Latest Interviews
Showing 226–240 of 3,490 transcripts.
Clear all filters- Milken Institute59 min
FinTech's Global Playbook: Breaking Barriers and Borders | Global Conference 2026
Nicole Valentine, Roberto Campos Neto, Denelle Dixon, Nigel Morris, Haseeb Qureshi, Barry Silbert
Industry pioneers including Roberto Campos Neto, Nigel Morris, and Danelle Dixon convened to map the global shift from legacy banking to a decentralized financial system driven by stablecoins, tokenization, and AI. The panel detailed how digital rails like Stellar and Nubank are bancarizing millions in Latin America while stablecoins challenge state power by enabling permissionless value transfer across borders. Ultimately, the discussion established that future leadership in this $300 billion sector demands extreme adaptability and technical literacy to navigate a volatile landscape where agentic commerce and asset tokenization are redefining economic sovereignty.
- Y Combinator47 min
Inside YC's AI Playbook
Pete Koomen, Gary, Jared, Diana, Tom, Boris
Y Combinator has redefined its operational model by evolving into a super AI-native organization that treats artificial intelligence as a foundational infrastructure rather than a mere tool, enabling autonomous agents to access a unified PostgreSQL database for complex business logic. This architecture supports a dynamic ecosystem of over 350 specialized tools and a daily "dream cycle" process that refines workflows based on meeting transcripts, effectively compressing employee onboarding and eliminating traditional manual coding bottlenecks. By broadcasting internal agent interactions to public channels and investing heavily in token costs, YC advocates for a decentralized future of just-in-time software where human prompts drive the interface, positioning the firm to leapfrog competitors reliant on conventional co-pilot methodologies.
- a16z55 min
The $1 Trillion Firm That Refuses The Private Equity Label | a16z
Apollo Global Management is pivoting from traditional private equity into a global retirement services giant with over $1 trillion in assets to address systemic market concentration and fund the capital-intensive AI infrastructure boom expected in 2025 and 2026. By standardizing private credit products and expanding into hybrid equity, the firm aims to provide diversification for public markets while navigating the shift toward hard-asset financing for data centers and energy. Simultaneously, Apollo is restructuring its organizational culture to prioritize merit and technological adaptation, positioning itself to capture value in a landscape where traditional enterprise software valuations face obsolescence due to artificial intelligence.
- Milken Institute1h 0m
Capital in Motion: Repositioning at Scale for the Next Cycle | Global Conference 2026
Sara Eisen, Marcie Frost, Ron O'Hanley, Harvey Schwartz, Daniel Simkowitz
Geopolitical conflicts and tariff pressures are driving a fundamental reprioritization of global capital toward national security, supply chain resilience, and AI infrastructure, fundamentally altering the fifty-year status quo of international markets. Leading institutional investors, including Carlyle, State Street, and Morgan Stanley, characterize the current private credit environment as a healthy cycle transition rather than a systemic risk while deploying significant resources to capture the estimated $3.2 trillion in shifting sovereign wealth and the emerging artificial intelligence sector. As the global economy pivots to prioritize defense and compute capacity, market participants are redefining portfolio allocations to focus on US innovation hubs, robust Asian markets, and rigorous underwriting standards to navigate rising capital demands and potential labor displacement.
- 80,000 Hours1h 7m
How to pivot before the intelligence explosion
Zershaaneh Qureshi, Benjamin Todd, Zashana, Ben Todd
Ben Todd and the *80,000 Hours* team outline a strategic framework for navigating AI risks by analyzing three potential timelines, from rapid AGI emergence to compute plateaus, while urging professionals to build career capital in operations, policy, and communication roles. The discussion details how automating AI research could compress five years of progress into months, creating extreme power concentrations that demand urgent governance and diversified workforce strategies to mitigate inequality. Finally, the event offers a five-step transition playbook and emphasizes that marginal improvements in career capital, donations, and political advocacy can significantly increase the probability of a positive outcome in an era of accelerated technological change.
Cerebras CEO on the Future of Data Centres, Token Costs & Memory | Should US Companies Sell to China
Andrew Feldman, Harry Stebbings
Cerebrus CEO Andrew Feldman highlights a $25 billion backlog in AI data center construction and persistent High Bandwidth Memory shortages that have driven hardware costs up fivefold. Following Cerebrus's historic $5.5 billion IPO and a $20+ billion partnership with OpenAI, the firm distinguishes itself by bypassing memory constraints through SRAM architecture and securing a six-point-seven times speed advantage over competing GPU clouds. Feldman further argues that geopolitical tensions necessitate stricter U.S. control over semiconductor exports to China while advocating for a twenty-year regulatory exemption to accelerate domestic fab construction and resolve the industry's looming electricity supply limits.
- Sequoia Capital46 min
How Cursor Trained Composer on Fireworks: Distributed Infrastructure for High-Performance RL
Federico Cassano, Dmytro Dzhulgakov, Sonya Huang
Cursor has pivoted from a pure application company to a foundation model developer by training Composer 2, a specialized software engineering model built on a Kimi 2.5 base using a global, asynchronous pipeline to maximize compute efficiency. The team deployed a custom infrastructure that integrates Reinforcement Learning from real-time user feedback and simulated rollouts while overcoming synchronization challenges through lossless delta compression and custom GPU kernels. This strategic approach allows Cursor to saturate model capacity with high-value coding data, achieving competitive performance at a fraction of the cost of general-purpose models while moving the industry toward baked-in specialized behaviors rather than prompt engineering.
Why Anthropic Are Causing a Comp Crisis & Why You’d Never Hire From Salesforce or ServiceNow
Chad Peets, Chris Degnan, Harry Stebbings
Snowflake's former CRO Chris Dagnon and CEO Chan Peets have formed a strategic partnership to address the critical challenge of building world-class sales teams, leveraging their contrasting "yin and yang" management styles to reshape hiring standards and quota-setting practices. The duo critiques the limitations of hiring from monopoly-driven environments like Salesforce and ServiceNow, advocating instead for candidates with proven grit at Tier 3 brands and warning founders against the inflated ARR signals and unsustainable compensation models currently prevalent in the AI sector. Their collaboration aims to help startups navigate a shifting landscape where traditional SaaS licensing is transitioning to consumption models, while simultaneously demanding rigorous accountability, global expansion, and a culture that prioritizes high-performance retention over socialist compensation structures.
- Stanford Online48 min
Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Enterprise Internal Knowledge
Stanford graduate and Applied Compute CEO Yash Patil explains how the AI industry is shifting from general pre-training to specialized post-training on proprietary data to solve enterprise bottlenecks. He argues that while frontier models like OpenAI's O1 leverage test-time compute, future progress depends on continual learning from sparse, real-world rewards and deterministic environments like software coding. Patil concludes with a bullish outlook on compute hardware while warning that pure data-selling businesses will fail as synthetic generation and robotics become the new differentiators.
- Dwarkesh Patel1h 20m
Chip design from the bottom up – Reiner Pope
This analysis dissects the hardware architecture of modern AI accelerators, detailing how Multiply-Accumulate units and systolic arrays minimize data movement to overcome the area and energy costs of traditional CPU logic. It contrasts fixed-function ASICs and programmable FPGAs while highlighting the strategic shift from cache-based CPU designs to deterministic scratchpads in TPUs to optimize compute-to-memory ratios. Furthermore, the discussion evaluates current trends such as low-precision FP4 arithmetic and splittable array topologies, emphasizing that quadratic scaling and massive parallelism drive future efficiency gains in silicon design.
- Y Combinator50 min
How The Best Companies Defend Against Mediocrity And Rot
Eric Ries exposes how the 1980s doctrine of shareholder primacy systematically undermines long-term company value, citing cases like Jeff Lawson's ouster at Twilio and Saul Price's departure from FedMart as evidence that founder control is often lost to short-term investor demands. To counter this instability, the event advocates for structural reforms such as the industrial foundation model, which legally prioritizes mission over profit, as demonstrated by the sustained success of entities like Novo Nordisk and the mission-preserving safeguards of Anthropic. The presentation concludes by urging founders to immediately adopt Public Benefit Corporation status and design "governance fortresses" to insulate their organizations from the inherent conflicts of standard corporate governance.
CIO of Marc & Ben's Multi-Family Office: SpaceX IPO, Anthropic & OpenAI
Michel Del Buono, Molly O'Shea
This comprehensive discussion explores wealth optimization strategies for founders and high-net-worth individuals, covering critical topics such as Trust, Estate, and Tax Planning, Secondary Market dynamics, and Portfolio Construction. Key figures and experts address the risks of isolated trust structures, the complexities of SPV secondary deals, and the tax efficiencies of real assets like data centers and qualified small business stock. The dialogue concludes by emphasizing a multidisciplinary approach that aligns investment diversification with global mobility choices and specific family values to maximize legacy and minimize unnecessary tax liabilities.
Anthropic Raises $30BN at $900BN Price | SpaceX Files S1: How Does it Trade | Cerebras Smashes Day 1
Jason Lemkin, Rory O'Driscoll, Harry Stebbings
Anthropic secured $30 billion at a $900 billion valuation, with founder Dario Amodei prioritizing rapid funding to build independent gigawatt-scale compute infrastructure rather than relying on hyperscalers. This capital injection contrasts with OpenAI's complex contingent structures and precedes a projected November IPO, while Cerebras' successful debut validates strong market demand for AI hardware despite growing public skepticism over layoffs and job displacement. The event highlights a strategic shift where enterprise AI adoption is becoming cost-efficient enough to challenge trillion-dollar revenue projections, forcing traditional SaaS models to compete against autonomous agents and massive infrastructure expansion.
- Sequoia Capital1h 3m
Notion’s Ivan Zhao: The Refounder
Ivan Zhao, Jack Dorsey, Brian Armstrong, B Halligan
Notion CEO Ivan Jawan has steered the company through two strategic refoundings, most recently pivoting to an AI-native model that replaces traditional hierarchies with a fluid "jazz band" structure relying on self-managed teams and AI as the central information processor. This transformation involves restructuring hiring to prioritize individual agency over experience, merging product roles to leverage AI agents, and shifting compensation toward a high-meritocracy "wartime" model. By treating product development as non-deterministic experimentation rather than rigid planning, Notion aims to scale effectively while maintaining a culture that functions as a shared belief system among its fifty to sixty acquired founder-employees.
- Stanford Online47 min
Stanford CS153 Frontier Systems | The AI Native Company: How One Founder Becomes a 1000x Engineer
This session outlines a paradigm shift where AI-native tools compress startup development timelines from years to months, enabling six-person teams to generate $10M in revenue through standardized "compute agreements" and high-productivity frameworks like the G-Stack. Speakers detail the architectural evolution from human-dependent workflows to closed-loop agentic systems that automate back-office functions, citing successful unicorns like Salient and Happy Robot as proof of concept for these rapid scaling models. Ultimately, the discussion defines a new organizational hierarchy where founders act as "AI founders" who curate evaluation metrics and orchestrate autonomous agents to manage the complexity of building companies that previously required hundreds of employees.