is real & coming soon.. FULL INTERVIEW Cog Stats: â€ș $2.5B raised, $26B valuation â€ș $500M+ run rate, up from $37M LY â€ș Customer usage is up 11x-12x in 6 months â€ș Total code shipped inside Cognition has grown 7x â€ș Devin writes ~95% of Cog's code, up from 89% at May Series D â€ș The entire Windsurf acquisition was negotiated over 1 weekend, ~40 people buying a 200 person company with $82M of ARR â€ș Goldman Sachs, Mercedes-Benz, Citi, Dell, Santander, NASA, the US Navy & the US Army all run Devin R I P : "The tokenmaxx era lasted from January to May of 2026, roughly." "I'm excited to have AI that allows me to spend all of my time & focus on the things that I care about & take care of the rest. I think the abundance era is real, & I think we'll be there pretty soon." Recorded 7 July 2026. On 23 July 2026 Cognition acquired Poke maker The Interaction Company 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Scott Wu, Co-Founder & CEO at Cognition (01:00) The Identity crisis of building Devin (01:42) How Cognition 7X-ed its output in 6 months (02:55) The Metric every AI company gets wrong (04:18) Cognition's 12x growth curve (07:46) The Windsurf acquisition (13:26) Scaling overnight: Cognition's hardest week (15:11) The strategy behind the integration of Cognition products (17:23) Cognition's M&A playbook (20:01) Why the DMV is Cognition's next big target (22:59) Why Cognition bet against AI centralization (25:09) Why enterprises refuse to bet on a single AI lab (28:32) Scott's honest take on Superintelligence (32:36) Is Silicon Valley losing its mind over the AI gold rush? (33:26) Devin's origin story (37:17) The question Scott thinks nobody's asking yet (39:59) Poker with Peter Thiel & Napoleon ? (41:24) Scott's vision for the next year
43:24

BREAKING: Devin now writes ~95% of Devin's code Scott Wu (Scott Wu), CEO of Cognition says the abundance era of AI is real & coming soon.. FULL INTERVIEW Cog Stats: â€ș $2.5B raised, $26B valuation â€ș $500M+ run rate, up from $37M LY â€ș Customer usage is up 11x-12x in 6 months â€ș Total code shipped inside Cognition has grown 7x â€ș Devin writes ~95% of Cog's code, up from 89% at May Series D â€ș The entire Windsurf acquisition was negotiated over 1 weekend, ~40 people buying a 200 person company with $82M of ARR â€ș Goldman Sachs, Mercedes-Benz, Citi, Dell, Santander, NASA, the US Navy & the US Army all run Devin R I P : "The tokenmaxx era lasted from January to May of 2026, roughly." "I'm excited to have AI that allows me to spend all of my time & focus on the things that I care about & take care of the rest. I think the abundance era is real, & I think we'll be there pretty soon." Recorded 7 July 2026. On 23 July 2026 Cognition acquired Poke maker The Interaction Company 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Scott Wu, Co-Founder & CEO at Cognition (01:00) The Identity crisis of building Devin (01:42) How Cognition 7X-ed its output in 6 months (02:55) The Metric every AI company gets wrong (04:18) Cognition's 12x growth curve (07:46) The Windsurf acquisition (13:26) Scaling overnight: Cognition's hardest week (15:11) The strategy behind the integration of Cognition products (17:23) Cognition's M&A playbook (20:01) Why the DMV is Cognition's next big target (22:59) Why Cognition bet against AI centralization (25:09) Why enterprises refuse to bet on a single AI lab (28:32) Scott's honest take on Superintelligence (32:36) Is Silicon Valley losing its mind over the AI gold rush? (33:26) Devin's origin story (37:17) The question Scott thinks nobody's asking yet (39:59) Poker with Peter Thiel & Napoleon ? (41:24) Scott's vision for the next year

Molly O’Shea

677,522 Aufrufe ‱ vor 1 Monat

This AI can read emotions better than you can. It was created by Hume (Hume AI) an AI research lab developing models that can read your face and your voice with uncanny accuracy. Their hope is that models that can read your emotions will help create AI that optimizes for human well-being. I sat down with Alan Cowen (Alan Cowen), the co-founder and CEO of Hume to talk about how all of this works: the science of emotion, AI that optimizes for human well-being, and more. Before starting Hume, Alan helped set up Google’s research into affective computing and got a Ph.D. in computational psychology from Berkeley. He's one of the bright lights in AI, and this was an incredible conversation. We get into: - What an emotion actually is - Why traditional psychological theories of emotion are inadequate - How Hume is able to model human emotions - How Hume's API enables developers to build empathetic voice interfaces - Applications of the model in customer service, gaming, and therapy - Why Hume is designed to optimize for human well-being instead of engagement - The ethical concerns around creating an AI that can interpret human emotions - The future of psychology as a science This is a must-watch for anyone interested in the science of emotion and the future of human-AI interactions. Watch! --- Timestamps: I tell Hume’s empathetic AI model a secret: 00:00:00 Introduction: 00:01:13 What traditional psychology tells us about emotions: 00:10:17 Alan’s radical approach to studying human emotion: 00:13:46 Methods that Hume’s AI model uses to understand emotion: 00:16:46 How the model accounts for individual differences: 00:21:08 My pet theory on why it’s been hard to make progress in psychology: 00:27:19 The ways in which Alan thinks Hume can be used: 00:38:12 How Alan is thinking about the API v. consumer product question: 00:41:22
56:12

This AI can read emotions better than you can. It was created by Hume (Hume AI) an AI research lab developing models that can read your face and your voice with uncanny accuracy. Their hope is that models that can read your emotions will help create AI that optimizes for human well-being. I sat down with Alan Cowen (Alan Cowen), the co-founder and CEO of Hume to talk about how all of this works: the science of emotion, AI that optimizes for human well-being, and more. Before starting Hume, Alan helped set up Google’s research into affective computing and got a Ph.D. in computational psychology from Berkeley. He's one of the bright lights in AI, and this was an incredible conversation. We get into: - What an emotion actually is - Why traditional psychological theories of emotion are inadequate - How Hume is able to model human emotions - How Hume's API enables developers to build empathetic voice interfaces - Applications of the model in customer service, gaming, and therapy - Why Hume is designed to optimize for human well-being instead of engagement - The ethical concerns around creating an AI that can interpret human emotions - The future of psychology as a science This is a must-watch for anyone interested in the science of emotion and the future of human-AI interactions. Watch! --- Timestamps: I tell Hume’s empathetic AI model a secret: 00:00:00 Introduction: 00:01:13 What traditional psychology tells us about emotions: 00:10:17 Alan’s radical approach to studying human emotion: 00:13:46 Methods that Hume’s AI model uses to understand emotion: 00:16:46 How the model accounts for individual differences: 00:21:08 My pet theory on why it’s been hard to make progress in psychology: 00:27:19 The ways in which Alan thinks Hume can be used: 00:38:12 How Alan is thinking about the API v. consumer product question: 00:41:22

Dan Shipper 📧

45,941 Aufrufe ‱ vor 2 Jahren

In this episode of the Lightcone Podcast, we sat down with Mukund Jha and Madhav Jha, the founders of Emergent - an AI platform that lets anyone build and ship production-ready software. In just eight months, users have created more than 7 million apps on Emergent, with the number doubling in just the last 45 days. We discuss how they built one of the most powerful AI coding agents, why they focused on non-technical users and what it's like building for a global audience from India. 00:00 - Intro 01:06 - What Is Emergent? 01:18 - Founder Backstory 02:09 - From AI Testing to General Coding Agents 02:52 - Getting Ahead of the Market 04:18 - The Pivot to Non-Technical Users 05:22 - Why Second Movers Can Win in AI 09:04 - Building for Production, Not Just Prototypes 18:21 - Live Demo: Building Apps with Emergent 24:40 - How Emergent Hires and Runs a Lean Team 29:04 - Is SaaS Dead? The Rise of Personalized Software 34:04 - The Future: Niche Apps, Solo Builders and AI Agency
39:32

In this episode of the Lightcone Podcast, we sat down with Mukund Jha and Madhav Jha, the founders of Emergent - an AI platform that lets anyone build and ship production-ready software. In just eight months, users have created more than 7 million apps on Emergent, with the number doubling in just the last 45 days. We discuss how they built one of the most powerful AI coding agents, why they focused on non-technical users and what it's like building for a global audience from India. 00:00 - Intro 01:06 - What Is Emergent? 01:18 - Founder Backstory 02:09 - From AI Testing to General Coding Agents 02:52 - Getting Ahead of the Market 04:18 - The Pivot to Non-Technical Users 05:22 - Why Second Movers Can Win in AI 09:04 - Building for Production, Not Just Prototypes 18:21 - Live Demo: Building Apps with Emergent 24:40 - How Emergent Hires and Runs a Lean Team 29:04 - Is SaaS Dead? The Rise of Personalized Software 34:04 - The Future: Niche Apps, Solo Builders and AI Agency

Y Combinator

107,806 Aufrufe ‱ vor 6 Monaten

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)
0:59

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

Rohan Paul

16,584 Aufrufe ‱ vor 3 Monaten