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⚫UNCANNY VALLEY: PERPLEXITY VS GOOGLE — THE WAR FOR THE FUTURE OF SEARCH BEGINS Special Guest: Aravind Srinivas Host: Dr Danish Search is dead. Agents are rising. Phones are getting smarter—without Apple or Google. Aravind Srinivas, CEO of Perplexity, lays out the future: AI-native assistants, ambient search, agent browsers,... and a war for the next-gen OS. If Google is the old internet—Perplexity wants to be the new one. Welcome to The Uncanny Valley Weekly Series, Fridays at 4:20 PM ET, ONLY on 𝕏. Episode 5: THE AGENT ERA IS HERE — AND GOOGLE CAN’T STOP IT 01:05 – “We started as an answer engine.” How Perplexity went from RAG to research to real-world action. 03:03 – “Tell me what I should think about NVIDIA.” Agents as consultants, not just search engines. 05:07 – Buy buttons, autofill, AI shopping carts—how agents are already doing tasks. 07:05 – “You don’t have to see the tabs.” What the new browser will look like. 10:45 – “Warren Buffett doesn’t use apps—why should you?” The inspiration behind the AI-native phone. 12:36 – Why Apple, Google, and even OpenAI won’t build an AI-native OS. 17:28 – “Search is the most important tool in the agent era.” And Perplexity owns it. 21:33 – Mukesh Ambani’s advice: “Content is king, but distribution is GOD.” 27:13 – “Retrofit AI into iOS? It’ll never work.” Why the future needs a native platform. 30:26 – Humane failed, but the idea didn’t. Why assistants—not apps—are the next big UX shift. 33:38 – “We want Perplexity to feel like Apple.” Design still matters—even with agents. 37:11 – Why the real moat in AI isn’t models—it’s trust, taste, and vibe. 42:07 – 80M impressions in 6 weeks: How “Ask Perplexity” is going viral on 𝕏. 47:52 – “We’ve survived the internet—AI’s not scarier.” Aravind pushes back on the doomerism. 50:00 – Healthcare, finance, travel—Perplexity wants to power the vertical agent revolution. 54:24 – “LLMs can reason. But only agents can do.” Why execution is the next AI frontier. 56:34 – COMET browser drops in 3 weeks.show more

Mario Nawfal

2,953,857 subscribers

1,748,592 views • 1 year ago •via X (Twitter)

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10 Comments

gökhan1 year ago

@AravSrinivas @operationdanish @perplexity_ai What do you think of AI search?

𝖑𝖎𝖑 𝖕𝖑𝖚𝖙𝖔 ₿1 year ago

@AravSrinivas @operationdanish @perplexity_ai interesting

VICTOR1 year ago

@AravSrinivas @operationdanish @perplexity_ai Interesting

Matty (Ø,G) ⚡🇨🇭1 year ago

@AravSrinivas @operationdanish @perplexity_ai The future of search is here, and agents are leading the way. Excited to dive into this conversation.

emey rollie1 year ago

@AravSrinivas @operationdanish @perplexity_ai Let’s see how that goes

Alva1 year ago

Aravind Srinivas on AI native assistants—big shift incoming. Going from reactive to proactive: AI will now anticipate needs, not just respond. Perplexity bets on deep AI integration, aiming to outmaneuver Google. Example? T-Mobile's AI phone, delivering proactive task management and context-aware suggestions. Watch out for more intuitive AI-driven interactions. 🚀 No web3 vibes here, but AI's evolution might just change the game. For deeper insights:

Andromeda1 year ago

@AravSrinivas @operationdanish @perplexity_ai Yes AI will kill search engine. It’s already dead. AI almost has everything you want to know.

Vox Silencio1 year ago

@AravSrinivas @operationdanish @perplexity_ai i would rather robots of the future not look human or anime but keep a machine "face"

Cuffin The Dip1 year ago

@AravSrinivas @operationdanish @perplexity_ai Exciting stuff! How do you see Perplexity shaping the future of everyday tasks and interactions for the average person?

Olivia1 year ago

@AravSrinivas @operationdanish @perplexity_ai The search revolution isn't just about better algorithms - it's about liberating information from tech monopolies. Perplexity's agent-based approach could finally break Google's stranglehold on digital knowledge flows.

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This Week in AI

40,470 views • 5 months ago

🚨Keith Rabois on Perplexity's AI browser: "It's a great Hail Mary attempt" because " absent something like this, Perplexity is toast." @jason: "OpenAI and Perplexity are going after the browser." "Perplexity launched Comet for their $200/month tier." "This is a really interesting category. Having your browser connected to agents lets you do really interesting things." Keith Rabois: "I think it's a great Hail Mary attempt by Perplexity." "I think absent something like this, Perplexity is toast." "Like, per the stat about ChatGPT going to a billion users, it's becoming the verb, you know, the way you describe using AI for a normal consumer." "There's nothing left of Perplexity if they can't pull this off." "So it's a great idea because the history of consumer technology companies is, whoever has uphill ground, like in a military sense, whoever's first has a lot of control." "This is actually what Google should be doing, truthfully." "I think Google Search is toast." "And since they have Chrome and they theoretically have a quality team in Gemini, they should be putting these two things together and hoping to compete with ChatGPT." "They're gonna lose the search game. The assets that are best at Google right now have nothing to do with search." "It's every other product that's the only thing that's gonna save that company if they can figure out how to use them."

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338,311 views • 1 year ago

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AI is replacing apps with agents, bypassing traditional distribution, and deciding which tech platforms survive. Hedgeye Asset Management Portfolio Manager Sam Rahman @SamofAmerica and Communications analyst Andrew Freedman Andrew Freedman, CFA 🦅 break down what Google x Apple’s Gemini deal means for Siri, agents, apps, ads, and the next platform war. (0:00) Why this conversation + the AI setup (4:30) Google x Apple: Gemini, Siri, and the inflection point (6:00) Distribution, defaults, and DOJ guardrails (8:17) AI as the next abstraction layer (11:52) When agents operate your phone (OSs matter less?) (23:30) Downstream fallout: apps, e-commerce, disintermediation (33:18) OTAs vs AI agents (travel as the test case) (38:55) Amazon’s moat: fulfillment, rewards, and control (42:16) Payments analogy: acceptance is the real battle (52:47) Ads in an agent-driven world (55:03) Meta’s risk and the glasses bet

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Sonya Huang 🐥

128,785 views • 1 month ago

In 2001, Jeff Dean and Sanjay Ghemawat did the math and realized Google’s entire search index would fit in RAM — then shipped it in a few days, and search got fast. In 2013, another napkin calculation showed that three minutes of daily speech recognition per user would require doubling Google’s server fleet. That one became the TPU. At Startup School 2026, Google’s Chief Scientist talks with YC’s Diana through the thought experiments behind both, why inference hardware is the next specialization, and where two or three people in a room can still win. 00:07 — Are AI Models Already Junior Engineers? 01:44 — AI Systems That Improve Themselves 02:40 — The Google Search Breakthrough That Changed Everything 04:38 — AI Agents Will Run for Weeks 05:58 — The Napkin Math That Led to TPUs 09:20 — How to Find Breakthrough Ideas 10:25 — The AI Engineer's New Mental Model 12:33 — Why AI Is Really an Energy Problem 16:11 — Context Engineering Is the Next Frontier 19:46 — The Skill That Made AI Better at Optimization 22:13 — Why Long-Running Agents Fail 25:21 — Where Startups Can Still Beat Google 31:19 — How to Become an AI-Native Founder 36:36 — Question Your Biggest Assumptions 42:08 — AI That Builds Better AI 50:02 — Build Something That Truly Matters

In 2001, Jeff Dean and Sanjay Ghemawat did the math and realized Google’s entire search index would fit in RAM — then shipped it in a few days, and search got fast. In 2013, another napkin calculation showed that three minutes of daily speech recognition per user would require doubling Google’s server fleet. That one became the TPU. At Startup School 2026, Google’s Chief Scientist talks with YC’s Diana through the thought experiments behind both, why inference hardware is the next specialization, and where two or three people in a room can still win. 00:07 — Are AI Models Already Junior Engineers? 01:44 — AI Systems That Improve Themselves 02:40 — The Google Search Breakthrough That Changed Everything 04:38 — AI Agents Will Run for Weeks 05:58 — The Napkin Math That Led to TPUs 09:20 — How to Find Breakthrough Ideas 10:25 — The AI Engineer's New Mental Model 12:33 — Why AI Is Really an Energy Problem 16:11 — Context Engineering Is the Next Frontier 19:46 — The Skill That Made AI Better at Optimization 22:13 — Why Long-Running Agents Fail 25:21 — Where Startups Can Still Beat Google 31:19 — How to Become an AI-Native Founder 36:36 — Question Your Biggest Assumptions 42:08 — AI That Builds Better AI 50:02 — Build Something That Truly Matters

Y Combinator

255,989 views • 2 months ago

Today we are announcing Keenable AI, an AI-native index of the best human knowledge we have, starting with the open web. AI seems to know just about everything until you ask it about something you know deeply. The answer isn’t wrong, but it's just very average. We started Keenable to fix this problem: every model and every agent should be able to query, reason over, and continuously learn from the living web. Backed by a $26M Seed from Accel and Conviction. Built by the team that took on Google at Yandex Search, with researchers and engineers from Amazon AGI, X, and Perplexity. The Web Search API and Web Query Language for AI are live now. Together they make the web queryable at AI scale. Both are free until end of September. Seven days of benchmarks, stories, and launches ahead. Let your agents search.

Today we are announcing Keenable AI, an AI-native index of the best human knowledge we have, starting with the open web. AI seems to know just about everything until you ask it about something you know deeply. The answer isn’t wrong, but it's just very average. We started Keenable to fix this problem: every model and every agent should be able to query, reason over, and continuously learn from the living web. Backed by a $26M Seed from Accel and Conviction. Built by the team that took on Google at Yandex Search, with researchers and engineers from Amazon AGI, X, and Perplexity. The Web Search API and Web Query Language for AI are live now. Together they make the web queryable at AI scale. Both are free until end of September. Seven days of benchmarks, stories, and launches ahead. Let your agents search.

Andrey Styskin

551,948 views • 1 month ago

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch

GREG ISENBERG

84,760 views • 3 months ago

We're entering a new era of software where a single person, working with AI agents, can build products that previously required entire teams. In this episode of the Lightcone Podcast, they break down the rise of AI coding agents, "tokenmaxxing", and the emerging workflows behind tools like Claude Code and OpenClaw. They discuss why AI systems today feel less like productivity tools and more like collaborators, why the future of AI should be personal and user-controlled, and how founders are starting to build software in completely new ways. 00:00 — Will you control your AI? 00:47 — Coding again after 13 years 01:56 — Rebuilding a startup with Claude Code 05:50 — Software that thinks like a journalist 07:09 — The rise of “tokenmaxxing” 10:07 — The accidental creation of GStack 14:21 — The workflow behind 400x output 20:59 — Thin Harness, Fat Skills 24:35 — AI agents are like Ferraris 27:12 — The future of personal AI 38:37 — Buying back time with tokens

We're entering a new era of software where a single person, working with AI agents, can build products that previously required entire teams. In this episode of the Lightcone Podcast, they break down the rise of AI coding agents, "tokenmaxxing", and the emerging workflows behind tools like Claude Code and OpenClaw. They discuss why AI systems today feel less like productivity tools and more like collaborators, why the future of AI should be personal and user-controlled, and how founders are starting to build software in completely new ways. 00:00 — Will you control your AI? 00:47 — Coding again after 13 years 01:56 — Rebuilding a startup with Claude Code 05:50 — Software that thinks like a journalist 07:09 — The rise of “tokenmaxxing” 10:07 — The accidental creation of GStack 14:21 — The workflow behind 400x output 20:59 — Thin Harness, Fat Skills 24:35 — AI agents are like Ferraris 27:12 — The future of personal AI 38:37 — Buying back time with tokens

Y Combinator

67,145 views • 4 months ago

There's probably $100+ billion up for grabs for people who build startup for AI agents Over the next 10 years you're going to have a market of billions of customers (agents) with millions of wallets that want to use your services. TLDR; The internet was built for people: 1. Search google 2. Read landing page 3. Book demo 4. Talk to sales 5. Buy Agents don’t do that. Agents will: 1. Ask which product to use 2. Read your docs/pricing/security pages 3. Compare you to competitors 4. Check if you have an MCP/API/tool layer 5. Buy or recommend you without ever “visiting” your site like a person Everyone is going to have personal agents and business agents. This feels inevitable at this point. OpenClaw, Hermes, Claude Code, Codex, Google Spark. The tools are here. Which means there will be more agents on the internet than humans. So, where's the opportunity?? Go look at every SaaS tool you use. Notion. Slack. Jira. Google Analytics. Now ask: what is the version of this built purely for agents? Agent-native payments. Agent-native communication. Agent-native memory. Every category gets rebuilt. I clearly break down this shift and explain you everything on today's ep of The Startup Ideas Podcast (SIP) 🧃. Over the next 10 years you're going to have a market of billions of customers (agents) with millions of wallets that want to use your services. The founders who build for them now are going to look like the people who built websites in 1995. Might feel janky at the moment, but also obvious in hindsight. This is the next shift. Link over here: Watch

There's probably $100+ billion up for grabs for people who build startup for AI agents Over the next 10 years you're going to have a market of billions of customers (agents) with millions of wallets that want to use your services. TLDR; The internet was built for people: 1. Search google 2. Read landing page 3. Book demo 4. Talk to sales 5. Buy Agents don’t do that. Agents will: 1. Ask which product to use 2. Read your docs/pricing/security pages 3. Compare you to competitors 4. Check if you have an MCP/API/tool layer 5. Buy or recommend you without ever “visiting” your site like a person Everyone is going to have personal agents and business agents. This feels inevitable at this point. OpenClaw, Hermes, Claude Code, Codex, Google Spark. The tools are here. Which means there will be more agents on the internet than humans. So, where's the opportunity?? Go look at every SaaS tool you use. Notion. Slack. Jira. Google Analytics. Now ask: what is the version of this built purely for agents? Agent-native payments. Agent-native communication. Agent-native memory. Every category gets rebuilt. I clearly break down this shift and explain you everything on today's ep of The Startup Ideas Podcast (SIP) 🧃. Over the next 10 years you're going to have a market of billions of customers (agents) with millions of wallets that want to use your services. The founders who build for them now are going to look like the people who built websites in 1995. Might feel janky at the moment, but also obvious in hindsight. This is the next shift. Link over here: Watch

GREG ISENBERG

55,882 views • 3 months ago

Perplexity declared war on the biggest open source AI movement of 2026. This changes how millions of people will interact with AI agents forever. Here is what happened and why almost nobody is talking about the real implications. OpenClaw exploded in January and it became one of the fastest growing open source projects in GitHub history. The premise was radical. An AI agent that runs on your own machine, connects to your messaging apps and actually does things while you sleep. Developers went wild and over 700 community built skills appeared on ClawHub. People were negotiating car deals, filing legal rebuttals, and building entire social networks run by AI agents. Then Perplexity showed up with something different. A cloud powered system that coordinates 20 frontier AI models at once. They call it Perplexity Computer and this week they went even further. They announced Personal Computer. An always on AI agent that lives on a Mac mini in your home, connected to your local files and Perplexity's secure servers around the clock. It never sleeps or stops working and you control it from any device, anywhere. But the real story is what CEO Aravind Srinivas said during the Q&A session at their inaugural developer conference in San Francisco. He called Perplexity Computer a product "meant for serious people." He talked about Uber drivers asking him when they could stop driving and let AI make them passive income. That, he said, is the actual vision and then he went directly after OpenClaw. He said even a former Perplexity engineer struggled to get OpenClaw running on their own machine. He warned about unvetted malware being imported through OpenClaw's community skill hub, with no control over what people are contributing. He called the hobbyist approach of managing 700 API keys and sub agent configuration files a dead end for mainstream adoption. And four years of building world class orchestration gives Perplexity something an open source project cannot match. Enterprise grade security for solopreneurs and businesses alike. On one side, OpenClaw represents radical openness. Your data stays local, you choose your own models, you own everything and the community builds the tools. On the other hand, Perplexity is betting that most people don’t want to be system administrators. They want results, security guarantees, and something that just works out of the box. The Personal Computer runs on Perplexity's SOC 2 certified infrastructure. Every sensitive action requires user approval, every action is logged, and there is a kill switch. The enterprise version connects natively to Snowflake, Salesforce, HubSpot, and hundreds of other platforms. Teams can query data warehouses and build financial models without waiting on an analytics team. The real question is not which product is technically better. The real question is whether the future of AI agents looks like Linux or looks like the iPhone. Because the Uber driver Srinivas described is not going to configure sub agent routing tables. That person needs something that works the moment they open it. And if Perplexity captures that market, the open source movement becomes a niche for developers instead of a revolution for everyone. That is the billion dollar bet being made right now.

Perplexity declared war on the biggest open source AI movement of 2026. This changes how millions of people will interact with AI agents forever. Here is what happened and why almost nobody is talking about the real implications. OpenClaw exploded in January and it became one of the fastest growing open source projects in GitHub history. The premise was radical. An AI agent that runs on your own machine, connects to your messaging apps and actually does things while you sleep. Developers went wild and over 700 community built skills appeared on ClawHub. People were negotiating car deals, filing legal rebuttals, and building entire social networks run by AI agents. Then Perplexity showed up with something different. A cloud powered system that coordinates 20 frontier AI models at once. They call it Perplexity Computer and this week they went even further. They announced Personal Computer. An always on AI agent that lives on a Mac mini in your home, connected to your local files and Perplexity's secure servers around the clock. It never sleeps or stops working and you control it from any device, anywhere. But the real story is what CEO Aravind Srinivas said during the Q&A session at their inaugural developer conference in San Francisco. He called Perplexity Computer a product "meant for serious people." He talked about Uber drivers asking him when they could stop driving and let AI make them passive income. That, he said, is the actual vision and then he went directly after OpenClaw. He said even a former Perplexity engineer struggled to get OpenClaw running on their own machine. He warned about unvetted malware being imported through OpenClaw's community skill hub, with no control over what people are contributing. He called the hobbyist approach of managing 700 API keys and sub agent configuration files a dead end for mainstream adoption. And four years of building world class orchestration gives Perplexity something an open source project cannot match. Enterprise grade security for solopreneurs and businesses alike. On one side, OpenClaw represents radical openness. Your data stays local, you choose your own models, you own everything and the community builds the tools. On the other hand, Perplexity is betting that most people don’t want to be system administrators. They want results, security guarantees, and something that just works out of the box. The Personal Computer runs on Perplexity's SOC 2 certified infrastructure. Every sensitive action requires user approval, every action is logged, and there is a kill switch. The enterprise version connects natively to Snowflake, Salesforce, HubSpot, and hundreds of other platforms. Teams can query data warehouses and build financial models without waiting on an analytics team. The real question is not which product is technically better. The real question is whether the future of AI agents looks like Linux or looks like the iPhone. Because the Uber driver Srinivas described is not going to configure sub agent routing tables. That person needs something that works the moment they open it. And if Perplexity captures that market, the open source movement becomes a niche for developers instead of a revolution for everyone. That is the billion dollar bet being made right now.

Milk Road AI

22,256 views • 6 months ago

LIVE NOW - Tempo Mainnet: The Race to Agentic Commerce Tempo is live, and the big bet is clear: AI agents need a native payment layer. Georgios Konstantopoulos and Brendan Ryan join Bankless to explore: - why Tempo launched with agentic payments front and center, - how MPP turns payments into auth, - why “give the agent the wallet” could unlock a new internet economy, - where MPP fits against x402, - what Tempo’s L1 design makes possible for builders. Enjoy the episode. --- TIMESTAMPS 0:00 Tempo Mainnet goes live 1:18 Why the launch is focused on agents 3:58 What MPP actually is 6:30 MPP vs x402 15:28 Why agentic commerce matters 20:08 The “original sin” of the internet 26:04 MCP, NLWeb, and the emerging agent stack 34:07 The onboarding flow: wallets for agents 37:11 How Tempo’s wallet security works 40:11 Tempo chain design and specs 51:13 Why build an L1 instead of an Ethereum L2? 56:10 The Ethereum tension 1:05:01 Agent identity, reputation, and ERC-8004 1:06:53 TIP20, stablecoins, and what can be built on Tempo 1:12:36 Builder opportunity in the agentic web

LIVE NOW - Tempo Mainnet: The Race to Agentic Commerce Tempo is live, and the big bet is clear: AI agents need a native payment layer. Georgios Konstantopoulos and Brendan Ryan join Bankless to explore: - why Tempo launched with agentic payments front and center, - how MPP turns payments into auth, - why “give the agent the wallet” could unlock a new internet economy, - where MPP fits against x402, - what Tempo’s L1 design makes possible for builders. Enjoy the episode. --- TIMESTAMPS 0:00 Tempo Mainnet goes live 1:18 Why the launch is focused on agents 3:58 What MPP actually is 6:30 MPP vs x402 15:28 Why agentic commerce matters 20:08 The “original sin” of the internet 26:04 MCP, NLWeb, and the emerging agent stack 34:07 The onboarding flow: wallets for agents 37:11 How Tempo’s wallet security works 40:11 Tempo chain design and specs 51:13 Why build an L1 instead of an Ethereum L2? 56:10 The Ethereum tension 1:05:01 Agent identity, reputation, and ERC-8004 1:06:53 TIP20, stablecoins, and what can be built on Tempo 1:12:36 Builder opportunity in the agentic web

Bankless

23,815 views • 6 months ago

Satya Nadella on Copilot, the AI backlash, and Microsoft’s future Satya Nadella thinks AI agents will create a market “orders of magnitude” bigger than the cloud. I recently sat down with him in Seattle for the unveiling of the new Copilot. We discuss Autopilot, Microsoft's new OpenClaw-based agent that can work on your behalf, and why he thinks newer AI models are finally capable of delivering on more of Copilot’s promise. Nadella also has a blunt assessment of the AI industry: “We are way too self-obsessed.” I ask him why the industry has struggled to explain its benefits and what it will take to earn people’s trust. We get into his concerns about agents acting deceptively, when a safety problem should stop a release, and why he doesn’t want AI oversight to become a “cartel-like arrangement.” We also discuss Microsoft’s relationship with OpenAI, the models Microsoft is building itself, and why Nadella wants investors to think about its apps, agents, and infrastructure as one connected business. He explains how he uses AI to track Microsoft’s capital spending, shares his vision for “unmetered intelligence” on Windows, and gives an update on Xbox’s path back to growth. Timestamps: 00:00 The race for AI agents 07:53 Copilot’s next chapter 11:50 Autopilot and the digital teammate 16:50 How Microsoft prices AI 19:48 Why Microsoft is betting on multiple models 23:18 Measuring AGI through economic growth 28:39 The economics of Microsoft’s AI build-out 32:13 OpenAI and Microsoft’s own models 35:27 AI safety, control, and regulation 43:53 Why the AI industry is losing public trust 46:59 The future of Xbox and Windows 50:34 Microsoft’s biggest risk and opportunity Thanks to the show's premier sponsors: Mercury, Granola, and Atlassian.

Satya Nadella on Copilot, the AI backlash, and Microsoft’s future Satya Nadella thinks AI agents will create a market “orders of magnitude” bigger than the cloud. I recently sat down with him in Seattle for the unveiling of the new Copilot. We discuss Autopilot, Microsoft's new OpenClaw-based agent that can work on your behalf, and why he thinks newer AI models are finally capable of delivering on more of Copilot’s promise. Nadella also has a blunt assessment of the AI industry: “We are way too self-obsessed.” I ask him why the industry has struggled to explain its benefits and what it will take to earn people’s trust. We get into his concerns about agents acting deceptively, when a safety problem should stop a release, and why he doesn’t want AI oversight to become a “cartel-like arrangement.” We also discuss Microsoft’s relationship with OpenAI, the models Microsoft is building itself, and why Nadella wants investors to think about its apps, agents, and infrastructure as one connected business. He explains how he uses AI to track Microsoft’s capital spending, shares his vision for “unmetered intelligence” on Windows, and gives an update on Xbox’s path back to growth. Timestamps: 00:00 The race for AI agents 07:53 Copilot’s next chapter 11:50 Autopilot and the digital teammate 16:50 How Microsoft prices AI 19:48 Why Microsoft is betting on multiple models 23:18 Measuring AGI through economic growth 28:39 The economics of Microsoft’s AI build-out 32:13 OpenAI and Microsoft’s own models 35:27 AI safety, control, and regulation 43:53 Why the AI industry is losing public trust 46:59 The future of Xbox and Windows 50:34 Microsoft’s biggest risk and opportunity Thanks to the show's premier sponsors: Mercury, Granola, and Atlassian.

Alex Heath

187,621 views • 3 days ago