Sanjit Biswas is one of the rare founders who has scaled AI in the physical world – first with Meraki, and now with Samsara, a $20B+ public company with sensors deployed across millions of vehicles and job sites. Capturing 90 billion miles of driving data each year, Samsara operates at a scale matched only by a small handful of companies. Sanjit discusses why physical AI is fundamentally different from cloud-based AI, from running inference on two- to ten-watt edge devices to managing the messy diversity of real-world data—weather, road conditions, and the long tail of human behavior.

He also shares how advances in foundation models unlock new capabilities like video reasoning, why distributed compute at the edge still beats centralized data centers for many autonomy workloads, and how AI is beginning to coach frontline workers—not just detect risk, but recognize good driving and improve fuel efficiency. Sanjit also explains why connectivity, sensors, and compute were the original “why now” for Samsara, and how those compounding curves will reshape logistics, field service, construction, and every asset-heavy industry.

Hosted by Sonya Huang and Pat Grady, Sequoia Capital

fal is building the infrastructure layer for the generative media boom. In this episode, founders Gorkem Yurtseven, Burkay Gur, and Head of Engineering Batuhan Taskaya explain why video models present a completely different optimization problem than LLMs, one that is compute-bound, architecturally volatile, and changing every 30 days. They discuss how fal's tracing compiler, custom kernels, and globally distributed GPU fleet enable them to run more than 600 image and video models simultaneously, often faster than the labs that trained them. The team also shares what they’re seeing from the demand side: AI-native studios, personalized education, programmatic advertising, and early engagement from Hollywood. They argue that generative video is following a trajectory similar to early CGI—initial skepticism giving way to a new medium with its own workflows, aesthetics, and economic models.Hosted by Sonya Huang, Sequoia Capital

Nathan Sobo has spent nearly two decades pursuing one goal: building an IDE that combines the power of full-featured tools like JetBrains with the responsiveness of lightweight editors like Vim. After hitting the performance ceiling with web-based Atom, he founded Zed and rebuilt from scratch in Rust with GPU-accelerated rendering. Now with 170,000 active developers, Zed is positioned at the intersection of human and AI collaboration. Nathan discusses the Agent Client Protocol that makes Zed "Switzerland" for different AI coding agents, and his vision for fine-grained edit tracking that enables permanent, contextual conversations anchored directly to code—a collaborative layer that asynchronous git-based workflows can't provide. Nathan argues that despite terminal-based AI coding tools visual interfaces for code aren't going anywhere, and that source code is a language designed for humans to read, not just machines to execute.

Hosted by Sonya Huang and Pat Grady, Sequoia Capital

Alex Kendall founded Wayve in 2017 with a contrarian vision: replace the hand-engineered autonomous vehicle stack with end-to-end deep learning. While AV 1.0 companies relied on HD maps, LiDAR retrofits, and city-by-city deployments, Wayve built a generalization-first approach that can adapt to new vehicles and cities in weeks. Alex explains how world models enable reasoning in complex scenarios, why partnering with automotive OEMs creates a path to scale beyond robo-taxis, and how language integration opens up new product possibilities. From driving in 500 cities to deploying with manufacturers like Nissan, Wayve demonstrates how the same AI breakthroughs powering LLMs are transforming the physical economy.

Hosted by: Pat Grady and Sonya Huang

When Google launched Nano Banana, it instantly became a global phenomenon, introducing an image model that finally made it possible for people to see themselves in AI-generated worlds. In this episode, Nicole Brichtova and Hansa Srinivasan, the product and engineering leads behind Nano Banana, share the story behind the model’s creation and what it means for the future of visual AI.

Nicole and Hansa discuss how they achieved breakthrough character consistency, why human evaluation remains critical for models that aim to feel right, and how “fun” became a gateway to utility. They explain the craft behind Gemini’s multimodal design, the obsession with data quality that powered Nano Banana’s realism, and how user creativity continues to push the technology in unexpected directions—from personal storytelling to education and professional design. The conversation explores what comes next in visual AI, why accessibility and imagination must evolve together, and how the tools we build can help people capture not just reality but possibility.

Hosted by: Stephanie Zhan and Pat Grady, Sequoia Capital

The OpenAI Sora 2 team (Bill Peebles, Thomas Dimson, Rohan Sahai) discuss how they compressed filmmaking from months to days, enabling anyone to create compelling video. Bill, who invented the diffusion transformer that powers Sora and most video generation models, explains how space-time tokens enable object permanence and physics understanding in AI-generated video, and why Sora 2 represents a leap for video. Thomas and Rohan share how they're intentionally designing the Sora product against mindless scrolling, optimizing for creative inspiration, and building the infrastructure for IP holders to participate in a new creator economy. The conversation goes beyond video generation into the team’s vision for world simulators that could one day run scientific experiments, their perspective on co-evolving society alongside technology, and how digital simulations in alternate realities may become the future of knowledge work.

Hosted by: Konstantine Buhler and Sonya Huang, Sequoia Capital

Recorded live at Sequoia’s Europe100 event: Michael Kagan, co-founder of Mellanox and CTO of Nvidia, explains how the $7 billion Mellanox acquisition helped transform Nvidia from a chip company into the architect of AI infrastructure. Kagan breaks down the technical challenges of scaling from single GPUs to 100K and eventually million-GPU data centers. He reveals why network performance—not just compute power—determines AI system efficiency. He discusses the shift from training to inference workloads, and his vision for AI as humanity's "spaceship of the mind," and why he thinks AI may help us discover laws of physics we haven’t yet imagined.

Hosted by Sonya Huang and Pat Grady

Irregular co-founder Dan Lahav is redefining what cybersecurity means in the age of autonomous AI. Working closely with OpenAI, Anthropic, and Google DeepMind, Dan, co-founder Omer Nevo and team are pioneering “frontier AI security”—a proactive approach to safeguarding systems where AI models act as independent agents.

Dan shares how emergent behaviors, from models socially engineering each other to outmaneuvering real-world defenses like Windows Defender, signal a coming paradigm shift. Dan explains why tomorrow’s threats will come from AI-on-AI interactions, why anomaly detection will soon break down, and how governments and enterprises alike must rethink defenses from first principles as AI becomes a national security layer.

Hosted by: Sonya Huang and Dean Meyer, Sequoia Capital

00:00 Introduction 03:07 The Future of AI Security 03:55 Thought Experiment: Security in the Age of GPT-10 05:23 Economic Shifts and AI Interaction 07:13 Security in the Autonomous Age 08:50 AI Model Capabilities and Cybersecurity 11:08 Real-World AI Security Simulations 12:31 Working with AI Labs 32:34 Enterprise AI Security Strategies 40:03 Governmental AI Security Considerations 43:41 Final Thoughts

Ping Wu built Google's contact center business before becoming CEO of Cresta, where he's pioneering a unique approach to contact center transformation. Rather than full automation Ping advocates a dual approach, automating what's ready while using AI to assist humans with the rest. He makes the case for an abundance mindset—imagining new customer experiences like talking to airline apps or turning synchronous interactions asynchronous. Ping breaks down the technical challenges of deploying Contact Center AI at scale, from solving latency to orchestrating 20+ models in real-time. Sequoia’s Doug Leone shares his framework for building AI companies at speed and why he believes we're at the front end of an Industrial Revolution 2.0.

Hosted by: Sonya Huang and Doug Leone, Sequoia Capital

00:00 Introduction

01:13 The Evolution of Contact Centers

02:05 Debating AI's Impact on Call Centers

04:07 Challenges and Opportunities in Contact Centers

08:14 Technological Waves in Contact Centers

11:10 AI vs Human Agents: The Future

13:35 Customer Experience and AI

16:33 The Role of Data in AI Automation

19:05 Competing in the AI Space

22:34 Building a Company in the AI Era

24:05 Instilling Speed in AI Companies

24:53 Management Experience and Growth Challenges

26:01 Identifying Leadership Potential

26:37 Cresta's Leadership Transition

28:34 Future Goals for Cresta

29:56 AI Market Cycles and Investment

35:38 Cresta's Technical Stack

45:11 AI's Impact on Business Communication

As CTO of Block, Dhanji Prasanna has overseen a dramatic enterprise AI transformation, with engineers saving 8-10 hours a week through AI automation. Block’s open-source agent goose connects to existing enterprise tools through MCP, enabling everyone from engineers to sales teams to build custom applications without coding. Dhanji shares how Block reorganized from business unit silos to functional teams to accelerate AI adoption, why they chose to open-source their most valuable AI tool and why he believes swarms of smaller AI models will outperform monolithic LLMs.

Hosted by: Sonya Huang and Roelof Botha, Sequoia Capital

Mentioned in the episode:

• goose: Block’s open-source, general-purpose AI agent used across the company to orchestrate workflows via tools and APIs. 

• Model Context Protocol (MCP): Open protocol (spearheaded by Anthropic) for connecting AI agents to tools; goose was an early adopter and helped shape.

• bitchat: Decentralized chat app written by Jack Dorsey

• Swarm intelligence: Research direction Dhanji highlights for AI’s future where many agents (geese) collaborate to build complex software beyond a single-agent copilot.

• Travelling Salesman Problem: Classic optimization problem cited by Dhanji in the context of a non-technical user of goose solving a practical optimization task.

• Amara’s Law: The idea, originated by futurist Roy Amara in 1978, that we overestimate tech impact short term and underestimate long term.

  
  

  00:00 Introduction

  01:48 AI: Friend or Foe?

  03:13 Block's Journey with AI and Technology

  04:47 Block's Diverse Product Range

  07:04 Driving AI at Block

  14:28 The Evolution of Goose

  27:45 Integrating Goose with Existing Systems

  28:23 Goose's Learning and Recipe Feature

  29:41 Tool Use and LLM Providers

  31:40 Impact of AI on Developer Productivity

  34:37 Block's Commitment to Open Source

  39:09 Future of AI and Swarm Intelligence

  43:05 Remote Work at Block

  45:15 Vibe Coding and AI in Development

  48:43 Making Goose More Accessible

  51:28 Generative AI in Customer-Facing Products

  54:09 Design and Engineering at Block

  55:38 Predictions for the Future of AI

  
  

  
  

Elias Torres has been building AI systems since 1999, from chatbots at IBM to co-founding Drift and now Agency. He believes businesses are caught in an expectation mismatch—demanding AI while rejecting it due to imperfection anxiety. Drawing from his experience scaling HubSpot, Elias explains why human-led customer experience doesn’t scale and how Agency is building AI-first solutions that work autonomously. His contrarian approach focuses on the back-end customer experience rather than front-end AI SDRs, aiming to “deprogram the entire business world” from inefficient human-dependent processes.

Hosted by: Sonya Huang and Pat Grady, Sequoia Capital

Mentioned in the episode:

• Lookery: David Cancel’s first startup that Elias joined after IBM; shut down in 2009

• Performable: Elias and David’s second startup, acquired by HubSpot in 2011

• Drift: Elias and David Cancel’s third startup, merged with Salesloft in 2024

• Klaviyo: B2C CRM company started by Andrew Bialecki after working with Elias at HubSpot

• Secret: Short-lived anonymous messaging app that inspired one of Drift’s early iterations

• Tatajuba: Kitesurfing destination in Jericoacoara, Brazil where Elias (briefly) considered retirement

00:00 Introduction 01:50 AI and Customer Expectations 03:36 Managing Emails with AI 07:21 Elias' Personal Journey 11:27 Early Career 14:28 Joining HubSpot and Scaling Challenges 16:31 Hiring Exceptional Talent 18:53 Founding Drift 20:27 Pivoting to Success with Drift 21:41 Drift's Chatbot Innovation 22:09 Challenges and Limitations of Drift 22:37 The Struggle with Customer Knowledge 23:09 Scaling Challenges and Lessons Learned 25:58 Rediscovering Purpose Post-Drift 28:55 The Birth of Agency 29:42 AI's Role in Customer Experience 35:13 Building a Sustainable Business Model 37:06 The Vision for Agency 38:22 Challenges and Opportunities with AI 41:22 Deprogramming and Embracing Change 43:23 Optimism for the AI Future 44:15 Closing Thoughts