Latest Interviews
Showing 16–30 of 38 interview transcripts.
Clear all filters- Sequoia Capital58 min
Arc Institute's Patrick Hsu on Building an App Store for Biology with AI
Patrick Hsu, Josephine Chen, Pat Grady
The ARC Institute, led by Patrick Hsu, has launched EVO2, a generative foundation model trained on genomic sequences across all domains of life to predict the functional consequences of genetic variants with state-of-the-art accuracy. By reclassifying Variants of Unknown Significance, this open-source tool aims to transform genetic testing outcomes and prevent unnecessary medical interventions while establishing a roadmap toward simulating virtual cells by 2030. This initiative reflects a strategic shift within ARC to merge academic rigor with industrial application, utilizing evolutionary data to build a unifying theory of biology rather than focusing solely on traditional drug design.
- Sequoia Capital1h 11m
Why CRM Needs an AI Revolution, with Day.ai Founder Christopher O’Donnell
Christopher O'Donnell, Pat Grady
Christopher O'Donnell, the former architect behind HubSpot's billion-dollar CRM growth, is launching Day.ai to replace manual data entry with an AI-native system that decompresses customer interactions into high-fidelity natural language records. By balancing autonomous automation with user oversight, the company targets the enterprise CRM market's $10 billion ARR potential while avoiding the risks of fully self-driving data models. The product's development strategy relies on direct customer engagement and a "slow is smooth" philosophy to ensure the system of record remains robust before scaling.
- Sequoia Capital54 min
How AI Breakout Harvey is Transforming Legal Services, with CEO Winston Weinberg
Winston Weinberg, Sonya Huang, Pat Grady
Founded in July 2022 by Winston Weinberg and Gabe, Harvey targets the $400 billion U.S. legal market by deploying specialized agentic workflows that prioritize citation accuracy over generic chat interfaces. The company differentiates itself through a hybrid revenue-share model and a rigorous technical architecture utilizing OpenAI's O-series models alongside proprietary process data to eliminate hallucinations in high-stakes legal tasks. By collaborating with top-tier law firms as design partners and transitioning toward automating commoditized work, Harvey aims to fundamentally shift industry economics from billable hours to fixed fees while expanding access to justice.
- Sequoia Capital1h 5m
The AI Product Going Viral With Doctors: OpenEvidence, with CEO Daniel Nadler
Open Evidence currently scales to over 400,000 global monthly active physicians through a direct-to-pro model that bypasses traditional enterprise sales by relying on word-of-mouth adoption. The platform distinguishes itself by training exclusively on peer-reviewed literature, including a strategic partnership with the New England Journal of Medicine, to prevent hallucinations while enabling doctors to resolve complex comorbidities that standard search engines cannot address. Co-founder Daniel Nadler projects this technology could prevent 300,000 to 800,000 deaths annually within five years, with a long-term vision of achieving hyper-personalized medicine to extend human life expectancy toward 120 to 130 years.
- Sequoia Capital1h 0m
AI, Security and the New World Order ft. Palo Alto Networks’s Nikesh Arora
Nikesh Arora, Sonya Huang, Pat Grady, Jim Goetz
Nikesh Arora outlines a shifting AI landscape where falling development costs enable specialized models while warning that premature agency requires rigorous "AI firewalls" to mitigate real-time cyber threats and hallucinations. He details Palo Alto Networks' strategy of acquiring only category leaders under strict co-authorship agreements, a tactic designed to preserve agility amidst a predicted five-year battle between autonomous agents. Additionally, Arora forecasts a regulatory bifurcation for critical infrastructure alongside a market split between enterprise-grade specialized systems and consumer-focused general-purpose AI.
- Sequoia Capital44 min
Vector Databases and the Data Structure of AI ft. MongoDB’s Sahir Azam
Sahir Azam, Sonya Huang, Pat Grady, Amy Quinton
This session explores the evolution of quality engineering for probabilistic software, highlighting how traditional deterministic models are being replaced by RAG architectures and vector databases to achieve 99.99% reliability in enterprise environments. It details concrete ROI from the automotive and pharmaceutical sectors, where embedding models and large language models have drastically reduced diagnosis times and automated complex clinical reporting while preserving data sovereignty. The discussion concludes by framing databases as the essential memory layer for AI agents, emphasizing MongoDB's strategy to unify structured, unstructured, and vector data into a single system that supports the next generation of agent-driven workflows.
- Sequoia Capital1h 3m
Getting the Most From AI With Multiple Custom Agents ft Dust’s Gabriel Hubert and Stanislas Polu
Gabriel Hubert, Stanislas Polu, Konstantine Buhler, Pat Grady
Dust positions itself as a horizontal platform for AI adoption, predicting a bimodal future where enterprise users seamlessly switch between frontier APIs and local models to navigate varying technological plateaus. By prioritizing product-market fit over proprietary model training and leveraging Retrieval-Augmented Generation to unlock data silos, the company enables diverse teams to build specialized agents that augment human work rather than replace it. This strategy targets a demographic of young power users and aims to scale from isolated pilots to organization-wide adoption, facilitating everything from cross-functional translation to global expansion despite current limitations in reasoning breakthroughs.
- Sequoia Capital45 min
How Glean CEO Arvind Jain Solved the Enterprise Search Problem – and What It Means for AI at Work
Arvind Jain, Sonya Huang, Pat Grady
Glean CEO Arvind Jain's company has evolved from an enterprise search provider into an AI application platform, leveraging a five-year vision to automate 80% of knowledge worker tasks through a unique RAG architecture that grounds responses in private data. The platform differentiates itself by prioritizing data governance, semantic knowledge graphs, and fine-grained access controls before layering on Large Language Models, which has enabled year-over-year revenue quadrupling. By abstracting complex infrastructure for developers and focusing on agentic workflows, Glean aims to shift the market from reactive querying to proactive, autonomous assistance that doubles productivity for engineering, sales, and support teams.
- Sequoia Capital42 min
OpenAI Researcher Dan Roberts on What Physics Can Teach Us About AI
Dan Roberts, Sonya Huang, Pat Grady
Former Sequoia AI Fellow and MIT PhD Dan Roberts discusses his transition to OpenAI to contribute to the o1 model, framing the current AI landscape as a modern Manhattan Project that requires a physics-inspired approach to understanding complex systems. Roberts argues that economic constraints on scaling will soon necessitate a shift from brute-force compute to architectural innovation, predicting that significant capability gains will depend on whether the next five months of model development can overcome these bottlenecks. He further details his optimistic outlook for AI's impact on mathematics and his advocacy for informal scientific communication to accelerate the adoption of new ideas in the field.
- Sequoia Capital32 min
Google NotebookLM’s Raiza Martin and Jason Spielman on the Potential for Source-Grounded AI
Raiza Martin, Jason Spielman, Sonya Huang, Pat Grady
Google's Notebook LM, developed by a lean team within Google Labs, is an AI-powered research tool that utilizes the Gemini 1.5 Pro model to generate realistic, two-host podcast-style audio summaries grounded strictly in user-uploaded documents. This source-grounded approach has driven viral adoption across educational and corporate sectors, with early users reporting up to a tenfold increase in efficiency when digesting complex materials like investment memorandums or training manuals. Currently in an experimental preview phase, the product aims to evolve from familiar audio formats into broader writing and code generation capabilities while addressing gaps in native collaboration features.
- Sequoia Capital1h 0m
Snowflake CEO Sridhar Ramaswamy on Using Data to Create Simple, Reliable AI for Businesses
Sridhar Ramaswamy, Sonya Huang, Pat Grady, Sonia
Snowflake CEO Sridhar Ramaswamy is driving the company's transformation into an "AI data cloud" that integrates acquired search technology from Neva to serve over 10,000 enterprise customers. The organization addresses reliability concerns in generative AI by prioritizing context engineering and managed governance, enabling business users to access data through grounded chatbots without extensive custom software development. This strategic pivot aims to democratize software creation by embedding AI directly into data workflows, positioning Snowflake to capitalize on the shift toward interoperable cloud storage and controlled mobile ecosystems.
- Sequoia Capital45 min
OpenAI's Noam Brown, Ilge Akkaya and Hunter Lightman on o1 and Teaching LLMs to Reason Better
Noam Brown, Ilge Akkaya, Hunter Lightman, Sonya Huang, Pat Grady
OpenAI's O1 model, internally codenamed Project Strawberry, introduces a paradigm shift by employing "inference time compute" to enable systems to engage in extended, self-correcting reasoning processes akin to human System 2 thinking. This architecture has delivered unprecedented capabilities in STEM domains, allowing the AI to solve complex Olympiad-level programming problems, pass research engineer interviews, and assist in scientific discovery by bridging the gap between difficulty in generation versus verification. While the project faces limitations in speed and creative tasks compared to predecessors like GPT-4, its demonstrated ability to scale performance through increased thinking time marks a significant advancement toward the operational goal of Artificial General Intelligence.
- Sequoia Capital40 min
Why Vlad Tenev and Tudor Achim of Harmonic Think AI Is About to Change Math—and Why It Matters
Vlad Tenev, Tudor Achim, Sonya Huang, Pat Grady
Harmonic, led by Robinhood CEO Vlad Todorovic and co-founder Tudor, is developing math-specialized superintelligence by utilizing the Lean formal verification language to generate synthetic training data and enable objective, self-correcting reinforcement learning. This approach targets the exhaustion of static internet data by creating an unbounded progression of rigorous mathematical proofs, with projected milestones including winning the International Mathematical Olympiad by 2025 and solving Millennium Prize problems by 2029. By shifting human mathematicians toward strategic problem selection and applying this reasoning framework to software verification and theoretical physics, the company aims to achieve superhuman deductive capabilities that transcend the limitations of current large language models.
- Sequoia Capital42 min
ServiceNow ft. Frank Slootman and Fred Luddy - From Starting Over at 50 to Dodging a $150B Mistake
Frank Slootman, Fred Luddy, Roelof Botha, Doug Leone, Pat Grady, Carl Eschenbach, Rolof Huerta
Founded by Fred Luddy in 2004 after a previous bankruptcy, ServiceNow evolved from a free IT help desk tool into a $150 billion enterprise platform through a strategic pivot to broad, seat-based licensing and a complete cloud infrastructure overhaul. In 2011, Luddy ceded the CEO role to Frank Slootman to enforce operational discipline, while investors from Sequoia Capital blocked a $2.5 billion acquisition offer from VMware to force a path toward an IPO. This decision proved prescient as the company's market value surged to $10 billion within two years of going public in 2012, validating the strategy to prioritize long-term disruption over immediate financial stability.
- Sequoia Capital1h 13m
Sierra co-founder Clay Bavor on Making Customer-Facing AI Agents Delightful
Clay Bavor, Ravi Gupta, Pat Grady, Brett Taylor, Karthik Narasimhan, Robbie
Former Google leader Clay Bavore and Brett Taylor founded Sierra in late 2022 to deploy proprietary AgentOS-branded AI agents that replace traditional navigation with natural language interactions for major brands like Weight Watchers and Sonos. The company addresses specific large language model limitations, such as hallucinations and data silos, by utilizing supervisor agents and a declarative SDK to achieve over 70% autonomous resolution rates for complex customer tasks. Sierra's unique resolution-based pricing model and proprietary TAU Bench benchmark underscore a strategic shift toward industrial-grade AI that prioritizes factual accuracy and task reliability over raw model size.