Sequoia Capital

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Channel • 2 Shows

Technology

Technology

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Entrepreneurship

Entrepreneurship

Updated Biweekly

2D AGO

Why AI Will Transform Customer Experience: Cresta CEO Ping Wu and Sequoia’s Doug Leone

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

2d ago

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45 min
SEP 30

Block CTO Dhanji Prasanna: Building the AI-First Enterprise with Goose, their Open Source Agent

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

Sep 30

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1 hr
JUL 22

OpenAI Just Released ChatGPT Agent, Its Most Powerful Agent Yet

Isa Fulford, Casey Chu, and Edward Sun from OpenAI's ChatGPT agent team reveal how they combined Deep Research and Operator into a single, powerful AI agent that can perform complex, multi-step tasks lasting up to an hour. By giving the model access to a virtual computer with text browsing, visual browsing, terminal access, and API integrations—all with shared state—they've created what may be the first truly embodied AI assistant. The team discusses their reinforcement learning approach, safety mitigations for real-world actions, and how small teams can build transformative AI products through close research-applied collaboration. Hosted by Sonya Huang and Lauren Reeder, Sequoia Capital

Jul 22

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38 min
FEB 13

MongoDB’s Sahir Azam: Vector Databases and the Data Structure of AI

MongoDB product leader Sahir Azam explains how vector databases have evolved from semantic search to become the essential memory and state layer for AI applications. He describes his view of how AI is transforming software development generally, and how combining vectors, graphs and traditional data structures enables high-quality retrieval needed for mission-critical enterprise AI use cases. Drawing from MongoDB's successful cloud transformation, Azam shares his vision for democratizing AI development by making sophisticated capabilities accessible to mainstream developers through integrated tools and abstractions. Hosted by: Sonya Huang and Pat Grady, Sequoia Capital Mentioned in this episode: Introducing ambient agents: Blog post by Langchain on a new UX pattern where AI agents can listen to an event stream and act on it Google Gemini Deep Research: Sahir enjoys its amazing product experience Perplexity: AI search app that Sahir admires for its product craft Snipd: AI powered podcast app Sahir likes

Feb 13

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44 min
SEP 9

Building the "App Store" for Robots: Hugging Face's Thomas Wolf on Physical AI

Thomas Wolf, co-founder and Chief Science Officer of Hugging Face, explains how his company is applying the same community-driven approach that made transformers accessible to everyone to the emerging field of robotics. Thomas discusses LeRobot, Hugging Face's ambitious project to democratize robotics through open-source tools, datasets, and affordable hardware. He shares his vision for turning millions of software developers into roboticists, the challenges of data scarcity in robotics versus language models, and why he believes we're at the same inflection point for physical AI that we were for LLMs just a few years ago. Hosted by: Sonya Huang and Pat Grady, Sequoia Capital

Sep 9

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43 min
TRAILER

Crucible Moments Season 3: Coming October 23

Previously on Crucible Moments, we explored the inflection points that shaped some of the most significant names in technology. Now, we're returning for a brand new season. Join us as leaders from Stripe, Zipline, Palo Alto Networks, Klarna, Supercell and more share what it's actually like to navigate the make-or-break decisions, early stumbles and leaps that turn scrappy startups into market defining forces. Hosted by: Roelof Botha, Sequoia Capital

Trailer

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3 min
SEP 23

Why Businesses Are Rejecting the AI They’ve Asked For: Agency CEO Elias Torres

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

Sep 23

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45 min
AUG 26

n8n CEO Jan Oberhauser on Building the Universal AI Automation Layer

When the AI wave hit, n8n founder Jan Oberhauser faced a critical choice: become irrelevant or become indispensable. He chose the latter, transforming n8n from a simple workflow tool into a comprehensive AI automation platform that lets users connect any LLM to any application. The result? Four times the revenue growth in eight months compared to the previous six years. Jan explains how n8n’s “connect everything to anything” philosophy, combined with a thriving open source community, positioned the company to ride the AI automation wave while avoiding vendor lock-in that plagues enterprise software. Hosted by George Robson and Pat Grady, Sequoia Capital Mentioned in this episode: Model Context Protocol (MCP): Open protocol that lets AI models safely use external tools and data that is used extensively by n8n for orchestration. Vector database: A database optimized for storing and searching embeddings. These “vector stores” can pair with LLMs for retrieval-augmented workflows. Granola: AI productivity tool mentioned by Jan as a recent favorite. Her: A film that Jan says, “a few years ago, it was sci fi, and it’s now suddenly this thing that is just around the corner.”

Aug 26

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36 min
JUL 30

OpenAI’s IMO Team on Why Models Are Finally Solving Elite-Level Math

In just two months, a scrappy three-person team at OpenAI sprinted to fulfill what the entire AI field has been chasing for years—gold-level performance on the International Mathematical Olympiad problems. Alex Wei, Sheryl Hsu and Noam Brown discuss their unique approach using general-purpose reinforcement learning techniques on hard-to-verify tasks rather than formal verification tools. The model showed surprising self-awareness by admitting it couldn’t solve problem six, and revealed the humbling gap between solving competition problems and genuine mathematical research breakthroughs. Hosted by Sonya Huang, Sequoia Capital

Jul 30

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30 min
AUG 12

Delphi’s Dara Ladjevardian: How AI Digital Minds Can Scale Human Connection

Dara Ladjevardian, founder and CEO of Delphi, is creating digital minds that allow people to scale their thoughts and availability without replacing human connection. Inspired by Ray Kurzweil’s theory of mind as a hierarchy of pattern recognizers, Dara built an adaptive temporal knowledge graph that captures how people think and reason. From helping CEOs train new hires to enabling coaches to monetize their expertise 24/7, Delphi represents a new form of conversational media. Dara explains why authentic human representation matters, how digital minds actually increase desire for real human connection, and why he believes 2026 will be the tipping point for adoption for digital minds. Hosted by Sonya Huang and Jess Lee, Sequoia Capital Mentioned in this episode: How to Create a Mind: 2012 book by Ray Kurzweil that inspired Dara The Memoirs of Akbar Ladjevardian: 2008 book about Dara’s grandfather, an Iranian industrialist, that led him to create his first “digital mind” Build: 2022 book by Tony Fadell that refers to itself as “a mentor in a box”; another inspiration for Dara The 2 Sigma Problem: 1984 paper by Benjamin Bloom about how students that receive one-on-one tutoring perform two standard deviations better than students educated in a classroom environment

Aug 12

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39 min

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