Latest Interviews

How Open Source Became AI's Backbone | Inferact with a16z

Elena Burger, Matt Bornstein, Simon Mo

VLLM serves as a critical inference engine for over half a million GPUs, bridging the gap between research and production by collaborating with hardware vendors and model labs to ensure day-zero compatibility for over 1,000 architectures. The platform addresses the industry's shift toward open-weight models by providing granular control over performance tiers, data retention, and guardrails that proprietary APIs often restrict. Looking forward, VLLM advocates for an ecosystem where open and frontier models become indistinguishable in capability, with infrastructure innovation focusing on optimization speed and algorithmic efficiency rather than mere data sourcing.

Chai Discovery's Bitter Lesson: Drug Design Is Another Scaling Problem

Josh Meier, Matt McPartlon, Pat Grady, Sonali Singh

Chai Discovery is industrializing drug discovery by deploying a simplified, AI-driven infrastructure that replaces traditional trial-and-error with scalable molecule design, partnering with major pharmaceutical firms like Eli Lilly and Pfizer rather than managing a full internal pipeline. The company's second-generation model has achieved a 15% binding success rate through diffusion-based generation and a continuous feedback loop from wet-lab experiments, effectively targeting historically undruggable biological structures. By shifting the industry toward computational "last in class" solutions, Chai aims to accelerate development timelines from months to days while ensuring extreme safety and manufacturability at the molecular generation stage.

Arena CEO: There Will be a $100BN US Open-Source Model & Data is a Trillion Dollar Market

Anastasios Angelopoulos, Harry Stebbings

Arena founder Anastasios outlines a shifting AI landscape where Chinese open-source models like Kimi K3 challenge American closed-source dominance, while geopolitical tensions and security concerns drive an anticipated five-year migration toward sovereign, fine-tuned architectures. The event analyzes critical economic friction points, including the unsustainability of current open-source business models, the looming risk of US export controls on advanced chips, and the consolidation of a volatile market where 75% of new "neo-labs" may fail or be acquired solely for talent. Ultimately, the discussion projects that future value will derive from integrating data into biological feedback loops and robust physical infrastructure, rather than the current hype surrounding GPU memory and speculative software applications.

How Decagon Runs 90% of Its Agents on Open-Source Models

Sarah Wang, Kimberly Tan, Jesse Zhang, Ashwin Sreenivas

Decagon Labs challenges the prevailing 2026 narrative that AI agents will replace all software by establishing a dedicated "model factory" that prioritizes open-source fine-tuning over frontier models to achieve superior latency for voice interactions. The company differentiates its enterprise deployment through a "glass box" approach and its Duet Autopilot system, which automates the creation of agent procedures and reduces production timelines from years to months. Despite rapid international expansion and the lowering of technical barriers, Decagon contends that the primary constraint remains human talent acquisition while affirming that AI will drive new service demand rather than eliminating careers or rendering legacy SaaS obsolete.

AssemblyAI Now Handles 4x YouTube's Daily Volume

Dylan Fox, Molly O'Shea

AssemblyAI has achieved explosive growth with weekly API conversations surging 800% to surpass 120 million voice interactions, driven by CEO Dylan Fox's infrastructure-focused strategy that supports over one million developers. The company distinguishes itself through advanced, context-aware voice models capable of real-time multi-language switching and noise filtering, while maintaining a lean, AI-native operational structure. Looking forward, leadership anticipates voice becoming a universal consumer interface within three years, though the industry must urgently address ethical transparency and on-device latency challenges to ensure trust.

“Every small business should run itself” | Lassie with a16z

Alex Rampell, Olivia Moore, Steijn Pelle, Frédéric Renken

Founders of Lassie address severe labor shortages in U.S. small businesses by developing autonomous AI agents that execute complex administrative workflows rather than merely digitizing data storage. Initially launched in the dental sector to replace 200 hours of monthly manual paperwork for practices like Dr. Kwan's, the platform utilizes a human-in-the-loop evolution to achieve 95% automation and targets a $1 billion market by selling labor savings instead of software licenses. This approach leverages regulatory shifts toward direct deposit and proprietary workflow ontologies to create a defensible moat against incumbents, with plans to expand into fully autonomous business operations across healthcare and other labor-constrained industries.

Jensen's Open-Weights Letter | Google Cloud Grows 82% But The Market Tanks

Jensen, Jason Lemkin, Rory O'Driscoll, Harry Stebbings

Jensen Huang's public endorsement of an open weights manifesto has ignited a strategic realignment among component manufacturers to counterbalance the dominance of Anthropic and OpenAI, while simultaneously exposing tensions regarding regulatory capture and the security risks posed by autonomous AI agents. This shifting landscape is further complicated by substantial capital deployments, including Travis Kalanick's $1.7 billion raise for industrial robotics and Google's record revenue paired with investor anxiety over its negative free cash flow. Amidst these developments, market dynamics are becoming increasingly volatile as specialized chip startups challenge NVIDIA's infrastructure, legacy SaaS firms struggle with growth ceilings, and geopolitical concerns threaten to conflate open-source models with foreign-origin restrictions.

The Robot Episode: Four Leaders on What's Coming

Dr. Péter Fankhauser, Bernt Børnich, Amanda McMaster, Jonathan Hurst, J-Cal

Leading robotics firms including Anybotics, Boston Dynamics, and Agility Robotics have collectively deployed over 1,000 specialized units globally to replace humans in hazardous industrial settings, prioritizing data sovereignty and ISO cybersecurity standards to avoid reliance on Chinese hardware. These companies are currently transitioning from pure detection to scalable autonomy through platform-based ecosystems and cost reductions, with humanoids targeting a $40,000 price point and quadrupeds enabling continuous 24-hour monitoring in extreme environments. While immediate returns focus on safety and leak prevention, the industry anticipates a hard take-off in manufacturing capabilities within a decade as foundational AI models enable complex, multi-arm manipulation without physical safety barriers.

Building the Automated AGI Lab: Core Automation's Jerry Tworek and Rohan Anil

Jerry Tworek, Rohan Anil, Sonya Huang, Pat Grady

Founded by Jerry Liu and Rohan Ramachandran, Core Automation aims to replace static Transformer models with a new class of AI systems capable of continual, test-time learning. The organization is building an automated research lab designed to overcome architectural bottlenecks by developing hardware-efficient kernels and enabling models to autonomously optimize their own code. Success for the venture is defined by the system's ability to self-improve without human intervention, effectively extending the team's operations while bypassing the diminishing returns of current scaling methods.

Blake Scholl: How 50 People Built a Supersonic Jet

Blake Scholl

Founded by Blake Scholl in 2014, Boom Supersonic successfully developed the XB-1, the first privately built jet to break the sound barrier, using a lean team and software-driven engineering to overcome decades of aviation stagnation. This historic flight directly catalyzed a shift in US federal policy, prompting an Executive Order that legalized supersonic flight over land and clearing the path for the upcoming Overture airliner. By vertically integrating manufacturing and creating revenue through ground-based engines, the company aims to double global travel speeds while eliminating the traditional sonic boom barrier.

Will Open-Source Threaten Anthropic's Business & Do Margins Matter in a World of AI | Matt Murphy

Matt Murphy, Harry Stebbings

Menlo Partners led Anthropic's initial $10 million seed round and subsequently deployed a $500 million Special Purpose Vehicle to secure a leading position in the AI sector, prioritizing access to high-conviction outliers over traditional ownership mandates. This strategy supports a broader barbell approach where the firm targets hyper-growth seed companies like Lovable and OpenRouter while maintaining large growth positions, effectively bypassing the crowded Series A stage. By focusing on technical depth, operational efficiency, and global talent hubs, Menlo aims to maximize upside in a market shifting toward "winner-take-all" dynamics despite high valuations.

Mercor Head of Product on Revenue Concentration from Frontier Labs

Osvald Nitski, Harry Stebbings

McCore, led by CPO Oswald Nitzke, is navigating a hyper-growth phase driven by insatiable demand for frontier model training data while strategically pivoting from enterprise labs to self-serve tools for smaller enterprises. To manage operational complexity amidst AI coding agent proliferation, the company is streamlining its product surface area and shifting hiring priorities toward senior candidates capable of rapid business impact assessment. Looking ahead, McCore anticipates expanding into robotics and cybersecurity data markets while maintaining a high-agency startup culture to address the persistent skills gap in enterprise AI deployment.

What Actually Makes A Startup Durable

Paul Graham and YC partners outline a strategic framework for navigating the AI era, emphasizing that while AI increases individual productivity by 1,000x, founders must target "hard" problems with durable moats to survive market saturation. The session advises building companies through co-founders who provide essential emotional support rather than just complementary skills, noting that human judgment remains critical for community building and navigating high-stakes pivots. Finally, students are offered over $25,000 in AI credits to neutralize geographical disadvantages, reinforcing the program's focus on rapid execution and deep market engagement over theoretical development.

BlackRock's Tony Kim on AI's Next Winners? Chips, Memory, Robotics & Quantum

Tony Kim, Molly O'Shea

Kim outlines a fundamental shift in the global technology sector where a $30 trillion hardware-centric economy is driven by a 10,000x increase in compute density and severe memory shortages known as the "Rampocalypse." Leading institutions are responding through silicon co-design and gigawatt-scale energy infrastructure while BlackRock allocates capital toward immediate compute needs and long-term bets on quantum and orbital data centers. The narrative concludes with strategic observations on China's robotics acceleration and the restructuring of traditional enterprises into AI-native entities through proprietary token flow architectures.

Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | The GPU Economy

Sunny Madra, Brad Gerstner, Apoorv Agrawal

Brad Gerstner of Altimeter Capital and Grok co-founder Sonny Maduro outline a transformative shift where AI distribution costs are now compute-intensive, driving the integration of deterministic architecture with Nvidia's GPU ecosystem to accelerate inference. This strategic fusion, which led to Nvidia's $20 billion acquisition of Grok, enables a 2.5x increase in token generation while addressing critical power and memory constraints to support the transition from chat-based tools to autonomous agents. As the industry approaches Artificial General Intelligence faster than anticipated, the convergence of these hardware innovations and emerging regulatory frameworks aims to redefine global economic output and the future value of human labor.