No Priors: Artificial Intelligence | Technology | Startups - Conviction

Latest Episodes:

Chasing Trillion-Dollar Companies, Founder Ambition, Token Budgets, and Regulatory Capture with Sarah & Elad Aug 06, 2026

Show notes

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.

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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

Building an Autonomous Enterprise for Real-World Services with Netic Founder Melisa Tokmak Jul 31, 2026

Show notes

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.

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

Building an Autonomous Delivery Experience with DoorDash Co-Founders Andy Fang and Stanley Tang Jul 23, 2026

Show notes

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.

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

Travel Through the Lens of AI with with Booking.com CEO Glenn Fogel Jul 09, 2026

Show notes

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.

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

How Nuclear Will Unlock Energy Abundance with Valar Atomics Founder Isaiah Taylor Jul 02, 2026

Show notes

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.

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

Really Big Test-Time Compute in AI Changes Benchmarks, Safety and Research with OpenAI Research Scientist Noam Brown Jun 26, 2026

Show notes

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.

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

Re-engineering the Semiconductor Supply Chain with Intel CEO Lip-Bu Tan Jun 18, 2026

Show notes

At 66 years old, instead of heading towards retirement, former Cadence CEO and legendary investor Lip-Bu Tan decided to take on the hardest job in tech: turning Intel around. Elad Gil and Sarah Guo sit down with Intel CEO Lip-Bu Tan to talk about why he took the job and what “saving” Intel actually looks like. Tan explains how his experience in startup culture informed his decisions to drive Intel’s culture towards faster decisions, focus on customer satisfaction, and engineer accountability. He also discusses his strategy to strengthen Intel’s balance sheet by welcoming investments from Jensen Huang’s Nvidia, Softbank, and the US government. Tan also shares his product roadmap that centers the CPU for agentic AI and inference, the collaboration with Elon Musk on Terafab, his investing framework for semiconductors, and his views on how AI is reshaping design and operations at, as he puts it, a ‘legacy spreadsheet’ tech company.

Chapters:

00:00 – Cold Open

01:01 – Lip-Bu Tan Introduction

01:24 – Why Lip-Bu Took the Reins at Intel

03:00 – Fixing Culture

04:08 – Intel’s 10-Year Vision

07:57 – Working with Elon Musk on Terafab

09:59 – Shifting Supply Chain for Semiconductors

15:34 – Limits to Scaling and Packaging

18:30 – Physical Limits to Engineering and Design

20:33 – Challenges in Semiconductor Investing

26:29 – Lessons from Cadence

28:02 – Scaling and Investment Decisions

32:03 – Rethinking Teams in AI Era

34:31 – Industrial Policy and Funding

37:25 – What Investors Misunderstand About Intel

41:10 – Where Compute Will Live

44:59 – Conclusion

Biohub: The Future of Biology is Open-Source with Co-Founders Mark Zuckerberg, Priscilla Chan, and Head of Science Alex Rives Jun 10, 2026

Show notes

Biohub started with an ambitious goal of curing, preventing, and managing all disease by the end of the century. A decade later, thanks to the convergence of frontier AI and biological data, that goal may have been too conservative. In this episode, Elad Gil and Sarah Guo sit down with Biohub co-founders Mark Zuckerberg and Priscilla Chan, alongside Biohub Head of Science Alex Rives. Together, they discuss Biohub’s $500 million virtual biology initiative, which integrates frontier AI with wet-lab work to build predictive world models of cells, proteins, and systems. They also talk about their newly announced open-source engine for digital protein and antibody design, ESMFold2; why Biohub is a nonprofit rather than a venture-backed startup; and how hierarchical simulations will soon allow doctors to treat patients at an individual, mechanistic level.

Chapters:

00:00 – Cold Open

01:02 - Mark Zuckerberg, Priscilla Chan, and Alex Rives Introduction

01:26 – Why Biohub and Their Mission

08:27 – Integrating Frontier AI and Frontier Biology

09:45 – Micro to Macro Biological Modeling

14:22 – Mechanistic Interpretiability

16:58 – Why Biohub is a Non-Profit

21:41 – Understanding How Biology Works

24:23 – Timeline for Curing All Diseases

26:25 – Translating Research to Patient Impact

28:04 – Launch of ESMFold2

32:13 – Tackling Off-Target Effects and Edge Cases

38:39 – Putting the Tech in Individual Hands

41:06 – Talent at Biohub

44:25 – What’s Next After ESMFold2

46:10 – Connecting ESMFold2 to Agentic Systems

46:51 – The Virtual Cell

49:33 – Defining Success for Biohub

51:52 – Biohub Strategy Update

56:20 – Conclusion

We Need An Ecosystem in AI, And Every Company Can Win A Place In It Jun 04, 2026

Show notes

What does it mean for a business to truly operate at the AI frontier? In a special crossover episode at Microsoft Build, Sarah Guo and Elad Gil team up with Latent Space host “swyx” to talk with Microsoft Chairman and CEO Satya Nadella about the future of AI platforms, software development, and the tech ecosystem. Satya reflects on the latest breakthroughs from Microsoft Build, the strategic shift toward multi-model harnesses, and why private evaluations (evals) are now a company’s most important intellectual property. They also discuss how autonomous AI agents are reshaping the role of software engineers, the durability of SaaS business models, and why showing communities the ROI on data centers is so critical. Plus, Satya shares his thoughts on the economic and societal impacts of the token economy, as well as the future of AI-driven education startups.

Chapters:

00:00 – Satya Nadella Introduction

01:48 – Reflections from Microsoft Build

03:12 – Microsoft’s AI Training Strategy

05:48 – Complexity of Real-World Deployment of AI

07:33 – Augmenting Human Capital

09:37 – Harnesses for Enterprise

11:49 – Developer Value

15:09 – Can Everybody Operate at the Frontier with Their Frontier Intelligence?

15:51 – Modern Definition of IP

17:38 – Future of Vendor vs. Enterprise Agents

21:48 – Near-Term Predictions on Model Pricing

24:02 – Durability of SaaS

25:58 – What Satya’s Building

28:18 – Future of Engineering Roles

30:54 – How Microsoft Can Be More Ambitious

34:36 – Data Centers and Community Impact

38:01 – AI’s Impact on Society

39:52 - AI and Education

42:28 – Conclusion

Building an AI Guardian for Enterprise with Onyx Security CEO Maxim Bar Kogan May 28, 2026

Show notes

We are now closer than ever before to living in a world where AI agents are smart enough to run our power grids and manage water supplies. How do we keep them from going rogue? Sarah Guo sits down with Maxim Bar Kogan, founder and CEO of Onyx Securities, to explore the complexities of supervising and securing autonomous agents at the enterprise level. Maxim explains Onyx’s product as an AI control plane, which oversees the permissions and flexible contexts of agents while balancing latency, cost, and reliability. He also discusses how current controls have insufficient context to monitor agent intent, tradeoffs for gradual model rollout, the need for vendor-independent oversight, and Israel’s growing AI and security talent ecosystem. Plus, why Maxim is all-in on AGI.

Chapters:

00:00 – Cold Open

00:45 – Maxim Bar Kogan Introduction

01:10 – AutoGPT and Betting on Agent Actions

05:17 – What Onyx Product Does

07:47 – State of Deployment in Large Enterprises

09:58 – Securing Agents

12:45 – Why Proxies Don’t Work

14:11 – Why Onyx Trains Its Own Models

18:38 – Onyx’s Talent Culture

21:24 – Mechanistic Interpretability

23:35 – How Onyx Builds Customer Trust