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No Priors: Artificial Intelligence | Technology | Startups

Conviction

At this moment of inflection in technology, co-hosts Elad Gil and Sarah Guo talk to the world's leading AI engineers, researchers and founders about the biggest questions: How far away is AGI? What markets are at risk for disruption? How will commerce, culture, and society change? What’s happening in state-of-the-art in research? “No Priors” is your guide to the AI revolution. Email feedback to show@no-priors.com.

Sarah Guo is a startup investor and the founder of Conviction, an investment firm purpose-built to serve intelligent software, or "Software 3.0" companies. She spent nearly a decade incubating and investing at venture firm Greylock Partners.

Elad Gil is a serial entrepreneur and a startup investor. He was co-founder of Color Health, Mixer Labs (which was acquired by Twitter). He has invested in over 40 companies now worth $1B or more each, and is also author of the High Growth Handbook.

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S1 · E186
Today · 54 min
Tokenization, Agentic Trading, Harmonic: Robinhood's Mission to Expand Ownership with CEO Vlad Tenev
What does it mean to build wealth as an individual investor in today’s society, especially as gains continue to get concentrated into smaller groups of VCs or institutional investors? Robinhood’s CEO and co-founder Vlad Tenev has a vision that can be summed up in one word: Ownership. In this episode, Sarah Guo chats with Vlad to get a closer look at how Robinhood has evolved from a simple app to buy stocks at zero commission into a global conglomerate that allows customers to own across a wide variety of surfaces and asset classes. Vlad explains how Robinhood is helping users extend ownership amidst the current economy and ongoing AI revolution through Trump accounts, tokenization of privates, and newer product offerings like Robinhood Chain, Agentic Trading, and Agentic Credit Card. He also talks about how his new mathematical superintelligence startup, Harmonic, is revolutionizing the field and how he hopes it will decentralize new discoveries and inventions. Vlad and Sarah also discuss how prediction markets could tie into the ownership conversation, whether financial infrastructure can be optimized to enable even higher volumes of high-frequency trading, and his advice for maintaining a level head when facing the vagaries of a changing financial market. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @vladtenev | @RobinhoodApp | @HarmonicMath Chapters: 00:46 – Intro to Vlad Tenev, His Background, and Robinhood Today 12:25 – A Revolutionary Future for Mathematics 18:49 – Robinhood’s Vision for Tokenization 26:06 – Monetizing Knowledge via Prediction Markets 28:48 – Impacts of Agentic Trading and Democratizing Trading 33:48 – Safeguarding Financial Infrastructure for a New Load of HFTs 38:30 – Ownership of Private Companies in the AI Revolution 48:34 – Robinhood and Trump Accounts 50:47 – Keeping a Steady Hand and Head as a Leader 53:48 – Conclusion
October 29 · 38 min
Taking on ServiceNow: Coding Agents the Rest of Us with Serval Co-Founder and CEO Jake Stauch
What happens when you put code-generation agents in the hands of enterprise IT teams? With Serval, you get a system where it's easy for everyone to be a builder. Sarah Guo and Elad Gil sit down with Serval co-founder and CEO Jake Stauch to analyze his company’s direct challenge to ServiceNow as the enterprise automation and service management system of record. Jake explains that by building an AI platform for enterprise IT departments with Serval, users can safely build while still safeguarding permissions by strict deterministic approvals and an audit trail. He also talks about ProServal, the company’s team that embeds automation engineers directly with customers in order to provide ongoing support and service. Jake also discusses how AI was the big unlock to taking on ServiceNow, why he’s betting on coding agents getting even better, why consumer is a window into what will happen next in enterprise and why the SaaS-pocalypse might look more like a consolidation, why background agents are still a moonshot in enterprise software, and the importance of hiring product-oriented engineers. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jakeserval | @getserval Chapters: 00:47 – Jake Stauch Introduction and Serval’s Background 03:00 – Expanding Coding Agents Beyond Engineers 04:40 – Limitations with Personal Agents in Enterprise 06:29 – Deploying Serval Effectively in Large Orgs 07:55 – Day 1 Ambition and Attacking Enterprise Systems of Record 09:51 – Taking on ServiceNow with Workflow Automation Platform 11:01 – Betting on the Evolution of Coding Agents and Building Guardrails in Enterprise 13:48 – Big Risks, Big Rewards, and Big Predictions for Serval and Coding Agents 16:40 – Adopting Different Sets of Building Principles at an Enterprise Level 20:49 – Token Maxing, Long-Term Budget Impacts, and ROI 22:39 – The SaaS-pocalypse and SaaS vs. AI 24:39 – The Mental Model for Delivering Platform-Level Power to the IT User at Enterprise 26:43 – Building Automations with Catalyst and Raising Technical Competence 28:55 – The Next Wave: Background Agents and Autonomy in Enterprise 32:23 – Hiring Velocity and Unlimited Ambition at Serval 34:17 – Keeping Pace with Customers and Fundamental Shifts in Product Function 37:05 – Conclusion
S1 · E184
October 23 · 41 min
Democratizing Security for the Agentic Web with Cloudflare CTO Dane Knecht
In the transition to the agentic web, security has become an afterthought. Now, organizations are racing to figure out what AI security means, and how to keep their data safe. Live from Cloudflare Connect, Sarah Guo sits down with Cloudflare CTO Dane Knecht to discuss the changing attacker landscape, and how his company is allocating its engineering resources to meet this emerging security challenge. Dane explains how enterprises that have moved away from castle-and-moat infrastructure to more of a zero trust infrastructure for security are in better positions than those who haven’t. He also discusses the challenges of patching 70 years of software and why the software development lifecycle will need to change for security for the agentic web, why he sees token spend in the next 18 months primarily going towards security rather than engineering, how the current web is in a ‘messy middle’ state where humans and agents are riding the same ‘rails’ on the internet, Cloudflare’s conference monetization gateway release as well as its Signals project with OpenAI, the rationale behind the release of Cloudflare OS, and the thinking behind a recent company restructuring. Plus, why Cloudflare hired one thousand interns, and why curiosity about AI is required to be successful at Cloudflare. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Cloudflare | @dok2001 Chapters: 00:00 – Trailer 00:55 – Cloudflare CTO Top Priorities 05:03 – Today’s Attacker Landscape 06:16 – State of Internet Infrastructure 07:31 – Shift Towards Security Spend 08:39 – Road to Better Software and Internet Security 09:50 – Building Secure Production Software 11:41 – Reducing Surface Area 12:54 – Near Future of the Web 17:27 – Monetization and Signals 19:13 – Success for Content Creators 20:07 – Workplace OS and Use Cases 24:07 – Restructuring for AI-First 27:11 – Token Budgeting 29:32 – Cloudflare’s Intern Strategy 33:39 – Importance of Curiosity 35:29 – Attacking the Legacy Software Security Problem 37:08 – Engineering Team Prioritization 38:25 – Open vs. Closed Models 39:43 – Democratizing Security for Everyone 41:29 – Conclusion
October 22 · 45 min
The New Apex Predator: CrowdStrike CEO George Kurtz on Adversaries Armed With AI Agents
Adversaries are already running AI agents, and the fastest attacks now play out in seconds. Sarah Guo and Elad Gil sit down with CrowdStrike president and CEO George Kurtz on what AI-equipped attackers mean for enterprise security. George explains how agents are flattening the adversary pyramid by putting advanced tradecraft in the hands of low-skill attackers, and why CrowdStrike and Nvidia are building a frontier-style lab of their own to train security models. They also get into how open-weight and closed models compare on security, where CrowdStrike is directing its platform investment, lessons from the recent Hugging Face incident, and why George sees AI, like every platform shift before it, as a net creator of opportunity. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @CrowdStrike | @George_Kurtz Chapters: 00:00 – Trailer 00:59 – George Kurtz Introduction 01:24 – Agentic Landscape 02:45 – AI and Adversaries 04:51 – Open Weight Models and Adversarial Attacks 06:37 – Adversary Geography 08:34 – Attacker Capability in Context 11:24 – Hugging Face Takeaways 13:59 – CrowdStrike Frontier Security Models 16:32 – CrowdStrike Key Offerings 19:51 – What Differentiates CrowdStrike’s Models 23:57 – Near Term State of Security World 25:46 – State of Model Distillation 27:53 – Open Weight Model Importance and Cost 29:59 – Assessing Real Agent Threat 32:40 – Areas to Watch in AI 35:02 – Case for Defense Dominance 39:15 – Executive Advice 43:16 – Shifts Create Opportunity 45:27 – Conclusion
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October 15 · 39 min
The Changing Physics of Cybersecurity and Drug Development with OpenAI President Greg Brockman
Technology has always been the fundamental driver of improvement for human quality of life. And with the recent rollout of advanced frontier models, like OpenAI’s GPT-6, humanity can now massively accelerate scientific discovery for its benefit. Sarah Guo and Elad Gil are joined by OpenAI President and co-founder Greg Brockman to discuss the company’s rapid progress across frontier models, cybersecurity, and scientific discovery. Greg shares how nearly 400 century-old math problems have been solved using its AI agents, and how the technology has the potential to transform other fields like biology in the realm of drug discovery. He also talks about how proactive, always-on AI agents like Dots impact modern productivity, why he believes the best UI is no UI at all, how cybersecurity is in a critical window of time to use peak intelligence to find and fix vulnerabilities in systems, and why OpenAI remains committed to keeping humans in the driver’s seat even as models surpass us in capability. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @gdb | @OpenAI Chapters: 00:42 – Trailer 00:59 – Greg Brockman Introduction 01:11 – AI and Advancements in Mathematics 05:55 – AI Communication and Oversight 07:45 – AI for Overcoming Biology Data Bottlenecks 11:28 – Revolutionizing Drug Discovery 14:18 – Changing Regulations to Accelerate Progress 16:51 – Dots the Proactive Agent 19:19 – Unifying Work and Consumer Agents 22:02 – How UI Will Evolve 26:08 – Cybersecurity in the AI Age 32:55 – Shift in Security Investment 35:49 – OpenAI’s Human-Centric Ethos 38:28 – Conclusion
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October 9 · 1 hr 9 min
Beam: The Great American Open Model with ReflectionAI Co-Founder and CEO Misha Laskin
Is the future of frontier AI open or closed? ReflectionAI co-founder and CEO Misha Laskin joins Sarah Guo and Elad Gil to discuss the launch of Beam, the company’s 500 billion parameter open-weight reasoning model. Misha breaks down the pre-training and reinforcement learning required to produce Beam’s reasoning efficiency, the shift in enterprise compute from renting to owning intelligence, and how he believes that open models will capture the majority of global token demand. He also talks about the open model ecosystem in China and why competition with China’s models is a good thing, safety considerations around open models, and how frontier-level open models may accelerate the pace of scientific discovery. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @MishaLaskin | @reflection_ai Chapters: 00:42 – Misha Laskin Introduction 00:59 – Latest with ReflectionAI 02:07 – Challenges Building an Open Model 03:56 – ReflectionAI’s Agentic Shift 07:37 – Resources for Model Training 10:09 – Scaling Efficiency 12:18 – Training Beam 16:51 – Where Model Value Comes From 19:55 – Beam’s Reasoning Efficiency 22:35 – Monetizing Open Weight Models 25:03 – Future of Open Versus Closed Tokens 31:29 – Competition with Open Models 34:38 – Chinese Open Source Model Ecosystem 38:40 – Will Chinese Models Remain Open 44:44 – Safety and Open Models 53:02 – Debating Access to Powerful Tools 57:16 – AI and Scientific Progress 01:00:36 – Data Centers and Jobs 01:02:07 – Beam and Scientific Research 01:05:37 – Research Head Count to Compute Ratio 01:10:29 – Conclusion
October 2 · 35 min
Frontier Chips for Frontier AI Labs, with Walter Goodwin, Founder/CEO of Fractile
Founder and CEO of full-stack AI chip company Fractile, Walter Goodwin, joins Sarah Guo to discuss the bets he’s made on the future of the chip market as other major players like Broadcom, NVIDIA, and AMD try to accelerate their workloads. They discuss the difference in Fractile’s newer approach on model architecture with a full-stack team in the current chip landscape and the technical bets they’re making in that direction. Walter also talks about compressing the gap between the chip design cycle and its payoff period, and making a generational leap in AI inference to realize the bet in volume against the value to be captured. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @goodwin_ml | @fractile_ai Chapters: 00:46 – Walter Goodwin and Fractile Introduction 02:29 – The Chip Landscape Now 04:56 – Common Handoffs From Architecture-Focused Players 07:18 – Full Stack Approach and Team Setup 09:49 – Fractile’s Most Important Technical Bets 15:32 – Workload Predictions and Compressing the Chip Design Cycle 23:03 – Architect Intent to Output Bottlenecks and Accelerating Trials 28:16 – Workload Bets on Model Architectural Shifts 31:20 – The Future of AI Chip Players and Market Structure 35:14 – Conclusion
September 24 · 42 min
Re-Founding Incumbents for the AI Era with Sequence Holdings Co-Founder and CEO Michael Lee
Can AI transform legacy incumbents rather than replacing them? Sequence Holdings co-founder and CEO Michael Lee joins Sarah Guo to discuss how holding company structures and engineering integrations are reshaping market leaders from the inside out. Michael details Sequence’s $7.7 billion take-private transaction of Baldwin alongside Dell Family Office (DFO), and shares his thesis on why traditional consulting models and software sales fall short for real enterprise AI transformations. They also talk about why permanent holding company structures are good for long-term compounding, real-world results from applying frontier engineering to BankSouth, and Michael’s lessons from his time in public investing, private equity, and operating at the intersection of market incumbents and AI. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @mjlee_2014 | @seqholdings Chapters: 00:34 – Michael Lee Introduction 01:03 – Sequence Holdings and Baldwin 01:54 – Idea for Sequence 04:36 – Incumbents in the AI Era 06:32 – Why a Holding Company 11:21 – Recruiting Top Engineers 13:08 – Investing in BankSouth 17:46 – Why an Insurance Brokerage 20:17 – Atlas Platform Explained 23:53 – Traditional Private Equity Limitations 27:23 – What Sequence Looks For in Management Teams 31:04 – Accomplishments at BankSouth 34:45 – Founder Lessons 36:08 – Story of Dell Partnership 37:10 – Career and Investment Approach 40:00 – Value of Exceptional People 42:23 – Conclusion
S1 · E178
September 18 · 38 min
Why Diffusion Will Win AI Inference with Inception Co-Founder and CEO Stefano Ermon
As generative AI hits hardware and latency bottlenecks, Stanford professor, diffusion pioneer, and Inception co-founder and CEO Stefano Ermon is betting on a radical new architecture. Stefano joins Sarah Guo to talk about Inception, and how his team is applying diffusion architecture beyond images and video into discrete text and code generation. Stefano explains the limitations of autoregressive LLMs, as well as why parallel token generation in diffusion models offers superior inference scaling and hardware utilization on standard GPUs. He also shares details about Inception’s Mercury models, real-world voice agent applications, the software stack required to serve diffusion-based models at scale, academia’s role at the frontier of AI innovations, and why the next era of AI competition will be defined by efficiency. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @StefanoErmon | @_inception_ai Chapters: 00:00 – Stefano Ermon Introduction 00:35 – Research Background 02:54 – Starting Inception 05:59 – Why Diffusion Beats Autoregressive 11:10 – Discrete vs. Continuous Modalities 13:19 – Inception Today 16:45 – Where Speed Wins 17:31 – Inception Customer Base 18:49 – Interaction with Hardware Landscape 19:34 – Inception and the Broader Industry 21:41 – Data Compression and Structure 24:45 – Controllability of Diffusion Modeles 27:25 – Emergent Capabilities at Scale 29:02 – Future Workload Split Between Diffusion vs. Traditional 30:03 – Adoption Challenges 31:44 – Hiring and Team Organization 32:50 – Recursive Self Improvement 34:02 – Resource Allocation 35:10 – Impact of Academia 38:13 – Conclusion
S1 · E177
September 10 · 45 min
Coinbase’s Everything Exchange: Agentic Finance, Stablecoins, and Tokenization with CEO Brian Armstrong
From the tokenization of real-world assets to funding research on anti-aging therapeutics, Coinbase co-founder and CEO Brian Armstrong is focused on solving meta-problems for the benefit of society. Brian joins Elad Gil this episode to discuss the intersections of artificial intelligence, crypto rails, and biotechnology. He details Coinbase’s vision for agentic finance, as well as how Coinbase is becoming the ‘Everything Exchange’, which includes tokenized real-world stocks, stablecoin payment adoption, and prediction markets. Brian also introduces his new venture, New Limit, a company founded to tackle longevity through epigenetic reprogramming, and outlines initial therapeutic programs and the roadmap toward clinical trials. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @brian_armstrong | @Coinbase Chapters: 00:00 – Cold Open Trailer 00:45 – Brian Armstrong Introduction 01:13 – Coinbase and the Everything Exchange 05:52 – Agentic Commerce 10:00 – AI and Crypto 10:49 – AI Inside Coinbase 15:39 – Productivity and Company Size 17:26 – The Everything Exchange and Tokenization 20:53 – Prediction Markets 23:15 – Introducing New Limit 34:17 – Looking Forward Five Years 40:24 – Special Economic Zones 44:26 – Conclusion
S1 · E176
September 3 · 37 min
Redefining Chip Architecture with Arm CEO Rene Haas
From data center orchestrators to AGI and robotics, CPUs remain the heart of modern computing. Arm CEO Rene Haas joins Elad Gil and Sarah Guo to explore how Arm is positioned at the epicenter of AI-driven demands for compute. Rene explains Arm’s position in the chip supply chain, and how Arm transitioned from an IP licensing model to producing physical chips like the Arm AGI CPU for Meta. He also discusses bottlenecks in hardware supply chains, SoftBank’s ecosystem and capital strategy, why US semiconductor manufacturing independence is critical, the future of robotics, and why CPUs remain crucial for executing AI workloads. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @renehaas237 | @Arm Chapters: 00:00 – Cold Open Trailer 00:49 – Rene Haas Introduction 01:14 – Arm and Chip Supply Chain 02:37 – Shift from IP to Manufacturing CPUs 04:23 – CPU IP and Customers 06:55 – AI Adoption at Arm 10:15 – Changes in Chip Time to Market 13:27 – Data Center Buildout Bottleneck 15:13 – Softbank Leverage and Capital Strategy 17:43 – Softbank Portfolio Overview 20:13 – Robotics Opportunities for Arm 24:49 – US Manufacturing Protectionism 28:59 – Data Center Backlash 32:30 – Arm Outlook 33:31 – CPU Opportunity 37:06 – Conclusion
S1 · E175
August 27 · 34 min
Rethinking Legacy Data Infrastructure with Eon Co-Founders Ofir Ehrlich and Gonen Stein
Google’s purchase of Spirit Airlines’ data out of bankruptcy signaled a shift in how the tech world values real-world datasets. Although compute and models get much of the attention, in this landscape, it’s data that is a company’s protective moat. Eon CEO / Co-Founder Ofir Ehrlich and President / Co-Founder Gonen Stein join Elad Gil to talk about how Eon is redefining cloud backup into a secure data foundation designed to power and protect enterprise AI. Ofir and Gonen discuss why historical enterprise data is in demand by AI labs, and how Eon facilitates access to scattered and locked data across business units through providing the mapping, classification, and access controls needed to connect it into AI workflows. They also explore how traditional ransomware defenses must now protect against rogue AI agents with legitimate system permissions, concerns around the influx of autonomous agents and non-human identities, and the implications for the breakneck speed of AI adoption compared to the slowness of the cloud era. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Eon_io_ | @OfirEhrlich Chapters: 00:00 – Cold Open Trailer 00:59 – Ofir Ehrlich and Gonen Stein Introduction 01:27 – What Eon Does 02:41 – Data as Moat 06:43 – Training Agents with Good Data 09:39 – Data is the New Oil 15:00 – Autonomous Security Threats 18:15 – How Agents Change the Enterprise Stack 22:11 – Re-imagining Data Infrastructure 27:52 – Cloud vs. AI Era Shift 30:26 – How AI is Changing Companies 34:31 – Conclusion
S1 · E174
August 20 · 31 min
From Restoring Sight to Reimagining the Brain, with Max Hodak
Max Hodak, co-founder and CEO of Science Corporation, joins Sarah Guo to discuss the future of vision, brain-computer interfaces, and the human experience. Max explains how Science’s PRIMA retinal implant could restore functional vision for people who have lost their sight, and why treating the brain as a computational system could unlock new approaches to medicine. They explore the broader potential of neural devices, from restoring lost capabilities to expanding human potential, as well as deeper questions around identity, consciousness, and whether the human experience can persist as our biological hardware changes. Max also shares Science’s long-term vision for reducing the fragility of the human condition by repairing, replacing, and ultimately upgrading parts of ourselves. Finally, he discusses the surprising parallels between AI models and biological brains, and why AI may offer a powerful new lens for understanding intelligence. Chapters: 00:00 – Cold Open Trailer 01:40 – Max Hodak Introduction 02:00 – Science Corporation Overview and Origin 02:53 – A Revolutionary Solve for Blindness 06:32 – Scope of Timeline and Engineer Cost 09:10 – Clinic Trial Process 09:45 - The Response from Clinicians 12:21 – Broader Biotech Landscape 14:59 – Brain’s Relationship to Senses 17:35 – The Study of Consciousness 19:50 – Investments in Brain Computer Interface 22:10 – Fertile Ways to Study Neuroscience 24:46 – Biotech Expansion for Science Corporation 27:50 – What Success Looks Like in Neuroscience and Tech 29:06 - Goals Within Human Preservation vs. Adaptation 30:25 – Conclusion
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August 13 · 46 min
What Chess.com Teaches US About Superhuman Capabilities, with CEO Erik Allebest
In a world of infinite gaming and entertainment possibilities, how does a centuries-old game stay so popular? Chess.com co-founder and CEO Erik Allebest joins Sarah Guo to explain how the evolution of technology has kept people coming back to chess, even when machines can beat us at the game. Erik talks about how the desire to build a MySpace-like community for chess led to the purchase of a domain name from a bankruptcy sale back in 2005, and scaled into a community with 10 million daily active users and 250 million total registered members. He also discusses the growth of the cultural relevance of chess, how investments from private equity firms General Atlantic and CVC helped grow and strengthen their platform, and how Chess.com is leveraging AI both within the business itself and to make a better product for its community. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @chesscom | @erikallebest Chapters: 00:00 – Cold Open Trailer 01:05 – Erik Allebest Introduction 01:48 – Chess.com Today 02:57 – Buying and Scaling Chess.com 06:29 – Competition and Growth 11:52 – Chess and Cultural Relevance 14:32 – Private Equity Investment 19:31 – Playing Games Amid Evolving Tech 25:09 – Tech, Skill Distribution, and Expertise 28:40 – Chess and Cheating 31:20 – What Makes Chess Special 33:17 – Chess.com Future Vision 34:54 – Founder Advice 36:48 – AGI/ASI Predictions 40:02 – AI Investments at Chess.com 42:13 – How AI May Change Product at Chess.com 43:27 – Poker Rating Algorithms 46:07 – Conclusion
S1 · E172
August 6 · 39 min
Chasing Trillion-Dollar Companies, Founder Ambition, Token Budgets, and Regulatory Capture with Sarah & Elad
Is the tech industry moving too quickly, or are founders letting fear of AI labs stunt their ambitions? Sarah and Elad explore the current landscape of artificial intelligence, venture capital, and startup dynamics. They discuss the realities of building multi-trillion-dollar companies, shifting market sizes and outcome-based pricing models, and how founders are reacting to the rise of major AI labs. They also talk about what the framework for startup exits should look like, the potential for researcher burnouts in the next eighteen months as ASI looms on the horizon, bottlenecks for compute, and the impact of regulatory capture and shifting ecosystems from California to Texas. Apply for Embed - Conviction’s Catalyst for AI-Native Startups Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil Chapters: 00:00 – Cold Open Trailer 00:31 – Episode Introduction 01:44 – The Next Trillion-Dollar Company 03:12 – Tech Waves as Punctuated Equilibria 04:42 – TAM vs. Revenue Reality 07:14 – Market Size vs. Speed 10:32 – When Founders Should Sell 14:04 – Financing and Time Cost 17:57 – RSI and the Looming Promise of ASI 21:49 – Compute Power Laws 28:12 – Regulations and Disruption 33:06 – Beyond Transformers 34:26 – Tradeoffs - Safety vs. Progress 39:11 – Conclusion
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July 31 · 34 min
Building an Autonomous Enterprise for Real-World Services with Netic Founder Melisa Tokmak
When your AC fails in a heatwave, you don’t want a busy signal; you need a solution. Netic founder and CEO Melisa Tokmak joins host Elad Gil to explain how Netic’s autonomous AI platform acts as an intermediary between companies and customers, deploying agents to instantly handle essential services, from emergency home repairs to hospitality to pet care. Melisa describes the complexity of these real-world workloads, which have traditionally relied on large human support teams, and how over 70% of Netic’s customers interact first with AI. She also talks about the reasoning behind building a scalable product company rather than an AI roll-up, why she believes robotics will not catch up in these industries in the near future, why she doesn’t view large frontier labs as competitive threats, and how private equity’s playbook has shifted toward measurable ROI in the AI-era. Plus, why Melisa is optimistic about the impact AI will have on education. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @netic_AI | @melisatokmak Chapters: 00:00 – Melisa Tokmak Introduction 00:32 – What Netic Builds 03:53 – Automating Workflows for Essential Services 06:26 – Building a Service vs. AI Roll-Up 10:38 – AI for the Real World Timeline 12:56 – Can Big Labs Compete? 15:35 – Modern Founder Mindset 19:09 – Screening for Agency 22:25 – Five Year Vision 23:53 – Selling to Slow Industries 27:23 – How Private Equity Approached AI 31:14 – What Excites Melisa About the Future of AI 34:27 – Conclusion
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July 23 · 49 min
Building an Autonomous Delivery Experience with DoorDash Co-Founders Andy Fang and Stanley Tang
DoorDash is not just a delivery company. From its inception, co-founders Andy Fang and Stanley Tang operated it as a robotics and autonomy company. Andy and Stanley join Sarah Guo to explain how autonomous tech and AI are reshaping consumer habits, commerce, and delivery. Andy and Stanley talk about the rollout of Ask DoorDash, a natural-language interface that’s driving both restaurant discovery and larger grocery orders. They also discuss Dot, their in-house autonomous delivery robot that has operated in Phoenix for over two years, and how it highlights the operational and hardware challenges they have faced and solved in autonomous tech. Andy and Stanley also speak about the “first and last 100 feet problem” in autonomous delivery, why multimodal strategies are the key to success, scaling autonomy and operations, and why they believe that more Dashers, not fewer, are the future of DoorDash. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @stanleytang | @andyfang | @DoorDash Chapters: 00:00 – Andy Fang and Stanley Tang Introduction 00:34 – Agentic Commerce and Behavioral Changes 03:52 – Next Steps for Ask DoorDash 06:54 – Investing in Robotics and Autonomy 16:31 – Building Autonomous Tech in the Physical World 21:20 – Dot: DoorDash’s Autonomous Delivery Robot 22:08 – Collecting Realistic Data 25:48 – Why Work at DoorDash 28:04 – Challenges in Scaling Up Autonomy 39:30 – Productivity Benchmarks 44:56 – Future of Agentic Commerce 49:10 – Conclusion
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July 9 · 41 min
Travel Through the Lens of AI with with Booking.com CEO Glenn Fogel
When Glenn Fogel joined Priceline in 2000, the business was worth a few hundred million dollars. One week later, the Nasdaq peaked, eventually sending its stock down to a dollar a share. But over 25 years later, Booking Holdings has scaled over 1000x into an over $100 billion dollar global travel behemoth. Elad Gil is joined by Booking Holdings CEO Glenn Fogel to discuss his career, from law school and Wall Street to working at Priceline through the dot-com crash, and to helping grow the business into a multifaceted, dynamic travel marketplace in the AI era. Glenn explains how leveraging AI and agents such as Priceline’s ‘Penny’ makes travel planning and customer service better, while emphasizing the importance of preserving some human support for some users. He also talks about Booking’s strategy of reinvesting over $700 million into AI and other technologies while still offering stock buybacks and dividends, the durability of their scale and complexities of dealing with a large portfolio physical properties across the world, and why upskilling is so important for employees amid concerns about AI-driven job displacement. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @bookingcom | @priceline Chapters: 00:00 – Cold Open 00:05 – Glenn Fogel Introduction 00:41 – Glenn’s Early Career 06:49 – Lessons from the Early Internet 09:24 – Deciding Factors for Exiting 10:56 – Travel Through the Lens of AI 13:30 – Agentic Travel Planning 18:59 – Agents, Token Economics, and ROI 22:46 – Booking’s Capital Investment Philosophy 25:23 – Scale as Durable Asset 29:40 – Purpose and Choosing Wisely 33:18 – AI’s Impact on Jobs 36:38 – Upskilling in the AI Era 38:36 – Public Perception of AI 40:24 – Conclusion
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July 2 · 1 hr 1 min
How Nuclear Will Unlock Energy Abundance with Valar Atomics Founder Isaiah Taylor
While the rest of the nuclear industry still relies on simulations and paper designs, Valar Atomics is busy splitting atoms. In fact, they just powered an NVIDIA Blackwell chip directly with a live nuclear reactor in order to power the world’s first nuclear powered website. Sarah Guo joins Valar Atomics founder and CEO Isaiah Taylor on-site at their reactor site in Utah to talk about how Valar is shifting nuclear energy from the theoretical to the practical by building and perfecting reactors via hardware iteration. Isaiah discusses why the US stopped building nuclear reactors in the 1970s, and how Valar utilized a little-known pathway via the Department of Energy, revived by a Trump administration executive order, to successfully develop and run their advanced reactor. He also shares Valar’s strategy for vertical integration, their venture-backed approach to financing, their giga-site plans, and why he believes cheap, abundant atomic energy has the power to vastly improve the quality of human life. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @isaiah_p_taylor | @valaratomics Chapters: 00:00 – Cold Open 00:57 – Isaiah Taylor Introduction 01:30 - Valar’s Mission and Origin 04:24 - Why Nuclear Development Stalled 07:18 - Reviving Nuclear through DoE and Executive Order 10:59 - Control Room Tour 16:17 - Misunderstandings About Nuclear 20:07 - Issues with Reliability 22:14 - Nuclear is a Hardware Execution Problem 24:32 - Timeline to Scale Production 26:32 - Introducing Ward 250 30:42 - Speed Through Simplicity 33:33 - AI Drives Nuclear Demand 35:02 - Running a Reactor with NVIDIA Blackwell 36:27 - Valar’s Nuclear Conviction 40:16 - Verticalization as Path to Scale 43:58 - Valar’s Control Skid 48:00 - Venture-Backed Nuclear 50:51 - Gigasite Strategy 53:11 - CEO Tick Rate 55:37 - Abundant Energy and Hyper-Techno Industrialism 1:01:27 – Conclusion
S1 · E167
June 26 · 36 min
Really Big Test-Time Compute in AI Changes Benchmarks, Safety and Research with OpenAI Research Scientist Noam Brown
When a new AI model drops, it’s judged based on a static benchmark grid that doesn’t account for how long the model is allowed to think. How then should we measure a model’s true capability? OpenAI research scientist Noam Brown returns to talk with Sarah Guo about his latest essay on why the AI industry’s traditional benchmark grids are broken, and how large-scale test-time compute is fundamentally changing how models are evaluated. Noam explains how, if properly scaffolded, today’s models can reason for weeks or even months on complex tasks. He also discusses real-world implications of test-time compute, from building poker solver bots to disproving legendary math conjectures. Together, they also unpack the large gaps in current AI safety frameworks, explore the bottlenecks for recursive self-improvement, and look ahead at the future of multi-agent collaboration and global knowledge sharing. Read more: Implications of Large-Scale Test-Time Compute Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @polynoamial | @OpenAI Chapters: 00:00 – Cold Open 00:43 – Noam Brown Introduction 01:23 – Why Benchmarks Are Broken 04:19 – Compute Budgets and Projections 05:34 – How Long Should Models Think? 06:47 – Benchmark-Maxxing 08:34 – Using Poker Bots as Evals 11:26 – Safety Evals When Model Capability Scales With Budget 14:41 – Release Cycle vs. Agent Runtime 17:06 – Latent Model Capability 20:59 – Limits on Recursive Self-Improvement 27:09 – Large-Scale Multi-Agent Coordination 29:11 – Competition at the Frontier 31:51 – Breaking the Benchmark Grid Equilibrium 33:29 – Why Benchmarks Should be Evaluated by Cost 36:18 – Conclusion

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