Latest Interviews
Showing 31–45 of 1,628 interview transcripts.
Clear all filtersHow LPs Allocate to Venture in 2026: What They Want, What They Don’t | Baylor University CIO
David Morehead, Harry Stebbings
Baylor University's $2.6 billion endowment office, led by Moorhead, is restructuring its 55% private and 45% public portfolio to prioritize capital velocity and upside capture amidst declining enrollment and rising tuition pressures. The team distinguishes itself through a mechanistic deployment strategy, conservative valuation discipline, and direct GP negotiations that favor annualized growth equity returns of 30% over traditional fund duration models. While maintaining a neutral stance on private credit, the fund actively bets on the resilience of legacy SaaS, permitted data center infrastructure, and biotech, aiming to navigate its expansion into the single-digit billion scale by maximizing the absolute dollar impact of its $2.5 million core positions.
Bending Spoons Founders on Buying Airtable, AOL, Vimeo & Miro
Luca Ferrari, Francesco Patarnello, Matteo Danieli, Valentina Jerusalmi, Molly O'Shea
Bending Spoons executes a high-volume acquisition strategy centered on buying small, high-caliber teams for near-total autonomy, evidenced by recent multi-billion dollar deals such as AOL and Airtable. The company differentiates its approach through a "forever ownership" model that avoids private equity exit timelines, supported by decentralized operations in Milan and an internal culture prioritizing rapid learning, extreme ownership, and aggressive meritocracy where leadership roles are periodically contested. This operational philosophy, combined with unconventional financing and an open-desk work structure, has enabled the firm to maintain under 1% employee churn while targeting five to ten strategic acquisitions annually to maximize platform synergies.
Labour, Engineering, Social Media, GrokBots, Cybercabs: 7 Predictions for How AI Changes the World
Matteo Franceschetti, Harry Stebbings
Eight Sleep Co-founder Matteo Franceschetti details how the company replaces traditional engineering and marketing teams with AI agents to operate as a 160-person entity generating revenue per employee exceeding Apple's. The presentation outlines the firm's aggressive global expansion into markets like China via super-apps and its strategic pivot from a hardware manufacturer to a medical platform while navigating intense talent retention wars and rising AI infrastructure costs. Franceschetti concludes with predictions on the future of work, suggesting that Universal Basic Income will eventually become necessary as AI-driven efficiency drastically reduces the demand for human labor.
- a16z48 min
How AI Is Rewriting the Power Law of Venture Capital
Jen Kha, David George, Aram Verdiyan
The summary details how an extreme power law in venture capital now demands that top-tier funds secure category-defining assets like SpaceX or OpenAI to generate returns, as traditional mid-stage investing has collapsed and late-stage exits increasingly favor early-stage franchise holders. Despite valuation distortions and structural misalignments between general partners and limited partners, capital is shifting aggressively toward AI-native growth and infrastructure bottlenecks like energy and data centers, which are viewed as the primary constraints on a projected $10 trillion market opportunity. This reallocation favors long-horizon investors who can tolerate early-stage loss rates up to 60% in exchange for the liquidity potential of future trillion-dollar companies emerging from robotics, autonomy, and deep healthcare innovation.
Saronic's 4 Co-Founders on Building a $9.25B Shipbuilder | Part III
Dino Mavrookas, Rob Lehman, Doug Lambert, Vibhav Altekar, Molly O'Shea
Ceronic, a hard tech manufacturer valued at $9.25 billion with $2.6 billion in funding, is addressing the critical U.S. naval shipbuilding deficit by developing autonomous surface vessels capable of surviving extreme accelerations exceeding 20 Gs. Partnering with Palantir and Path Robotics to secure aluminum supplies and master aluminum welding, the company is transitioning from low-volume prototyping to mass production models that utilize hardware-software co-design to reduce costs and eliminate personnel from harm's way. This industrial strategy aims to expand the U.S. fleet from 290 to 381 ships over three decades while creating a scalable, cost-effective platform for both defense operations and emerging commercial ocean markets.
Jensen Huang Declares AGI Has Arrived | Tesla Launches Cybercabs | Index Pulls Out of Town
Jensen Huang, Jason Lemkin, Rory O'Driscoll, Harry Stebbings
Jensen Huang, Jason Calacanis, and other industry leaders debated the arrival of AGI and the economic potential of AI in coding versus law while discussing critical safety breaches that bypassed current guardrails. The conversation also covered market dynamics where aggressive startups like Instinct challenge regulations, alongside autonomous vehicle unveilings by Elon Musk and a wave of record-breaking valuations and M&A activity. Ultimately, the panel warned of an impending "Neolab" bubble correction, emphasizing that only companies capable of rapid evolution or those with massive corporate backing will survive the current capital crunch.
- a16z1h 5m
Inside OpenAI’s Breakthroughs in Mathematical Reasoning
Lisha Li, Mehtaab Sawhney, Mark Sellke
The AI model Astra has achieved significant breakthroughs in pure mathematics by resolving open problems in sphere packing, spherical codes, and the existence of non-sofic groups through emergent reasoning capabilities like backtracking and parallel processing. These results demonstrate that large language models can synthesize complex algebraic structures and high-dimensional analysis without explicit programming, effectively closing long-standing gaps in asymptotic bounds and group theory. Consequently, the mathematical community is shifting its focus from theorem proving to the curation of problems and the interpretation of AI-generated insights, signaling a new era where human intuition complements machine persistence.
Town vs Instinct vs GrokBot | Why the AI Assistant Market Is Not a Bubble
Jean-Denis "JD" Grèze, Harry Stebbings
Town, led by founder Jean-Denis, has pivoted from a failed tax prep venture to a mainstream email and calendar AI assistant targeting a $100 billion valuation through a network effect at the agent level. With conversion rates exceeding 15% and a multi-model routing strategy to optimize costs, the company navigates competitive pressure from tech giants like Google and Apple by prioritizing enterprise workflow integration over consumer subsidies. JD anticipates that future market leaders will be defined by their ability to build emotional defensibility through autonomous agents while maintaining strict token economics to ensure sustainable revenue growth.
How to Build Your Own Data Center & Why Every Startup Should Do It
Cliff Weitzman, Harry Stebbings
Speechify founder Cliff Weitzman openly acknowledged a strategic error in initially avoiding the B2B API market, prompting the company to launch competitive products against rivals like 11 Labs while leveraging a proprietary hardware strategy to secure cost-efficient access to next-generation NVIDIA GPUs. By owning assets to lower training costs and prioritizing a specialized "Simba 3.2" model, Speechify aims to dominate the B2C voice space and compete directly with industry giants through a hybrid compute approach that decouples legacy inference hardware from high-performance training clusters. This infrastructure investment supports the company's pivot toward generalist AI agents and synthetic data generation, positioning Speechify to capitalize on a predicted shift from screen-based to voice-first human-computer interfaces over the next five years.
- Y Combinator57 min
Open Models Are Collapsing The Cost Of AI
Driven by cost efficiency and customization needs, enterprises are increasingly adopting open AI models, with major corporations like AT&T shifting significant token consumption away from proprietary systems toward flexible, locally deployable solutions. Ollama has emerged as a critical orchestration layer for this ecosystem, supporting 85% of Fortune 500 companies and facilitating a hybrid deployment strategy that balances local hardware capabilities with cloud-based inference for complex tasks. This market shift positions open models to handle the majority of daily enterprise workflows, reducing reliance on expensive frontier closed models while navigating geopolitical security concerns through rigorous supply chain verification and secure hosting environments.
- a16z59 min
Why AI Agents Could Finally Reinvent the Credit Card
Erik Torenberg, Alex Rampell, Max Levchin
This analysis examines the structural dominance of credit cards in high-frequency micro-transactions due to superior user experience, contrasting this with the declining revenue efficiency of high-value wire transfers and the friction that historically limited digital payment innovation. It details Affirm's strategic pivot from B2B financing to consumer "Buy Now, Pay Later" models, leveraging transparent zero-interest terms and machine learning underwriting to achieve negative customer acquisition costs within the direct-to-consumer mattress sector. Finally, the discussion outlines how PayPal's culture of entrepreneurial trust enabled a network of high-risk ventures while highlighting emerging AI-driven shifts where agentic systems may eventually optimize payment selection and negotiation, potentially displacing the static credit card interface.
NVIDIA Crushes Quarter | OpenAI Cuts Off Cursor | Instinct Hits $2.5B Valuation
Jason Lemkin, Rory O'Driscoll, Harry Stebbings
NVIDIA reported record $96.2 billion quarterly revenue and announced strategic talks to acquire Hugging Face for $12.9 billion to secure its position in the open-weights inference market. Simultaneously, the broader AI ecosystem is defined by aggressive venture capital deployment into personal agents and coding tools, alongside intensifying conflicts between major players like OpenAI and Cursor over data access and intellectual property. These developments are driving a shift toward "compound startups" that must achieve 100x faster development velocities to survive, while emerging security threats from autonomous agents force organizations to rapidly upgrade defense protocols.
- Jane Street1h 25m
Wrestling the World Into Rows with Eric Mannes
Eric Manis details Jane Street's evolution from a trading firm into a technology-driven organization by shifting from centralized infrastructure to embedded "desk devs" and launching a scaled alternative data team. The firm navigates complex market mechanics, such as the 2020 negative oil pricing event, by prioritizing rigorous data engineering and physical world insight over pure mathematical modeling. This strategic focus on high-quality unstructured data and specialized hiring practices has enabled the company to transform raw information into actionable trading signals while maintaining robust risk management systems.
- a16z1h 3m
Can AI Learn Mathematical Intuition?
Recent AI advancements have achieved fully autonomous results like the Erdős Unit Distance Problem, yet the mathematical community warns that over-reliance on these tools risks homogenizing research and stifling the diverse human intuition required for genuine theoretical breakthroughs. While models excel at executing known techniques and verifying logical steps, they currently lack the capacity to build new theories without human-derived "hints," necessitating a collaborative model where mathematicians guide AI to discover deeper conceptual statements. Experts argue that to avoid incentivizing low-insight automation, the field must adapt educational and academic structures to prioritize deep conceptual understanding and the maintenance of cognitive diversity over rapid paper production.
- Sequoia Capital52 min
Making Cities Awesome: Peregrine’s Nick Noone & Ben Rudolph
Nick Noone, Ben Rudolph, Sonya Huang
Founded by ex-Palantir and UNHCR veterans Nick Benes and Ben Hallowell, Peregrine deploys a "forward-deployed" engineering model to help municipalities build privacy-preserving data infrastructure without creating a surveillance state. The company leverages agentic AI to automate 95% of complex data integration and execute rapid analytics, such as identifying hidden crime patterns in Florida or simulating hurricane impacts for local leaders. By maintaining strict local data sovereignty and reducing delivery costs below one million dollars annually, Peregrine enables thousands of unique cities to preserve institutional memory and solve specific community safety challenges.