No Priors: Artificial Intelligence | Technology | Startups

Imagine learning chess from a grand master, or negotiating tactics from an expert FBI hostage negotiator. ElevenLabs’ voice AI technology is making that unlock possible. Sarah Guo sits down with Mati Staniszewski, co-founder of ElevenLabs, to explore how the three-year old company is transforming how humans interact with technology through voice. Mati talks about the technical challenges of building foundational audio models, the strategic thinking between conducting research and deploying products in tandem, and why voice is the ultimate interface for everything from computers to robots to immersive media. They also discuss how the coming revolution of AI personal tutors will shift agentic AI from reactive to proactive support, break down language barriers globally, and even provide the framework for agentic government services. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @elevenlabsio |@matiii Chapters: 00:00 – Mati Staniszewski Introduction 00:46 – 11 Labs: Growth and Scale 02:46 – Voice Technology and Applications 06:52 – Research and Product Development 12:36 – Voice Quality and Customer Preferences 17:54 – Agent Platform and Use Cases 23:21 – Choosing the Right Technology Partner 26:43 – The Role of Foundation Models 29:58 – Open Source Models and Future Trends 32:37 – Research and Development Focus 36:53 – Future of AI Companions and Education 41:37 – Conclusion

In just over three years, Harvey has not only scaled to nearly one thousand customers, including Walmart, PwC, and other giants of the Fortune 500, but fundamentally transformed how legal work is delivered. Sarah Guo and Elad Gil are joined by Harvey’s co-founder and president Gabe Pereyra to discuss why the future of legal AI isn’t only about individual productivity, but also about putting together complex client matters to make law firms more profitable. They also talk about how Harvey analyzes complex tasks like fund formation or M&A and deploys agents to handle research and drafting, the strategic reasoning behind enabling law firms rather than competing with them, and why AI won’t replace partners but will change law firm leverage models and training for associates. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @gabepereyra | @Harvey Chapters: 00:00 – Gabe Pereyra Introduction 00:09 – Introduction to Harvey 02:04 – Expanding Harvey’s Reach 03:22 – Understanding Legal Workflows 06:20 – Agentic AI Applications in Law 09:06 – The Future Evolution of Law Firms 13:36 – RL in Law 19:46 – Deploying Harvey and Customization 23:46 – Adoption and Customer Success 25:28– Why Harvey Isn’t Building a Law Firm 27:25 – Challenges and Opportunities in Legal Tech 29:26 – Building a Company During the Rise of Gen AI 37:24 – Hiring at Harvey 40:19 – Future Predictions 44:17 – Conclusion

The robotics industry is on the cusp of its own “GPT” moment, catalyzed by transformative research advances. Enter Memo, the first general-intelligence personal robot, focused on taking on your chores to give back your time. Sarah Guo sits down with Tony Zhao and Cheng Chi, co-founders of Sunday Robotics, to discuss the state of AI robotics. Tony and Cheng speak to the challenges they faced while developing their technology, the innovative glove system employed to scale real-world data collection, and the impact of diffusion policy and imitation learning. Plus, they talk about their 2026 in-home beta program and why personal robots are only a handful of years away from mass deployment. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @tonyzzhao | @chichengcc | @sundayrobotics Chapters: 00:00 – Tony Zhao and Cheng Chi Introduction 00:56 – State of AI Robotics 02:11 – Deploying a Robot Pre-AI 03:13 – Impact of Diffusion Policy 04:29 – Role of ACT and ALOHA 07:02 – Imitation Learning - Enter UMI 10:38 – Introducing Sunday 11:57 – Sunday’s Robot Design Philosophy 15:05 – Sunday’s Shipping Timeline 19:02 – Scale of Sunday’s Training Data 23:58 – Importance of Data Quality at Scale 24:56 – Technical Challenges 27:59 – When Will People Have Home Robots? 30:48 – Failures of Past Demos 32:34 – Sunday’s Demos 36:53 – What Sunday’s Hiring For 39:10 – Conclusion

Bringing new drugs to market is a costly, time-consuming endeavor. On top of that, most medicines fail at some point in the research and development phase. Sarah Guo is joined by Sajith Wickramasekara, co-founder and CEO of Benchling, a company that has not only become the central system of record for biotech R&D, but uses AI agents to assist scientists to help fix this broken system. Sajith details the roadblocks that impede drug development and approval, the “dot com” bust occurring in biotech, and how AI agents and simulation can help scientists experiment faster. Plus, they talk about China’s competitive rise in the pharma space, and the unique challenges of building an interdisciplinary culture that merges the worlds of science and software. Rebuild biotech for the AI era - Sajith Wickramasekara Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @sajithw | @benchling Chapters: 00:00 – Sajith Wickramasekara Introduction 00:38 – Origin and Mission of Benchling 02:08 – The Drug Development Process 03:49 – Current State of the Biotech industry 08:46 – AI’s Role in Biotech 16:14 – Benchling AI and Its Impact 18:36 – The Future of AI in Biotech 26:28 – Debunking AI Drug Discovery Myths 28:50 – Data’s Role in Biotech 29:35 – The Importance of Tools in Pharma 31:28 – AI’s Impact on Scientific Research 34:55 – Building a Biotech Company 40:18 – Interdisciplinary Collaboration in Biotech 43:06 – Tech and Biotech: Learning from Each Other 48:16 – Conclusion

Snowflake is moving beyond the data warehouse. Its new Snowflake Intelligence is an agentic platform for every employee, not just data teams. Sarah Guo sits down with Snowflake CEO Sridhar Ramaswamy to discuss his first 18 months at the helm, as well as the massive pivot to make the data giant AI-first. Sridhar talks about Snowflake Intelligence, the company's new AI agent platform, and its implications for enterprise data management. They also explore how Sridhar navigates partnerships with major tech companies, how he fosters a culture of continuous improvement within the organization, and how he envisions Snowflake’s future as an integral data-driven enterprise solution. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Snowflake Chapters: 00:00 – Sridhar Ramaswamy Introduction 00:42 – Snowflake’s Market Adaptation 03:14 – Snowflake’s Evolution and AI Integration 05:44 – Introducing Snowflake Intelligence 09:01 – Snowflake Intelligence User Experience 11:55 – Drawing the Line Between Data, Agent System, and App 13:30 – Leadership and Organizational Changes 16:19 – How Being an Investor, Entrepreneur Informed Sridhar’s Leadership 18:50 – Importance of Product-Market Fit 22:46 – Snowflake’s Strategic Positioning 27:10 – Snowflake’s Partnership Strategy 30:20 – How Sridhar Sees the ROI of AI 35:09 – How AI Changes the Ad Model 38:15 – Why LLMs Still Need Search 42:11 – Conclusion

2025 has thus far been a year of great leaps and advances in AI technology. And Sarah and Elad have spoken with some of the most enterprising founders and scientific minds in the field of AI today. So we’re revisiting a few of our favorite conversations on No Priors so far in 2025 – Winston Weinberg (Harvey), Dr. Fei-Fei Li (World Labs), Brendan Foody (Mercor), Dan Hendrycks (Center for AI Safety), Noubar Afeyan (Flagship Pioneering), Brandon McKinzie and Eric Mitchell (OpenAI o3), Isa Fulford (OpenAI), Arvind Jain (Glen), and Dr. Shiv Rao (Abridge). Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil Chapters: 00:00 – Episode Introduction 0:21 – Winston Weinberg on Leaning into New Capabilities 02:01 – Dr. Fei-Fei Li on Spatial Intelligence 04:13 – Brendan Foody on AI Disruption in the Workforce 06:10 – Dan Hendrycks on the Geopolitics of Superintelligence 08:06 – Noubar Afeyan on Entrepreneurship 10:38 – Brandon McKinzie and Eric Mitchell on Reasoning Models 12:41 – Isa Fulford on Training Deep Research 13:49 – Arvind Jain on Innovating Enterprise Search 16:21 – Dr. Shiv Rao on AI’s Human Impact 18:58 – Conclusion

For decades, the developer terminal has remained largely unchanged. But for Warp CEO and co-founder Zach Lloyd, reinventing this core tool is the key to unlocking AI agents for coding, debugging, and automating the entire development process. Zach joins Elad Gil to discuss how seeing this opportunity for innovation led to Warp’s agentic terminal for developers. Zach talks about the phases of software development, from coding by hand to the current "develop by prompt" era, and the coming age of fully automated development. Plus, Zach and Elad explore the deep philosophical questions around intelligence versus consciousness in AI models, and what it would take to believe a computer program is truly aware. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @zachlloydtweets | @warpdotdev Chapters: 00:00 – Zach Lloyd Introduction 00:32 – AI, Intelligence, and Consciousness 06:55 – What Warp Does 07:38 – Benefits of the Terminal as a Launchpoint 08:27 – Features Driving Warp’s Adoption 09:12 – Zach’s View of the Coding Market 10:27 – Evolution of Coding Development 12:45 – Importance of Senior Engineer Expertise 14:11 – Future of Security and Other Dev Tools 22:22 – Why Zach Focused on the Terminal 23:52 – The Future of the Model Layer 25:36 – What Zach’s Excited About in the AI Dev World 27:18 – Conclusion

With demand from AI for energy already exploding, our electric grid is facing a crisis. Base Power CEO and co-founder Zach Dell is ready to re-architect its future from the ground up. Zach sits down with Elad Gil to talk about Base Power’s recent $1 billion fundraise from major investors. Zach discusses the role of energy across industries, as well as Base Power's mission to lower electricity costs through vertical integration. Zach and Elad also explore the future of energy, the role of batteries in transforming the grid, and the regulatory challenges facing the energy industry. Plus, Zach pitches why top talent should make their careers in energy generation. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ZachBDell | @basepowerco Chapters: 00:00 – Zach Dell Introduction 00:50 – Base Power’s Vision 02:15 – Base Power’s Products and Services 04:00 – What Drew Zach to Working on Power 05:12 – Base Power’s Founding Team 06:58 – Base Power’s Hiring Needs 08:02 – How Zach Hired an Awesome Founding Team 09:51 – How Do We Meet Energy Demands? 12:58 – How Viable is Nuclear Energy? 17:04 – Global Energy Cost Dynamics 17:41 – Future of AI Training Centers 18:32 – What Will Drive Energy Buildout 20:38 – Drivers of Energy Transmission Cost 22:30 – Regulation and the Energy Industry 23:52 – What Zach is Optimistic About in Energy 24:42 – Cultivating Base Power’s Culture 27:26 – Zach’s Philosophy on Capitalization 30:00 – How Base Power Uses Scale 31:57 – Conclusion

The AI industry is obsessed with making models smarter. But what if they’re building the wrong kind of intelligence? In launching his new venture, humans&, Eric Zelikman sees an opportunity to shift the focus from pure IQ to building models with EQ. Sarah Guo is joined by Eric Zelikman, formerly of Stanford and xAI, who shares his journey from AI researcher to founder. Eric talks about the challenges of building human-centric AI, integrating long-term memory in models, and the importance of creating AI systems that work collaboratively with humans to unlock their full potential. Plus, Eric shares his views on abunance and what he’s looking for in talent for humans&. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ericzelikman Chapters: 00:00 – Eric Zelikman Introduction 00:29 – Eric’s Early Interest in AI 01:29 – Challenges in AI and Automation 02:25 – Research Contributions 06:14 – Q-STaR and Scaling Up AI 08:14 – Current State of AI Models 15:23 – Human-Centric AI and Future Directions 22:08 – Eric’s New Venture: humans& 35:33 – Recruitment Goals for humans& 36:57 – Conclusion

Between the future of search, the biggest threats in cybersecurity, and the jobs and platforms of tomorrow, Nikesh Arora sees one common thread connecting and transforming them all—AI. Sarah Guo and Elad Gil sit down with Nikesh Arora, CEO of cybersecurity giant Palo Alto Networks and former Chief Business Officer of Google, to talk about a wide array of topics from agentic AI to leadership. Nikesh dives into the future of search, the disruptive potential of AI agents for existing business models, and how AI has both compressed the timeline for cyberattacks as well as fundamentally shifted defense strategies in cybersecurity. Plus, Nikesh shares his leadership philosophy, and why he’s so optimistic about AI. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @nikesharora | @PaloAltoNtwks Chapters: 00:00 – Nikesh Arora Introduction 00:39 – Nikesh on the Future of Search 04:46 – Shifting to an Agentic Model of Search 08:12 – AI-as-a-Service 16:55 – State of Enterprise Adoption 20:15 – Gen AI and Cybersecurity 27:35 – New Problems in Cybersecurity in the AI Age 29:53 – Deepfakes, Spearfishing, and Other Attacks 32:56 – Expanding Products at Palo Alto 35:49 – AI Agents and Human Replaceability 44:28 – Nikesh’s Thoughts on Growth at Scale 46:52 – Nikesh’s Leadership Tips 51:14 – Nikesh on Ambition 54:18 – Nikesh’s Thoughts on AI 58:21 – Conclusion

What if kids could master their academics in just two hours a day and spend the rest of their time developing real-world skills they’re passionate about? Joe Liemandt, founder of the software company Trilogy, is doing just that. Sarah Guo and Elad Gil are joined by Joe Liemandt, principal of Alpha School, to discuss his AI-driven vision of reinventing K-12 education. Joe talks about the strategies that Alpha School employs: reducing the traditional six-hour school day to two, replacing teachers with “Guides,” using financial incentives as motivation, and dedicating the remainder of the school day to project-based workshops that reflect the students’ passions. Together, they also examine Joe’s plan to scale Alpha School, the youth mental health crisis, and why edtech so far has failed. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @AlphaSchoolATX Chapters: 00:00 – Joe Liemandt Introduction 00:27 – From Trilogy to Alpha School 02:45 – How Joe Changed His Mind About Alpha School 04:16 – Reenvisioning the School Day 09:06 – An Example Day at Alpha School 20:13 – Educating Based on Motivations 22:56 – Incentives-Based Learning 24:40 – Standards for Guides 26:39 – Extrinsic vs. Intrinsic Motivators 35:12 – Tackling Learning Differences 39:13 – Alpha School Pricing Structure 43:08 – Education Tech at Alpha School 44:54 – Rebuilding Education in the AI Age 48:43 – Reforming Education Policy 56:25 – Ed Tech as a Product 58:58 – Fixing Gaps in Education 59:45 – Why Education is Joe’s Mission 01:01:49 – Conclusion

The traditional call center may soon be a thing of the past. Jessie Zhang is building AI agents designed to replace monotonous human labor and transform how consumers interact with brands. Elad Gil sits down with Jesse Zhang, co-founder and CEO of Decagon, an AI agent company at the forefront of AI customer service. Jesse talks about how Decagon secured large enterprise clients and the impact of its AI agents, his journey as a second-time founder, and Decagon’s company culture. Plus, they discuss what the future of agentic customer service may look like. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @thejessezhang | @DecagonAI Chapters: 00:00 – Jesse Zhang Introduction 00:30 – Decagon’s Services 01:11 – Decagon’s Customers and Growth 02:41 – Productivity Gains with Decagon 03:33 – How Decagon Integrates in Customer Workflows 04:25 – Jesse’s Second Time Founder Story 05:41 – Jesse’s Hiring Philosophy 09:13 – Counter-intuitive Advice for Founders 11:19 – How Decagon Thinks About Talent 14:12 – Areas for Longer Term Planning 15:37 – Decagon’s Path to Customer Service 16:57 – Thoughts on Pushing Into the Application Layer 19:40 – What Decagon Does Uniquely 22:05 – Pricing Services in the AI Age 24:46 – How Decagon Sees Customer Service 25:53 – Defining Long-Term Success for Decagon 27:41 – Jesse’s Views on an Agentic Future 31:22 – Conclusion

From negotiating with world leaders to partnering with top entrepreneurs, businessman and investor Jared Kushner has traveled the unique path of bringing private sector knowledge to government work and back again. Jared Kushner joins Sarah Guo and Elad Gil to cover a wide range of topics, from his founding of investment firm Affinity Partners, to his time in government, to his new AI venture BrainCo. Jared discusses Affinity Partners’ mission and strategy, how he has leveraged his government experience in business and investing, and the geopolitics of technological advancements like AI. Plus, he makes a case for why private sector talent should do “tours of duty” in government. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jaredkushner Chapters: 00:00 – Jared Kushner Introduction 00:30 – Starting Affinity Partners Post-Government 01:59 – Value of Global Perspective 03:34 – Ventures with Affinity 05:14 – Evaluating Investments Via Macro Trends 09:09 – Undervalued Countries 12:32 – Origins of BrainCo 16:50 – BrainCo Use Cases 23:49 – BrainCo’s Biggest Challenge 24:47 – Determining Customer Fit 26:39 – AI and Policy 30:03 – Middle East and AI 31:59 – Jared’s Experience in Middle East Diplomacy 40:16 – Brokering Peace Post-October 7th 43:52 – Making Deals with Middle Eastern Partners 47:14 – Jared and Ivanka’s Partnership 49:18 – Benefits of Joining Public Sector from the Private Sector 52:07 – Jared’s Pitch for Serving in Government 56:25 – Jared’s Leadership Style 58:24 – Conclusion

How does a new technology get adopted by 40% of American doctors in just 18 months? In an era where the golden age of biotechnology has also created a dark age of physician burnout, OpenEvidence found the answer by fundamentally changing how doctors access critical information. OpenEvidence founder Daniel Nadler sits down with Sarah Guo and Elad Gil to discuss how his company solved the semantic search problem in medicine. He talks about the strategy of treating doctors as consumers, striking the balance of keeping patients in the loop in medical conversations, and how technology will reshape both medicine and medical education. Plus, Daniel gives his thoughts on the roots of motivation, as well as his philosophy for recruitment. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @EvidenceOpen Chapters: 00:00 – Daniel Nadler Introduction 00:08 – OpenEvidence’s Success 01:54 – How OpenEvidence Works 06:35 – Dealing with Ambiguity 11:37 – Treating Knowledge Workers as Consumers 15:53 – Balancing Keeping Patients in the Loop 19:28 – How Technology May Shape the Future of Medicine 22:12 – How Technology Will Change Medical Education 30:40 – Examining Consumer Adoption of Preventative Health Measures 36:02 – Lessons for Other Fields 37:27 – Rationalism vs. Will 41:13 – Daniel’s Thoughts on Motivation 42:44 – Daniel’s Recruiting Philosophy 44:48 – Conclusion

AI doomers say that the technology will be the ultimate job-killer. But Jacob Helberg wants people to see AI as a tech that will boost, not replace, human workers and give them superpowers. Under Secretary of State for Economic Growth, Energy, and the Environment Jacob Helberg joins Sarah Guo and Elad Gil to talk about AI’s role in reshoring manufacturing in America, supply chain security, and transforming the US energy grid. He also discusses the CapEx revolution, why he sees opportunity for tech and energy partnerships in the Middle East, and the path to more nuclear energy for the US. Plus, the three explore what the “superintelligence century” could look like. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jacobhelberg Chapters: 00:00 – Jacob Helberg Introduction 00:50 – Jacob’s Agenda for Capitol Hill 01:53 – Reshoring the American Supply Chain 04:38 – Areas of CapEx Growth 06:56 – Importance of Supply Chain Security 08:52 – Reshoring Rare Earth Minerals 11:12 – How AI Can Help America Reindustrialize 15:37 – AI and Productivity Gains 17:38 – The Superintelligence Century 22:56 – Creating an Open Source AI Ecosystem 24:41 – The Middle East and AI 26:24 – Growing Energy Resources in the US 28:28 – The Path to More Nuclear Energy in the US 35:50 – Essential Domains for Strategy and Security 38:20 – The Tech Industry and the Administration 40:29 – Conclusion

Andrew Ng has always been at the bleeding edge of fast-evolving AI technologies, founding companies and projects like Google Brain, AI Fund, and DeepLearning.AI. So he knows better than anyone that founders who operate the same way in 2025 as they did in 2022 are doing it wrong. Sarah Guo and Elad Gil sit down with Andrew Ng, the godfather of the AI revolution, to discuss the rise of agentic AI, and how the technology has changed everything from what makes a successful founder to the value of small teams. They talk about where future capability growth may come from, the potential for models to bootstrap themselves, and why Andrew doesn’t like the term “vibe coding.” Also, Andrew makes the case for why everybody in an organization—not just the engineers—should learn to code. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @AndrewYNg Chapters: 00:00 – Andrew Ng Introduction 00:32 – The Next Frontier for Capability Growth 01:29 – Andrew’s Definition of Agentic AI 02:44 – Obstacles to Building True Agents 06:09 – The Bleeding Edge of Agentic AI 08:12 – Will Models Bootstrap Themselves? 09:05 – Vibe Coding vs. AI Assisted Coding 09:56 – Is Vibe Coding Changing the Nature of Startups? 11:35 – Speeding Up Project Management 12:55 – The Evolution of the Successful Founder Profile 19:23 – Finding Great Product People 21:14 – Building for One User Profile vs. Many 22:47 – Requisites for Leaders and Teams in the AI Age 28:21 – The Value of Keeping Teams Small 32:13 – The Next Industry Transformations 34:04 – Future of Automation in Investing Firms and Incubators 37:39 – Technical People as First Time Founders 41:08– Broad Impact of AI Over the Next 5 Years 41:49 – Conclusion

What would it take to challenge Nvidia? SemiAnalysis Founder and CEO Dylan Patel joins Sarah Guo to answer this and other topical questions around the current state of AI infrastructure. Together, they explore why Dylan loves Android products, predictions around OpenAI’s open source model, and what the landscape of neoclouds looks like. They also discuss Dylan’s thoughts on bottlenecks for expanding AI infrastructure and exporting American AI technologies. Plus, we find out what question Dylan would ask Mark Zuckerberg. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @dylan522p | @SemiAnalysis_ Chapters: 00:00 – Dylan Patel Introduction 00:31 – Dylan’s Love for Android Products 02:10 – Predictions About OpenAI’s Open Source Model 06:50 – Implications of an American Open Source Model for the Application Ecosystem 10:48 – Evolution of Neoclouds 17:26 – What It Would Take to Challenge Nvidia 27:43 – What Would an Nvidia Challenger Look Like? 28:18 – Understanding Operational and Power Constraints for Data Centers 34:48 – Dylan’s View on the American Stack 43:01 – What Dylan Would Ask Mark Zuckerberg 44:22 – Poker and AI Entrepreneurship 46:51 – Conclusion

Cloudflare has spent nearly fifteen years making the Internet faster, more reliable, and more secure. So now that AI systems are changing the way we interact with the Internet, Cloudflare wants to help level the playing field for content creators. Sarah Guo and Elad Gil sit down with Matthew Prince, co-founder and CEO of Cloudflare to discuss the evolution of the internet from search to AI, including Cloudflare’s role in facilitating that shift. Matthew talks about how AI assistants are changing the shape of the Internet, the problems Google created by making traffic the arbiter of content value, and how he sees Cloudflare’s part in facilitating the new content marketplace for the mutual benefit of creators and AI companies. Plus, a look towards how agentic infrastructure may unfold in the near future. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @eastdakota | @Cloudflare Chapters: 00:00 – Matthew Prince Introduction 00:37 – Cloudflare’s Role in Securing the Internet 02:08 – The Road to Cloudflare’s Dominance 03:20 – The Internet’s Shift from Search to AI 06:34 – Role of Agents and Content on the New Web 09:44 – Reshaping the Content Market Online 13:05 – De-emphasizing Traffic as a Proxy for Value 18:04 – Will We Run Out of Quality Human-Generated Content? 20:01 – Scaling the Value of Content in the AI Age 22:32 – Cloudflare’s Approach to Inference 24:55 – How Cloudflare Responds to Market Demand 26:04 – Open vs. Closed Models 27:21 – Path to the New Marketplace for Content 30:58 – Advice for Content Creators 32:47 – Exploring the Timeline for Running Models Locally 40:07 – The Future of Agentic Infrastructure 44:52 – Conclusion

Sriram Krishnan was never interested in policy. But after seeing a gap in AI knowledge at senior levels of government, he decided to lend his expertise to the tech-friendly Trump administration. Senior White House Policy Advisor on AI Sriram Krishnan joins Elad Gil and Sarah Guo to talk about America’s AI Action Plan, a recent executive order that outlines how America can win the AI race and maintain its AI supremacy. Sriram discusses why winning the AI race is important and what that looks like, as well as the core goals of the Action Plan that he helped to author. Together, they explore how AI is the latest iteration of American cultural exportation and soft power, the bottlenecks in upgrading America’s energy infrastructure, and the importance of America owning the “full stack” from GPUs and models to agents and software. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @skrishnan47 | @sriramk Chapters: 00:00 – Sriram Krishnan Introduction 01:00 – Sriram’s Role in Government 03:43 – Impetus for the America AI Action Plan 06:14 – What Winning the AI Race Looks Like 10:36 – Algorithms and Cultural Bias 12:26 – Main Tenets of the America AI Action Plan 19:13 – Infrastructure and Energy Needs for AI 22:56 – Manufacturing, Supply Chains, and AI 24:52 – Ensuring American Dominance in Robotics 26:30 – Translating Policy to Industry and the Economy 29:30 – Should the US Be a Technocracy? 32:33 – Understanding the Argument Against Open Source Models 36:07 – Conclusion

In the generative AI revolution, quality data is a valuable commodity. But not all data is created equally. Sarah Guo and Elad Gil sit down with SurgeAI founder and CEO Edwin Chen to discuss the meaning and importance of quality human data. Edwin talks about why he bootstrapped Surge instead of raising venture funds, the importance of scalable oversight in producing quality data, and the work Surge is doing to standardize human evals. Plus, we get Edwin’s take on what Meta’s investment into Scale AI means for Surge, as well as whether or not he thinks an underdog can catch up with OpenAI, Anthropic, and other dominant industry players. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @echen | @HelloSurgeAI Chapters: 00:00 – Edwin Chen Introduction 00:41 – Overview of SurgeAI 02:28 – Why SurgeAI Bootstrapped Instead of Raising Funds 07:59 – Explaining SurgeAI’s Product 09:39 – Differentiating SurgeAI from Competitors 11:27 – Measuring the Quality of SurgeAI’s Output 12:25 – Role of Scalable Oversight at SurgeAI 14:02 – Challenges of Building Rich RL Environments 16:39 – Predicting Future Needs for Training AI Models 17:29 – Role of Humans in Data Generation 21:27 – Importance of Human Evaluation for Quality Data 22:51 – SurgeAI’s Work Toward Standardization of Human Evals 23:37 – What the Meta/ScaleAI Deal Means for SurgeAI 24:35 – Edwin’s Underdog Pick to Catch Up to Big AI Companies 24:50 – The Future Frontier Model Landscape 26:25 – Future Directions for SurgeAI 29:29 – What Does High Quality Data Mean? 32:26 – Conclusion

Superintelligence, at least in an academic sense, has already been achieved. But Misha Laskin thinks that the next step towards artificial superintelligence, or ASI, should look both more user and problem-focused. ReflectionAI co-founder and CEO Misha Laskin joins Sarah Guo to introduce Asimov, their new code comprehension agent built on reinforcement learning (RL). Misha talks about creating tools and designing AI agents based on customer needs, and how that influences eval development and the scope of the agent’s memory. The two also discuss the challenges in solving scaling for RL, the future of ASI, and the implications for Google’s “non-acquisition” of Windsurf. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @MishaLaskin | @reflection_ai Chapters: 00:00 – Misha Laskin Introduction 00:44 – Superintelligence vs. Super Intelligent Autonomous Systems 03:26 – Misha’s Journey from Physics to AI 07:48 – Asimov Product Release 11:52 – What Differentiates Asimov from Other Agents 16:15 – Asimov’s Eval Philosophy 21:52 – The Types of Queries Where Asimov Shines 24:35 – Designing a Team-Wide Memory for Asimov 28:38 – Leveraging Pre-Trained Models 32:47 – The Challenges of Solving Scaling in RL 37:21 – Training Agents in Copycat Software Environments 38:25 – When Will We See ASI? 44:27 – Thoughts on Windsurf’s Non-Acquisition 48:10 – Exploring Non-RL Datasets 55:12 – Tackling Problems Beyond Engineering and Coding 57:54 – Where We’re At in Deploying ASI in Different Fields 01:02:30 – Conclusion

As a three-time founder, Parker Conrad has one piece of advice for aspiring entrepreneurs—don’t do it. The Rippling co-founder and CEO joins Sarah Guo to talk about what he learned from the crash at Zenefits, why most advice to founders is wrong, and how building a real platform—not a point solution—is the only way to win in SaaS. The two get into founder psychology, the myth of learning from failure, and what true ownership looks like inside a company. He also shares why AI won’t shrink teams anytime soon, what people misunderstand about vertical software, and why ambition trumps efficiency with long-lasting companies. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @parkerconrad Chapters: 00:00 Introduction to Parker Conrad 00:33 Lessons from Zenefits to Rippling 01:54 The Psychology of Founding a Company 07:56 Rippling's Ambitious Vision 10:41 Building a Platform Company 15:05 Challenges and Strategies in Scaling 30:36 AI's Impact on Software Development 42:06 Public vs. Private: Rippling's Future 44:19 Conclusion

AI has already fueled breakthroughs in biotechnology—but now, further advances in AI are poised to fuel pharmaceutical discoveries as well. Sarah Guo sits down with Joshua Meier and Jack Dent, co-founders of Chai Discovery, whose newly launched Chai-2 designs bespoke antibodies that bind to their targets at a jaw-dropping 20% rate. Jack and Joshua talk about the implications for Chai-2’s success rate at discovering antibodies for the pharmaceutical industry, how structure prediction is pivotal in making the model work, and future potential for using the model to optimize other molecular properties. Plus, they talk about what they believe bioscientists should be learning to best utilize Chai-2’s technology. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @_jackdent | @joshim5 Chapters: 00:00 – Joshua Meier and Jack Dent Introduction 01:09 – Genesis of Chai Discovery 06:12 – Chai-2 Model 10:13 – Criteria for Specifying Targets for Chai-2 13:12 – How the Chai-2 Model Works 16:12 – Emergent Vocabulary from Chai-2 18:15 – Hopes for Chai-2’s Impact 20:33 – Reception of the Chai-2 Model 22:16 – Future of Wet Lab Screening and Biotech 27:08 – Optimizing Other Molecule Properties 31:37 – Where Chai Invests From Here 36:20 – What Bioscientists Should Learn for Chai-2 40:23 – How Jack and Josh Oriented to the Biotech Space 43:38 – Platform Investment and Chai-2 46:53 – Scaling Chai Discovery 48:21 – Hiring at Chai Discovery 49:09 – Conclusion

Much of the scientific process involves searching. But rather than continue to rely on the luck of discovery, Google DeepMind has engineered a more efficient AI agent that mines complex spaces to facilitate scientific breakthroughs. Sarah Guo speaks with Pushmeet Kohli, VP of Science and Strategic Initiatives, and research scientist Matej Balog at Google DeepMind about AlphaEvolve, an autonomous coding agent they developed that finds new algorithms through evolutionary search. Pushmeet and Matej talk about how AlphaEvolve tackles the problem of matrix multiplication efficiency, scaling and iteration in problem solving, and whether or not this means we are at self-improving AI. Together, they also explore the implications AlphaEvolve has to other sciences beyond mathematics and computer science. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @pushmeet | @matejbalog Chapters: 00:00 Pushmeet Kohli and Matej Balog Introduction 0:48 Origin of AlphaEvolve 02:31 AlphaEvolve’s Progression from AlphaGo and AlphaTensor 08:02 The Open Problem of Matrix Multiplication Efficiency 11:18 How AlphaEvolve Evolves Code 14:43 Scaling and Predicting Iterations 16:52 Implications for Coding Agents 19:42 Overcoming Limits of Automated Evaluators 25:21 Are We At Self-Improving AI? 28:10 Effects on Scientific Discovery and Mathematics 31:50 Role of Human Scientists with AlphaEvolve 38:30 Making AlphaEvolve Broadly Accessible 40:18 Applying AlphaEvolve Within Google 41:39 Conclusion

When will fully autonomous vehicles see widespread adoption? According to Applied Intuition, that future is closer than you may think. Applied Intuition’s CEO, Qasar Younis, and CTO, Peter Ludwig, talk with Elad Gil about how now is the best time to both work on self-driving vehicle technology and monetize it. Qasar and Peter discuss the advantages of developing their own OS in-house for their autonomous applications, self-driving technology’s potential to drive re-shoring of vehicle manufacturing to the United States, and how best to gauge the bar for safety in autonomous systems. Plus, they explore how self-driving technology may reshape the designs of not only vehicles, but cities themselves. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @qasar | @AppliedInt Chapters: 00:00 Qasar Younis and Peter Ludwig Introduction 01:28 A Primer on Applied Intuition 11:08 Applied Intuition’s Customers 12:04 Impact of Chinese Vehicles Manufacturers 15:44 EV Policies in the European Market 20:49 Can Robotics and Automation Re-Shore Vehicle Manufacturing? 21:53 Training Models for Autonomous Vehicles 26:41 Gauging the Bar for Autonomous Vehicles Safety 32:03 Timeline for Large-Scale Autonomous Vehicle Adoption 36:28 Rethinking Urban Design for Autonomous Vehicles 38:47 How Applied Intuition Uses AI for Tooling and OS 42:09 Designing for User Experience 43:31 Applied Intuition’s Hiring Strategy 45:01 Conclusion