Clay’s Kareem Amin On Building The Sales ‘System Of Action’ With AI Training Data podcast

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Amjad Masad set out more than a decade ago to pursue the dream of unleashing 1B software creators around the world. With millions of Replit users pre-ChatGPT, that vision was already becoming a reality. Turbocharged by LLMs, the vision of enabling anyone to code—from 12-year-olds in India to knowledge workers in the U.S.—seems less and less radical. In this episode, Amjad explains how an explosion in the developer population could change the economy, society and more. He also discusses his early days programming in Jordan, his unique management approach and what AI will mean for the global economy. Hosted by David Cahn and Sonya Huang, Sequoia Capital Mentioned in this episode: On the Naturalness of Software : 2012 paper on applying NLP to code Attention Is All You Need : Seminal 2017 paper on transformers I Am a Strange Loop : 2007 follow up to Douglas Hofstadter’s 1979 classic Gödel, Escher, Bach that explores how self-referential systems can describe minds On Lisp : Paul Graham’s 1993 book on the original programming language of AI…

Training Data

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Why CRM Needs an AI Revolution, with Day.ai Founder Christopher O’Donnell 1:11:05

hace 11 días1:11:05

1:11:05

Christopher O’Donnell believes the fundamental problems with CRM—incomplete data, complex workflows, siloed work products and the fear of leads falling through the cracks—can finally be solved through AI. Founder of Day.ai and former Chief Product Officer of HubSpot, Christopher explains how his team is building a system that automatically captures the full context of customer relationships while giving users transparency and control. He shares lessons from building HubSpot’s CRM and why he’s taking a deliberate approach to product development despite the pressure to scale quickly in the AI era. Hosted by Pat Grady, Sequoia Capital Mentioned in this episode: The Innovator's Dilemma : Classic book by Clay Christensen (referenced regarding HubSpot's second S-curve strategy) Hubspot CRM : The only product to successfully challenge Salesforce’s dominance in the CRM category From Super Mario Brothers to Elden Ring : Analogy to what an AI-powered CRM experience can be through comparison of video games launched in 1985 vs 2022 Punk’d : Hidden camera–practical joke reality television series that premiered on MTV in 2003, created by Ashton Kutcher and Jason Goldberg Slow is smooth and smooth is fast : SEALs-derived concept mentioned regarding product development) Aga stove (highlighted as extraordinary product design example)…

Training Data

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From Software Engineers to AI Word Artisans: Filip Kozera of Wordware 43:04

hace 18 días43:04

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Filip Kozera sees parallels between Excel’s democratization of data analytics and Wordware’s mission to put AI development in the hands of knowledge workers. Drawing inspiration from Excel’s 750 million users (compared to 30 million software developers), Wordware is creating tools that balance the rigid structure of programming with the fuzziness of natural language. Filip explains why effective AI development requires working across multiple abstraction layers—from high-level concepts to detailed implementation—while preserving human creative control. He shares his vision for “word artisans” who will use AI to amplify their creative impact. Hosted by Sonya Huang, Sequoia Capital Mentioned in this episode: Lovable : Generative AI app that builds UIs and web apps Her : 2013 Spike Jonze film that Filip uses as an example of how voice will not be the best modality to express knowledge work. Descript : AI video editing app that Filip uses a lot. Granola : AI notetaking app Filip uses every day.. Gemini 2.0 Pro : Google’s newest long context model that can handle 6000 page pdfs. Limitless pendant : Wearable device for collecting personal conversational context to drive AI experiences that Filip can’t wait for to ship. DeepLearning.AI : Andrew Ng’s amazing resource for learning about AI 3Blue1Brown : Grant Sanderson’s incredible channel on YouTube that explains math and AI visually.…

Training Data

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Josh Woodward: Google Labs is Rapidly Building AI Products from 0-to-1 51:16

hace 25 días51:16

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As VP of Google Labs, Josh Woodward leads teams exploring the frontiers of AI applications. He shares insights on their rapid development process, why today’s written prompts will become outdated and how AI is transforming everything from video generation to computer control. He reveals that 25% of Google’s code is now written by AI and explains why coding could see major leaps forward this year. He emphasizes the importance of taste, design and human values in building AI tools that will shape how future generations work and create. Mentioned in this episode: Notebook LM : Personal research product based on Gemini 2 (previously discussed on Training Data .) Veo 2 : Google DeepMind’s new video generation model. Paul Graham on X replying to Aaron Levie’s post that “One approach to take in building in AI is to do something that's too expensive to be reasonably practical right now, and just bet that the costs will drop by 10X or 100X over time. The cost curve is on your side.” Where Good Ideas Come From : Book on the history of innovation by Steven Johnson. Project Mariner : Google DeepMind’s research prototype exploring human-agent interaction starting with browser use. Replit Agent : Josh’s favorite new AI app The Lego Story : Book on the history of Lego. Hosted by: Ravi Gupta and Sonya Huang, Sequoia Capital…

Training Data

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How AI Breakout Harvey is Transforming Legal Services, with CEO Winston Weinberg 54:09

hace 4 weeks54:09

54:09

Harvey CEO Winston Weinberg explains why success in legal AI requires more than just model capabilities—it demands deep process expertise that doesn’t exist online. He shares how Harvey balances rapid product development with earning trust from law firms through hyper-personalized demos and deep industry expertise. The discussion covers Harvey’s approach to product development—expanding specialized capabilities then collapsing them into unified workflows—and why focusing on complex work like international mergers creates the most defensible position in legal AI. Hosted by: Sonya Huang and Pat Grady, Sequoia Capital…

Training Data

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The AI Product Going Viral With Doctors: OpenEvidence, with CEO Daniel Nadler 1:04:52

hace 6 weeks1:04:52

1:04:52

OpenEvidence is transforming how doctors access medical knowledge at the point of care, from the biggest medical establishments to small practices serving rural communities. Founder Daniel Nadler explains his team’s insight that training smaller, specialized AI models on peer-reviewed literature outperforms large general models for medical applications. He discusses how making the platform freely available to all physicians led to widespread organic adoption and strategic partnerships with publishers like the New England Journal of Medicine. In an industry where organizations move glacially, 10-20% of all U.S. doctors began using OpenEvidence overnight to find information buried deep in the long tail of new medical studies, to validate edge cases and improve diagnoses. Nadler emphasizes the importance of accuracy and transparency in AI healthcare applications. Hosted by: Pat Grady, Sequoia Capital Mentioned in this episode: Do We Still Need Clinical Language Models? : Paper from OpenEvidence founders showing that small, specialized models outperformed large models for healthcare diagnostics Chinchilla paper : Seminal 2022 paper about scaling laws in large language models Understand : Ted Chiang sci-fi novella published in 1991…

Training Data

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OpenAI’s Deep Research Team on Why Reinforcement Learning is the Future for AI Agents 32:45

hace 7 weeks32:45

32:45

OpenAI’s Isa Fulford and Josh Tobin discuss how the company’s newest agent, Deep Research, represents a breakthrough in AI research capabilities by training models end-to-end rather than using hand-coded operational graphs. The product leads explain how high-quality training data and the o3 model’s reasoning abilities enable adaptable research strategies, and why OpenAI thinks Deep Research will capture a meaningful percentage of knowledge work. Key product decisions that build transparency and trust include citations and clarification flows. By compressing hours of work into minutes, Deep Research transforms what’s possible for many business and consumer use cases. Hosted by: Sonya Huang and Lauren Reeder, Sequoia Capital Mentioned in this episode: Yann Lecun’s Cake : An analogy Meta AI’s leader shared in his 2016 NIPS keynote…

Training Data

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Palo Alto Networks’ Nikesh Arora: AI, Security and the New World Order 1:00:08

hace 8 weeks1:00:08

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Palo Alto Networks’s CEO Nikesh Arora dispels DeepSeek hype by detailing all of the guardrails enterprises need to have in place to give AI agents “arms and legs.” No matter the model, deploying applications for precision-use cases means superimposing better controls. Arora emphasizes that the real challenge isn’t just blocking threats but matching the accelerated pace of AI-powered attacks, requiring a fundamental shift from prevention-focused to real-time detection and response systems. CISOs are risk managers, but legacy companies competing with more risk-tolerant startups need to move quickly and embrace change. Hosted by: Sonya Huang and Pat Grady, Sequoia Capital Mentioned in this episode: Cortex XSIAM : Security operations and incident remediation platform from Palo Alto Networks…

Training Data

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MongoDB’s Sahir Azam: Vector Databases and the Data Structure of AI 44:26

hace 8 weeks44:26

44:26

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…

Training Data

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Roblox Studio Head Stef Corazza: Using AI to Empower Creators 54:46

hace 10 weeks54:46

54:46

Stef Corazza leads generative AI development at Roblox after previously building Adobe’s 3D and AR platforms. His technical expertise, combined with Roblox’s unique relationship with its users, has led to the infusion of AI into its creation tools. Roblox has assembled the world’s largest multimodal dataset. Stef previews the Roblox Assistant and the company’s new 3D foundation model, while emphasizing the importance of maintaining positive experiences and civility on the platform. Mentioned in this episode: Driving Empire : A Roblox car racing game Stef particularly enjoys RDC : Roblox Developer Conference Ego.live : Roblox app to create and share synthetic worlds populated with human-like generative agents and simulated communities| PINNs : Physics Informed Neural Networks ControlNet : A model for controlling image diffusion by conditioning on an additional input image that Stef says can be used as a 2.5D approach to 3D generation. Neural rendering : A combination of deep learning with computer graphics principles developed by Nvidia in its RTX platform Hosted by: Konstantine Buhler and Sonya Huang, Sequoia Capital…

Training Data

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ReflectionAI Founder Ioannis Antonoglou: From AlphaGo to AGI 52:29

hace 11 weeks52:29

52:29

Ioannis Antonoglou, founding engineer at DeepMind and co-founder of ReflectionAI, has seen the triumphs of reinforcement learning firsthand. From AlphaGo to AlphaZero and MuZero, Ioannis has built the most powerful agents in the world. Ioannis breaks down key moments in AlphaGo's game against Lee Sodol (Moves 37 and 78), the importance of self-play and the impact of scale, reliability, planning and in-context learning as core factors that will unlock the next level of progress in AI. Hosted by: Stephanie Zhan and Sonya Huang, Sequoia Capital Mentioned in this episode: PPO : Proximal Policy Optimization algorithm developed by DeepMind in game environments. Also used by OpenAI for RLHF in ChatGPT. MuJoCo : Open source physics engine used to develop PPO Monte Carlo Tree Search : Heuristic search algorithm used in AlphaGo as well as video compression for YouTube and the self-driving system at Tesla AlphaZero : The DeepMind model that taught itself from scratch how to master the games of chess, shogi and Go MuZero : The DeepMind follow up to AlphaZero that mastered games without knowing the rules and able to plan winning strategies in unknown environments AlphaChem : Chemical Synthesis Planning with Tree Search and Deep Neural Network Policies DQN : Deep Q-Network, Introduced in 2013 paper, Playing Atari with Deep Reinforcement Learning AlphaFold : DeepMind model for predicting protein structures for which Demis Hassabis, John Jumper and David Baker won the 2024 Nobel Prize in Chemistry…

Training Data

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Kumo’s Hema Raghavan: Turning Graph AI into ROI 52:06

hace 12 weeks52:06

52:06

Hema Raghavan is co-founder of Kumo, a company that makes graph neural networks accessible to enterprises by connecting to their relational data stored in Snowflake and Databricks. Hema talks about how running GNNs on GPUs has led to breakthroughs in performance as well as the query language Kumo developed to help companies predict future data points. Although approachable for non-technical users, the product provides full control for data scientists who use Kumo to automate time-consuming feature engineering pipelines. Mentioned in this episode: Graph Neural Networks : Learning mechanism for data in graph format, the basis of the Kumo product Graph RAG : Popular extension of retrieval-augmented generation using GNNs LiGNN : Graph Neural Networks at LinkedIn paper KDD : Knowledge Discovery and Data Mining Conference Hosted by: Konstantine Buhler and Sonya Huang, Sequoia Capital…

Training Data

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Databricks Founder Ion Stoica: Turning Academic Open Source into Startup Success 1:00:05

hace 13 weeks1:00:05

1:00:05

Berkeley professor Ion Stoica, co-founder of Databricks and Anyscale, transformed the open source projects Spark and Ray into successful AI infrastructure companies. He talks about what mattered most for Databricks' success -- the focus on making Spark win and making Databricks the best place to run Spark. He highlights the importance of striking key partnerships -- the Microsoft partnership in particular that accelerated Databricks' growth and contributed to Spark's dominance among data scientists and AI engineers. He also shares his perspective on finding new problems to work on, which holds lessons for aspiring founders and builders: 1) building systems in new areas that, if widely adopted, put you in the best position to understand the new problem space, and 2) focusing on a problem that is more important tomorrow than today. Hosted by: Stephanie Zhan and Sonya Huang, Sequoia Capital Mentioned in this episode: Spark : The open source platform for data engineering that Databricks was originally based on. Ray : Open source framework to manage, executes and optimizes compute needs across AI workloads, now productized through Anyscale MosaicML : Generative AI startups founded by Naveen Rao that Databricks acquired in 2023. Unity Catalog : Data and AI governance solution from Databricks. CIB Berkeley : Multi-strategy hedge fund at UC Berkeley that commercializes research in the UC system. Hadoop : A long-time leading platform for large scale distributed computing. VLLM and Chatbot Arena : Two of Ion’s students’ projects that he wanted to highlight.…

Training Data

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XBOW CEO and GitHub Copilot Creator Oege de Moor: Cracking the Code on Offensive Security With AI 51:37

hace 18 weeks51:37

51:37

Oege de Moor, the creator of GitHub Copilot, discusses how XBOW’s AI offensive security system matches and even outperforms top human penetration testers, completing security assessments in minutes instead of days. The team’s speed and focus is transforming the niche market of pen testing with an always-on service-as-a-software platform. Oege describes how he is building a large and sustainable business while also creating a product that will “protect all the software in the free world.” XBOW shows how AI is essential for protecting software systems as the amount of AI-generated code increases along with the scale and sophistication of cyber threats. Hosted by: Konstantine Buhler and Sonya Huang, Sequoia Capital Mentioned in this episode: Semmle : Oege’s previous startup, a code analysis tool to secure software, acquired in 2019 by GitHub Nico Waisman : Head of security at XBOW, previously a researcher at Semmle The Bitter Lesson : Highly influential post by Richard Sutton HackerOne : Cybersecurity company that runs one of the largest bug bounty programs Suno : AI songwriting app that Oege loves Machines of Loving Grace : Essay by Anthropic founder, Dario Amodei…

Training Data

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Ramp CEO Eric Glyman: Using AI to Build “Self-Driving Money” 38:48

hace 19 weeks38:48