Latest Interviews
Showing 1–14 of 14 transcripts.
Clear all filters- Sequoia Capital10 min
From Early Failures to ‘Clash of Clans’ and ‘Brawl Stars’ - Supercell ft Ilkka Paananen
Ilkka Paananen, Maya Hoffree, Joost van Dreunen, Roelof Botha
Supercell established a unique corporate structure known as "cells" that empowers individual game teams with startup-like autonomy, a strategy that enabled leaders to cancel their initial €8 million investment in the Facebook title *Gunshine* to pivot successfully toward mobile platforms. This bold approach fostered a culture where project failures are celebrated as learning experiments, ultimately leading to the creation of industry-defining hits like *Clash of Clans* and *Hay Day* that currently command 60% of total industry playtime. Now fifteen years old, the company continues to navigate the high barrier of launching new titles by embracing increased risk-taking, aiming to emulate the century-long legacy of Nintendo or LEGO while maintaining operational excellence.
- Sequoia Capital15 min
The $10 Trillion AI Revolution: Why It’s Bigger Than the Industrial Revolution
Sequoia Capital frames the current AI landscape as a "cognitive revolution" poised to expand the $10 trillion U.S. services market by applying the "specialization imperative" to transform general-purpose infrastructure into specific high-value applications. The firm targets startups like Harvey, Factory, and Nominal that deliver tangible leverage in professional roles, while anticipating a shift in investment metrics toward real-world performance, reinforcement learning, and compute efficiency per knowledge worker. Looking 12 to 18 months ahead, Sequoia prioritizes breakthroughs in persistent memory, autonomous agent communication protocols, AI voice interfaces, and comprehensive security layers to accelerate the creation of large-scale public service companies.
- Sequoia Capital10 min
How to Scale AI Application Inference 100x ft. Fireworks’ Lin Qiao
Fireworks addresses the critical gap between generic model capabilities and specific application needs by co-optimizing inference across quality, speed, and concurrency for over 100,000 variables. This strategic approach reduces inference costs by 10x to 100x through virtual cloud infrastructure that dynamically selects hardware and aligns data distributions, enabling rapid enterprise scaling. The platform has already demonstrated success in transforming high-cost operations into sustainable models, exemplified by a food chain expanding to 1,000 shops and a software firm serving 25 million developers within three months.
- Sequoia Capital20 min
Will Open Source AI Overtake Closed Models? Ft. Olama, Fireworks and Open Router
Jeff Morgan, Dmytro Dzhulgakov, Alex Atallah, Dima, Matthew Walkerman
Industry leaders from Ollama, Fireworks, and OpenRouter advocate for a balanced future where open-source and closed-source models each command 50% of inference tokens, driven by the strategic advantages of decentralized innovation and lower capital barriers. While current open adoption sits at 30%, panelists predict this share will expand as foundational models improve through reinforcement learning and enterprises prioritize ownership of proprietary fine-tuned artifacts. This shift relies critically on sustainable decentralized inference infrastructure to compete against the entrenched advantages of large, closed-source providers.
- Sequoia Capital7 min
Open Evidence Captures Doctors’ Collective Wisdom with AI ft. Zachary Ziegler
OpenEvidence, a medical search tool used daily by over 25% of US physicians, recently enabled an internal medicine doctor to successfully manage an in-flight emergency for an immunocompromised cancer patient without diverting the aircraft. By synthesizing current literature and CDC data, the platform confirmed the patient did not require immediate intervention and provided a targeted treatment protocol that ensured a positive outcome upon landing. Building on this high-volume, real-time performance, the company is now expanding into direct workflow integration and developing an Aggregate Clinical Wisdom initiative to encode expert consensus from top specialists across various fields.
- Sequoia Capital10 min
9 Years to AGI? OpenAI’s Dan Roberts Reasons About Emulating Einstein
OpenAI demonstrated a strategic pivot toward test-time compute and reinforcement learning by showcasing models like O1 and O3 that solve complex physics problems, such as quantum electrodynamics and General Relativity, in minutes compared to human timescales. To support this new scaling paradigm where reasoning effort outweighs pre-training data, the organization plans to raise $500 billion to construct massive data center facilities in Abilene, Texas. This infrastructure investment aims to accelerate a timeline predicting that within nine years, systems will evolve from reproducing existing scientific knowledge to generating novel discoveries comparable to Einstein's major breakthroughs.
- Sequoia Capital9 min
How OpenAI Built its Groundbreaking Deep Research Product ft. Isa Fulford
OpenAI's Deep Research introduces an agentic o3 model capable of executing complex, multi-step online investigations over five to thirty minutes to generate analyst-level reports. Targeted at professionals like venture capitalists and academics, the system synthesizes cross-lingual data through interactive clarifications and real-time transparency into its reasoning process. While current versions prioritize read-only browsing and citation granularity, the roadmap outlines plans to integrate these tools into broader reasoning models and enable autonomous action-taking based on findings.
- Sequoia Capital19 min
The Data Center is the New Unit of Compute: Crusoe CEO Chase Lochmiller
Chase Lochmiller, David Kahn, Pat
Crusoe Energy is rapidly constructing massive AI factories in Abilene, Texas, leveraging a vertically integrated supply chain to deliver gigawatts of power capacity decades ahead of traditional utility timelines. By repurposing stranded renewable energy and deploying advanced cooling architectures, the company accelerates the shift toward sovereign AI infrastructure while addressing critical bottlenecks in power and hardware availability. Founder Chase Lockmiller positions this industrial-scale approach as the mechanism to manufacture intelligence, creating a resilient foundation for the next phase of artificial general intelligence.
- Sequoia Capital18 min
The Physical Turing Test: Jim Fan on Nvidia's Roadmap for Embodied AI
NVIDIA Director Jim Phan outlines the "Physical Turing Test," a benchmark for robots performing complex physical tasks indistinguishable from human performance, while identifying data scarcity as the primary bottleneck for current systems. To overcome this, NVIDIA employs Simulation 2.0, utilizing generative models like Robocasa and video diffusion to exponentially scale training environments and introduce the GR00T N1 open-source model capable of zero-shot generalist control. This technological evolution aims to transition the physical world into a "Physical API," where software-defined skills enable autonomous robots to seamlessly handle household and industrial tasks, effectively embedding human-like dexterity into everyday infrastructure.
- Sequoia Capital8 min
Ambient Agents and the New Agent Inbox ft. Harrison Chase
LangChain CEO Harrison Chase introduces ambient agents as background systems designed to execute complex, multi-step operations by monitoring event streams rather than relying on direct chat input. These agents operate within a strict human-in-the-loop framework that utilizes patterns like action approval, editing, and time-travel rollback to ensure accuracy while preventing full autonomy. To support this architecture, LangChain has enhanced its LangGraph infrastructure for state persistence and scalability while deploying an Agent Inbox UI that enables users to manage long-running workflows through direct oversight and feedback integration.
- Sequoia Capital7 min
AI-augmented game development with Inworld co-founder Kylan Gibbs
Kylan In-World has launched a vertically integrated platform combining a local execution runtime engine with an AI studio to resolve the industry tension between technical performance and creative control in game development. Backed by strategic partnerships with NVIDIA, Microsoft Studios, and Ubisoft, the system powers dynamic narratives by processing multi-modal inputs in parallel to generate real-time quests, adjust environmental states, and modify mission objectives based on player dialogue. By prioritizing local latency reduction over cloud-based models, the technology enables non-scripted interactions where emotional states and relationship dynamics evolve in the backend to directly influence gameplay mechanics.
- Sequoia Capital11 min
AI-powered workflow automation with Zapier co-founder Mike Knoop
Zapier is launching Zapier Central, a new platform that replaces its traditional workflow canvas with natural language "AI Bots" capable of executing over 500,000 autonomous actions. These self-healing agents utilize zero-shot inference to automatically configure triggers, resolve parameters, and repair broken steps when external variables shift without manual intervention. The system now supports all 7,000 existing integrations while allowing users to refine bot behavior through direct feedback and a threading feature for step-level approval.
- Sequoia Capital7 min
What's next for AI agents ft. LangChain's Harrison Chase
Harrison Chase positions LangChain as the dominant generative orchestration platform, while defining agent systems as loop-based entities that utilize language models to plan, act, and observe external tools. To address current reliability gaps in complex reasoning, the discourse advocates for "flow engineering" strategies that offload planning logic to human-designed state machines and introduces a "rewind and edit" user experience to facilitate human-in-the-loop correction. Furthermore, the next generation of agent applications is expected to integrate distinct procedural and personalized memory architectures, enabling systems to retain specific workflows and user preferences for enhanced personalization and task completion.
- Sequoia Capital14 min
What's next for AI agentic workflows ft. Andrew Ng of AI Fund
AI agents are driving a paradigm shift from single-step prompting to iterative workflows that combine reflection, multi-agent collaboration, tool use, and planning to achieve results that can surpass larger, faster models running in zero-shot mode. This approach allows systems using smaller language models like GPT-3.5 to outperform GPT-4 on complex benchmarks such as HumanEval by enabling self-correction loops and specialized role delegation. While reflection patterns are now robust enough for immediate integration, emerging capabilities in planning and multi-agent debate are expected to dramatically expand the scope of autonomous tasks over the coming year.