Latest Interviews
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Why World Models Could Change Robotics, 3D, and Creativity
Fei-Fei Li, Justin Johnson, Ben Mildenhall, Martin Casado
World Labs has unveiled Atlas, a unified spatial intelligence model that uniquely combines generative video with sparse 3D reconstruction to create high-fidelity simulations from as few as three input views. This architectural breakthrough enables "AI-complete" new view prediction and robotic real-to-sim transfer while reducing data capture requirements by up to 100 times compared to traditional dense methods. By treating 3D poses as native inputs, the system delivers consistent, dynamically stable environments that eliminate the unpredictability of standard generative video for applications ranging from industrial design to autonomous robot training.
- Goldman Sachs21 min
Why AI Spending is Driving Rates Higher
Mark Wilson, Jan Scheffel, George Cole
Global fixed income yields have surged to multi-decade highs driven by persistent fiscal deficits, stubborn inflation, and massive corporate capital expenditure for AI infrastructure. Federal Reserve Chair Jerome Powell signaled a continued hawkish stance, asserting that current monetary policy remains insufficient to curb inflation without further tightening. Analysts warn that while geopolitical instability and upcoming elections in France and the US pose political risks, the structural demand for capital from the AI sector and government borrowing will likely keep long-term yields elevated until productivity gains eventually materialize.
- Y Combinator21 min
Paul Graham On Startups, Ambition, and Great Founders
Paul Graham delivered his 47th Y Combinator batch talk, highlighting a shift toward high-seriousness ventures in logistics and cancer research while defining founder ambition through the "formidable" archetype of those who consistently achieve their goals. Graham analyzed the current AI landscape, noting its uneven "jagged frontier" and the economic reality that token costs now eclipse salaries despite rapid price declines. He concluded that Y Combinator's ecosystem remains vital for peer collaboration and that the next trillion-dollar company will emerge not from a specific idea but from formidable founders capable of adapting to shifting market conditions.
- Goldman Sachs33 min
The Outlook for Data Center Power Demand as AI Token Use Grows
Brian Singer, Carly Davenport, Allison Nathan, George Lee
Goldman Sachs forecasts a surge in U.S. power demand reaching a 3.5% CAGR through 2030, driven by a 170% rise in global data center consumption that will equal Japan's total electricity usage. This growth is propelled by hyperscaler spending hitting $2.1 trillion by 2029, though projects face critical bottlenecks from skilled labor shortages, interconnect queues, and over 300 local moratoria. Consequently, the sector is increasingly relying on 30 gigawatts of behind-the-meter natural gas generation as a bridge while navigating regulatory uncertainty and community opposition regarding grid stability and environmental impacts.
- Y Combinator40 min
Michael Kratsios: Inside the White House's AI Strategy
White House OSTP Director Michael Kratos advocates for an AI strategy that prioritizes open-weight models and rejects rigid regulatory thresholds, emphasizing a unified national standard to prevent incumbents from stifling startups. Through the report *A New Golden Age for Science*, the administration proposes shifting federal research funding toward private sector leadership while accelerating scientific breakthroughs via autonomous cloud labs and rapid-grant mechanisms. This approach complements President Trump's executive order on quantum computing and a broader "born free" philosophy that aims to remove barriers for digital technologies while carefully managing specific physical risks.
- Bank of America22 min
Global Rates & FX Views: August summer guide
Mark Cabana, Katie Craig, Adarsh Sinha
Bank of America Global Research forecasts a pause in U.S. Federal Reserve rate hikes through September and likely December due to soft macro data and historical electoral precedents, prompting the firm to close specific yield curve trades. Simultaneously, the strategy anticipates Japanese rate increases by mid-2026 to normalize the yen against the dollar while maintaining a hold on Canadian rates despite recent labor strength. Forward-looking analysis highlights upcoming catalysts including the Jackson Hole symposium and the Xi-Trump summit, which will be critical for determining whether markets shift toward a short-dollar view or maintain current neutral positioning.
- Sequoia Capital22 min
Continual Learning: How AI Agents Get Better With Every Use | Arjun Karanam, Trajectory
Arjun Karanam, Ronak, Gabe, Harrison, Nico, Harvey
Trajectory, co-founded by Arjun and Ronak, addresses the lack of accumulated experience in AI by building a platform that enables models to continuously learn from the 100 trillion daily tokens generated by real-world agent interactions. The company utilizes a dual-learning architecture combining differential privacy with reinforcement learning on user-corrected traces, allowing organizations to transition from static models to systems that compound capability through automated post-training and flexible harness optimization. By abstracting complex training parameters into a 15-minute workflow, Trajectory empowers enterprises to retain ownership of their specialized models while refining agent performance directly against production traffic.
- Sequoia Capital24 min
When to Build Your Own Agent Harness | Harrison Chase, LangChain
The framework defines autonomous agents as systems built from three owned components: the model, context, and a prioritized harness that orchestrates data flow through an iterative LLM loop. Organizations can customize this harness via middleware for domain-specific optimizations or maintain off-the-shelf versions for in-distribution tasks, ensuring compatibility through dynamic model profiles. Continuous improvement is driven by a flywheel where trace data from evaluations using the Harbor benchmark feeds into an automated engine that identifies failures and suggests prompt, code, or context fixes.
- Sequoia Capital26 min
RL Environments Explained: How AI Agents Learn Real-World Work | Brendan Foody, Mercor
Mercore has expanded its revenue run rate to $2 billion by transitioning the AI data market from basic crowdsourcing to high-skilled "agentic data" services that enable frontier labs to build complex reinforcement learning environments. The company leverages expert networks of lawyers, engineers, and doctors to create realistic simulated worlds with precise human-verified rubrics, demonstrating a fivefold increase in model performance on specific legal tasks during recent training. As the primary data vendor for major application layer companies, Mercore addresses the industry's need for ultra-long horizon tasks and social dynamics evaluations that synthetic models cannot yet self-generate.
- Sequoia Capital28 min
Post-Training Is How You Keep Your Taste | Fireworks CEO Lin Qiao
Fireworks CEO Linh Nguyen advocates for a strategic industry shift from relying on rented APIs to owning intelligence through deep model customization, enabling companies to preserve unique business judgment while reducing inference costs by five to ten times. This approach utilizes a structured lifecycle of data curation, fine-tuning, and serving loops to transition from generic prompting to specialized models, as demonstrated by success stories like Cursor and niche vertical leaders in healthcare and security. Ultimately, post-training is positioned as the critical mechanism for startups to scale after product-market fit by converting proprietary user data into unclonable domain expertise before high API expenses threaten unit economics.
- Sequoia Capital29 min
How Harvey Built a Research Lab on a Budget | Gabe Pereyra
Harvey, Gabe Pereyra, Brendan, Julio, Ross, Brock
Harvey differentiates itself from well-funded frontier labs by leveraging an application-layer strategy that combines synthetic data generation guided by domain experts with post-training on open-source models. The company builds specialized legal benchmarks and utilizes infrastructure partnerships to train agents on complex tasks like contract negotiation without exposing sensitive client information. By deploying these capabilities across multiple vendors and product surfaces, Harvey aims to solve organizational productivity challenges while mitigating the performance gaps inherent in current long-context environments.
- Y Combinator42 min
Peter Steinberger: What Happens When 4.7 Million People Let It Cook
Launched in November 2024 by a solo developer to solve personal automation needs, the open-source agent project "OpenClaw" rapidly evolved into a viral community initiative that engaged over 18,000 contributors and achieved 4.7 million weekly downloads by mid-2025. Rather than accepting venture capital or acquisition offers, the founder established a 501(c)(3) non-profit status with Nvidia support to maintain independence while addressing security misconceptions and refining the architecture for multimodal voice interactions. The project's trajectory highlights a strategic shift from proprietary models to open-weight alternatives, ultimately serving as a case study on sustaining developer velocity through personal enjoyment and rigorous community governance.
- Bank of America29 min
Global Rates & FX Views: NFP & refunding review
Sphia Salim, Aditya Bhave, Mark Cabana, Meghan Swiber
The July U.S. labor report revealed a net loss of 23,000 nonfarm payrolls driven by seasonal education declines and reduced hospitality staffing, though private payrolls remained resilient near break-even levels. This data, characterized by falling wage growth and a surprising drop in the unemployment rate due to labor force exit, has shifted Federal Reserve policy expectations toward a dovish stance with diminished probability for September rate hikes. Concurrently, Treasury guidance maintained constant auction sizes while coordinated yen interventions utilized Federal Reserve swap facilities, effectively limiting direct selling pressure on the U.S. debt market.
- Goldman Sachs32 min
Steven Tananbaum: The Evolution of Credit Investing and AI Opportunities
Steven Tananbaum, John Waldron, Steve Tenenbaum
GoldenTree Asset Management founder Steve Tenenbaum outlines current credit market risks driven by AI adoption, noting widened spreads for entities like SpaceX alongside his firm's evolution from post-2008 distress turnaround strategies to targeted 3.0 platform acquisitions. He details the firm's disciplined investment process, which prioritizes specific catalysts and strict asset coverage ratios to navigate complex environments like the 2020 oil services and European bank sectors where the firm generated billions in returns. Looking forward, Tenenbaum identifies dispersion caused by AI disruption as a key driver for new opportunities in private credit, software, and 30-year TIPS while emphasizing the necessity of rigorous process discipline over complex narratives.
- Y Combinator42 min
Garry Tan: The Future of AGI Is Personal
The speaker advocates for "Personal AGI," a system of user-owned agents that process vast personal context on private infrastructure to drastically increase output and preserve cognitive independence. Drawing parallels to Baruch Spinoza's rejection of institutional compromise, the talk details how "skill files" and hybrid architectures enable individuals to replace traditional workforces with scalable, compounding digital labor. This shift promises to democratize high-level execution by allowing founders to achieve unprecedented economic leverage while retaining full ownership of their generated knowledge and intellectual tools.