The a16z Show

a16z co-founder and General Partner Ben Horowitz joins James Norman on the inaugural episode of Vintage x Vintage for a conversation spanning entrepreneurship, investing, hip-hop, and what changes when AI makes building dramatically easier. Ben reflects on going from Netscape to becoming a first-time CEO, why every founder eventually hits a “we’re fucked, it’s over” moment, and what he learned from building a16z around the needs of entrepreneurs. He explains why great investors should look for world-class strengths rather than an absence of weaknesses, and why expanding the ways we recognize talent can raise the bar rather than lower it. They also look at the current AI cycle, why Ben believes it is bigger than the internet, how AI changes who can become a builder, and why the infrastructure beneath today’s models may need to be rebuilt from the ground up.

a16z's Raghu Raghuram and Guido Appenzeller sit down with Playground Global General Partner and former Intel CEO Pat Gelsinger to discuss the next wave of semiconductor innovation and the physical constraints shaping the AI buildout. Drawing on his experience designing Intel's 386 and 486 processors, Pat explains how AI could transform chip design, but also why faster design alone won't solve the industry's biggest problems. They examine the bottlenecks in manufacturing, memory bandwidth, advanced packaging, and power, and why today's explosion of specialized AI chips may eventually consolidate around a smaller number of architectures. They also discuss the potential for new memory technologies, the shift from copper to optical networking, and why energy capacity could become a major constraint on AI growth. Finally, they revisit Pat's VMware years to ask what virtualization might look like when infrastructure is built for agents rather than humans.

a16z’s Raghu Raghuram sits down with AWS CEO Matt Garman to discuss how AI is reshaping the cloud, from the needs of AI-native startups to infrastructure increasingly designed for agents. Matt explains how AWS is adapting as agents write code and manage infrastructure, why it’s reserving scarce GPU capacity for startups, and where custom chips like Trainium and Graviton fit into the AI stack. They also discuss Amazon's $220 billion capital investment, the shifting bottlenecks in the infrastructure buildout, what enterprises need to trust autonomous agents, and how AWS's own teams are building with agents.

a16z General Partner Angela Strange sits down with Valon’s Andrew Wang and Linda Du to unpack what it takes to rebuild the infrastructure underneath a $13 trillion mortgage market that still relies heavily on systems designed before the internet. Linda and Andrew explain why Valon chose the hardest path: becoming a regulated mortgage servicer, translating decades of federal and state regulation into software, and proving the platform on its own loans before selling it to the industry. That foundation made Valon roughly three times as efficient as traditional servicing and created the system of record it is now using to bring AI into complex mortgage workflows. They also discuss what AI makes possible on top of that infrastructure, from agents handling long-tail servicing tasks to voice interfaces and more personalized customer experiences. And they explain why deploying the technology into large regulated enterprises is ultimately as much a change-management challenge as a technical one.

a16z General Partner David George sits down with Armadin founder and CEO Kevin Mandia to discuss what happens to cybersecurity when attackers can operate at machine speed. After 30 years in security and building Mandiant, Kevin says AI convinced him to get back on the field. He explains how AI changes the economics of cyberattacks, allowing attackers to probe thousands of paths simultaneously, and why that means defense will ultimately need to become autonomous too. They also unpack Armadin’s approach: continuously attacking customers’ systems with AI to find exploitable vulnerabilities before adversaries do, then building toward autonomous defenses that can respond in real time. Kevin shares what Armadin has learned from finding more than 90 zero-days in production environments this year, why humans can’t remain in the detect-and-respond loop, and how the entire security stack could change over the next few years.

a16z Editorial Partner Elena Burger sits down with investing partners Olivia Moore and Josh Elman to unpack the seventh edition of a16z’s Top 100 Consumer AI Apps, including a new dimension this time: what consumers are actually paying for. The data reveals a striking power-user economy. Only a small share of consumers currently pay for AI, but among those who do, spending is heavily concentrated at the top. Olivia and Josh discuss why developers, creators, and other power users dominate spending today, and why subscriptions may not be the business model that ultimately brings consumer AI to everyone. They also dig into the rise of personal agents, the different trajectories of ChatGPT, Claude, and Gemini, how ads could reshape AI economics, and the enormous amount of consumer white space still left to build, from shopping and entertainment to social, dating, and marketplaces.

a16z General Partner David George joins Jack Altman on Uncapped to make the case that many of the biggest debates in AI are framed the wrong way. Frontier models or open source? Labs or applications? David’s answer is often “and.” With AI adoption still concentrated among a relatively small group of heavy users, he argues there could be room for multiple layers of the stack to grow at once. David and Jack discuss why demand for compute continues to outstrip supply, why applications can thrive even as frontier labs expand into new products, and why consumer AI may still be at the beginning of its biggest shift, from reactive chatbots to proactive assistants that can act on our behalf. They also zoom out to autonomy, robotics, healthcare, and the next generation of technology companies, before turning to venture itself: why David believes today’s product cycle is unusually strong, how capital can accelerate AI companies in ways it couldn’t during the SaaS era, and why founders and narrative become increasingly important as companies scale. This conversation originally appeared on Jack Altman’s Uncapped.

A16z’s Erik Torenberg sits down with OpenRouter’s Alex Atallah and Replit founder and CEO Amjad Masad to discuss why the future of AI may look less like one all-purpose model and more like an ecosystem of specialized models working together. Alex explains why OpenRouter is betting on “neurodiversity”: different models trained in different ways, routed and combined based on the job at hand. Amjad makes a similar case from inside the enterprise, where companies increasingly need to own their AI capabilities rather than depend entirely on a single model provider. They explore what happens when general-purpose agents give way to teams of specialized agents, why smaller models can sometimes be cheaper, safer, and easier to control, and how routing and model fusion could deliver frontier-level performance at lower cost. They also get into agent-to-agent communication, AI security, and why the next generation of companies may need an independence layer across models, clouds, and data.

a16z’s Seema Amble and Elena Burger sit down with Lio co-founder and CEO Vladimir Keil to ask where AI-native startups have an advantage when incumbent software companies already own the customer, the data, and the system of record. Their answer comes down to the work that happens outside those systems. In procurement, a final price in an ERP can hide hundreds of emails, spreadsheets, supplier conversations, engineering analyses, and decisions across legal, finance, and operations. Vlad explains how Lio uses multi-agent systems to take on more of that end-to-end work, from sourcing and RFQs to negotiation, shipment tracking, and invoices. They also discuss how enterprises learn to trust agents with increasingly consequential decisions, why the last 20% of an internal AI build can require most of the effort, and what happens when both buyers and suppliers have agents working on their behalf.

a16z’s Joel de la Garza sits down with DoxxNet founder Barrett Lyon to discuss what it would take to rebuild the internet around privacy, direct communication, and less dependence on centralized intermediaries. Barrett explains why he thinks traditional VPNs only solve part of the problem and how DoxxNet is building a parallel mesh network where users can communicate peer-to-peer, transfer large files, make calls, and message without routing those interactions through a central application server. He also explains why the company owns its infrastructure and runs its AI systems locally rather than relying on third-party inference providers. doxxnet_assembly They also get into the growing amount of tracking embedded across the internet, what happens when that data can be analyzed by increasingly capable AI, and why Barrett believes the underlying protocols of the internet are due for another wave of experimentation. Along the way, he shares lessons from decades of building internet infrastructure, from fighting early DDoS attacks to mapping the internet and building global networks.

a16z’s David George, Sarah Wang, Alex Immerman, and Santiago Rodriguez unpack 25 key charts from the latest State of Markets presentation, from the scale of the AI infrastructure buildout to what adoption looks like inside companies today. They examine why rising markets have so far been supported by earnings rather than multiple expansion, why hyperscaler CapEx is approaching $1 trillion annually, and why demand for compute continues to outrun supply. They also look at the downstream effects of that spending across chips, power, construction, and physical infrastructure. State of Markets Then they move up the stack: OpenAI and Anthropic’s revenue growth, the gap between AI deployment and measurable enterprise impact, the rise of agents, falling inference costs, and what all of this means for SaaS. They close with where the team is spending time next, including consumer agents, robotics, autonomy, AI and biology, personal health, defense, and the continued diffusion of AI across the enterprise. State of Markets

a16z General Partner Anish Acharya sits down with Assistant Benchmark creator David Pawlan to unpack the sudden explosion of personal AI agents and what it will take for one to become part of everyday life. David has been testing dozens of assistants across real-world tasks, from managing email and booking travel to handling financial admin. They discuss why the most useful agents may become increasingly invisible, proactively checking you into flights, finding refunds, filing reimbursements, or simply handling the small tasks that pile up across everyday life. They also explore whether the winning interface is an app, text thread, voice, or wearable; how much autonomy consumers will actually give their agents; and what happens when agents start interacting with other agents. From commerce and restaurant reservations to entirely new agent-native services, Anish and David ask what the internet looks like when software starts acting on our behalf. This episode was recorded on September 24, 2026.

a16z’s Ben Horowitz and Martin Casado sit down with TypeSafe AI founder Diogo Almeida to ask a simple question: AI has become remarkably capable, so where is all the automation? Diogo argues that coding agents may help us write software faster, but the software they produce still largely works the way software always has. TypeSafe is taking a different approach with Jev: putting intelligence inside software itself, so developers can build programs that reason about intent and make probabilistic decisions rather than simply generate text for a human to interpret. They discuss why reliability is the key to making AI genuinely programmable, how this could open a new era of probabilistic software, and why established SaaS companies may be particularly well positioned to benefit. Ultimately, Diogo’s goal is straightforward: technology that can reliably “do what I mean.”

a16z’s Katie Kirsch sits down with Harvey VP of Talent Maggie Landers to discuss what happens inside a company growing at AI speed, and how you preserve culture while adding more than 1,000 employees in a year. Maggie explains why Harvey prioritizes progress over perfection, how its values of simplicity, decisiveness, and “job’s not finished” shape the way people work, and why moving quickly requires giving employees significant trust and autonomy. For people accustomed to being the “A student,” that can mean learning to experiment, make mistakes, and course-correct quickly. They also get into how Harvey identifies people who can thrive in that environment, what changes when most of your company is relatively new, the role its founders play in maintaining culture, and why judgment becomes increasingly important when employees are given the freedom to move fast.