No Priors: Artificial Intelligence | Technology | Startups

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.

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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

25:10 – Mitigating Risk at the Foundational Level

27:45 – Phased Rollout of Glasswing and Daybreak

29:11 – Large Enterprise Holdouts

30:46 – Onyx and the Larger AI Security Space

32:36 – Should Labs Address Model Trust and Governance? 

36:56 – What Needs to Happen in Security

39:14 – Why Maxim is AGI-Pilled

41:15 – Conclusion

Companies in Silicon Valley from Nvidia to AMD are racing to fuel the AI revolution with postage stamp-sized AI chips. Meanwhile, a chip the size of a dinner plate just fueled a $63 billion IPO for Cerebras. Elad Gil and Sarah Guo sit down with Cerebras founder and CEO Andrew Feldman to discuss the company’s journey to making one of the largest tech go-publics in history. Andrew details the multi-year journey of pioneering wafer-scale AI computing, including surviving a brutal period of being ahead of market demand. He also explains the engineering breakthroughs that led to delivering inference speeds at 20x that of standard GPUs. Andrew then shares how a remarkable $20 billion deal with OpenAI came together in only four weeks. Plus, Andrew’s thoughts on why architecting the future of AI requires the fortitude to be a “professional David” against the Goliaths of tech.

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Chapters:

00:00 – Cold Open

00:36 – Andrew Feldman Introduction

01:19 – Cerebras’ Evolution

02:48 – Wafer-Scale Bet Pays Off

06:38 – Challenges and Breakthroughs

08:37 – Crossing the Market Chasm

10:38 – Scaling Software and Hardware

12:03 – Relevance of AI-Generated Coding

13:31 – Leadership and Hiring Culture

17:16 – When to Quit vs. Persist

19:40 – Why Cerebras Went Public

22:57 – The OpenAI Deal

25:54 – Open Source and Post-Trained Workloads

27:37 – How Speed Opens Up New Business

30:33 – Conclusion

Securing AI dominance requires more than just semiconductors; it demands a complete overhaul of how the West manages everything that goes into them, from rare earth minerals to actuators. Enter: Pax Silica. Sarah Guo and Elad Gil sit down with US Under Secretary of State for Economic Affairs Jacob Helberg to discuss the launch and expansion of Pax Silica, a 14-country economic security coalition designed to secure the entire AI supply chain. Jacob talks about the creation of a forward-deployed industrial base in the Philippines, where 4,000 acres will be developed into an “economic security zone.” He also compares and contrasts Pax Silica with China’s Belt and Road initiative, explains how the US plans to reindustrialize through automation and robotics, and explores how the Trump administration envisions making these policies durable across future presidencies. Plus, we hear why Jacob believes America to be a “global underdog.”

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Chapters:

00:00 – Cold Open

00:41 – Jacob Helberg Introduction

01:02 – Pax Silica’s Mission

03:51 – Investing in AI Chip Supply Chains

05:43 – Comparing Pax Silica to China’s Belt and Road Initiative

12:38 – Pax Silica’s Value Proposition

14:38 – US vs. Partnered Manufacturing

19:10 – Rare Earth Mineral Pricing

22:16 – Role of Venture Capital in Pax Silica

24:50 – Near vs. Long-Term Priorities

27:09 – Making AI Policy Durable

28:09 – How Policies Impact Entrepreneurs

31:00 – Trump’s Entrepreneurial Administration

33:00 – Why America is a Global Underdog

38:00 – Conclusion

The world’s first AI-take-private just proved that AI can revolutionize the real economy. Long Lake Management co-founder and CEO Alexander Taubman joins Elad Gil to discuss his firm’s agreement to acquire the legacy platform American Express Global Business Travel (Amex GBT) in a deal valued at $6.3 billion. Alexander explains the mechanics of AI-driven roll-ups, and why Long Lake chooses to acquire and transform businesses rather than simply selling them software. He also talks about how Long Lake’s horizontal AI platform, Nexus, automates workflows across diverse verticals, and how automation through AI not only powers growth for their portfolio companies, but results in both satisfied customers and employees. Plus, they explore Alexander’s vision of Amex GBT as a multi-decade compounding machine. 

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Chapters:

00:00 – Alexander Taubman Introduction

00:30 – Long Lake’s Nexus Platform

03:35 – Retention and Talent Flywheel

05:01 – Acquisition vs. Offering Software

06:57 – Building Long Lake’s Founding Team

10:37 – Taking American Express Global Business Travel Private

13:36 – Taking Berkshire Hathaway’s Approach to Management

16:37 – How AI Strategy Makes Long Lake Stand Out 

19:32 – AI Makes Services Scale

22:00 – Conclusion

Baseten CEO and co-founder Tuhin Srivastava sits down with Sarah Guo and Elad Gil to discuss the rapid growth of AI inference demand, Baseten’s 30x growth, and why inference is becoming the strategic “last market.” Tuhin Srivastava argues the application layer will persist because companies with unique user signals can encode value into workflows and post-train specialized models, citing examples like Abridge and support workflows. The conversation covers GPU capacity constraints, Baseten’s multi-cloud fabric across 18 clouds and 90 clusters, long-term contracting dynamics, the importance of the software layer for stickiness, evolving workloads, multichip possibilities, and operational lessons at scale.

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Chapters:

00:31 Baseten growth

01:55 Why the app layer wins

05:57 Serving frontier customers

07:55 Open source model mix

09:21 Chinese models and geopolitics

13:07 Custom inference dominates

14:22 Post training acquisition

17:10 When to invest in custom models

18:35 Supply crunch and data centerse

22:25 Longer GPU Contracts

24:09 What Makes a Winner

26:07 Multi Chip Future

28:19 Runtime Roadmap

31:08 Scaling Edge Cases

33:48 Hiring and Leadership

36:44 Operations Pager Culture

38:19 Efficiency Drives Demand

40:41 Concierge Everything Future

42:34 Conclusion