The a16z Show

In 2025, we saw the first glimpses of true AI agents. In 2026, every company will be rushing to get them into production, and they’ll need companies like Keycard to manage fleets of agents. In this conversation, a16z Partner Joel de la Garza sits down with Keycard Cofounder and CEO Ian Livingstone to discuss the continuum from copilots to agents, the security realities of tool-calling, why enterprises will adopt before consumers, and how to control your agents.

a16z co-founder and General Partner Marc Andreessen joins an AMA-style conversation to explain why AI is the largest technology shift he has experienced, how the cost of intelligence is collapsing, and why the market still feels early despite rapid adoption. The discussion covers how falling model costs and fast capability gains are reshaping pricing, distribution, and competition across the AI stack, why usage-based and value-based pricing are becoming standard, and how startups and incumbents are navigating big versus small models and open versus closed systems. Marc also addresses China’s progress, regulatory fragmentation, lessons from Europe, and why venture portfolios are designed to back multiple, conflicting outcomes at once.

Dylan Field is the co-founder and CEO of Figma, a design software company that went public in July 2025. Founded in 2012, Figma transformed how people design, prototype, and build products together. After a $20 billion acquisition attempt by Adobe collapsed in 2022 because of regulators, Dylan helped Figma rebound stronger than ever. Just three years later, Figma listed its shares at nearly $20 billion and its stock price more than tripled on its first trading day. A few highlights: Expanding a sleepy market Merging of designers and product roles Counter-narrative to polarizing CEOs If models get better, we have to Remembering Brat Summer

This episode is a special replay of David George’s conversation with Harry Stebbings on 20VC. David is a General Partner on a16z’s growth team, and in this discussion he breaks down how he thinks about breakout growth investing: why great business models are now table stakes, where real edge comes from non-consensus views on TAM, and how to underwrite upside in a world of higher prices and increasing competition. They also dig into the mechanics behind the scenes: unit economics at growth, “pull vs push” products, winner-take-most market structures, and how David decides when to double or triple down on a company. Along the way, they touch on SPACs, the rise of crossover funds, single-trigger decision making, and how David manages fear, pressure, and performance over the long arc of an investing career.

This episode is a special replay from The Generalist Podcast, featuring a conversation with a16z General Partner Martin Casado. Martin has lived through multiple tech waves as a founder, researcher, and investor, and in this discussion he shares how he thinks about the AI boom, why he believes we’re still early in the cycle, and how a market-first lens shapes his approach to investing. They also dig into the mechanics behind the scenes: why AI coding could become a multi-trillion-dollar market, how a16z evolved from a small generalist firm into a specialized organization, the growing role of open-source models, and why Martin believes AGI debates often obscure more meaningful questions about how technology actually creates value.

As 2025 comes to a close, consumer AI is entering a new phase. A small number of products now dominate everyday use, multimodal models have unlocked entirely new creative workflows, and the big labs have pushed aggressively into consumer experiences. At the same time, it is becoming clearer which ideas actually changed user behavior and which ones did not. In this episode, a16z consumer investors Anish Acharya, Olivia Moore, Justine Moore, and Bryan Kim look back at the biggest product and model shifts of 2025 and then look ahead to what 2026 may bring. They discuss why consumer AI appears to be trending toward winner-take-most, how subtle product design choices can matter more than raw model quality, and why templates, multimodality, and distribution are shaping the next wave of consumer products. Where do startups still have room to win? How will the role of the big labs continue to change? And what will it actually take for consumer AI apps to break out at scale in 2026?

New infrastructure primitives are creating entirely new rails for building. In this episode of Big Ideas 2026, we explore three foundational shifts that unlock new markets and workflows, not through incremental upgrades, but through primitives that compound over time. First, programmable money evolves beyond stablecoins into on-chain credit origination and synthetic financial products, offering lower operational costs and greater composability than traditional finance. Second, autonomy begins entering scientific research through collaborative labs, where AI reasoning models work alongside automation and robotics, and interpretability becomes essential for progress. Third, distribution itself becomes a primitive, as AI-native startups win early by selling to other startups at formation, then scale alongside the next generation of companies. You will hear from Guy Willette on the next phase of on-chain finance, Oliver Shu on autonomous labs and AI-assisted discovery, and James da Costa on the greenfield go-to-market strategy. Together, these ideas define what new infrastructure primitives really mean: the rails that enable entirely new systems to emerge, compound, and scale.

AI is moving into the physical economy. In this episode of Big Ideas 2026, we explore what changes when AI leaves the screen and becomes part of factories, construction sites, supply chains, and critical infrastructure. When the product is physical, reliability matters, real-world constraints appear quickly, and the advantage shifts from standalone software to end-to-end systems. You will hear from Erin Price-Wright on factory-first principles, Ryan McEntush on the electro-industrial stack, Zabie Elmgren on physical observability, and Will Bitsky on why data, not compute, determines who wins. Together, these ideas define what physical AI really means: not smarter chat, but deployable systems built for the real world, grounded in new operating models, industrial infrastructure, and defensible data collection.

Voice is becoming one of the fastest paths for AI to do real work, especially in regulated environments where accuracy and compliance matter. In this episode, we look at voice agents replacing and augmenting phone-based workflows, what trust and measurement look like when AI runs sensitive interactions, and how healthcare and consumer products shift toward continuous monitoring and deeper connection. The throughline is simple: as AI enters higher-stakes moments, the winners will be the systems people can trust and actually rely on.

AI is becoming the orchestration layer inside the enterprise. In this episode of Big Ideas 2026, we explore the shift from isolated AI copilots to coordinated multi-agent systems that plan, analyze, and execute work across teams and tools. This is not a new feature, but a new way workflows run inside large organizations. You will hear from Seema Amble on context extraction and coordinated agent teams, Angela Strange on why unified data and parallel workflows accelerate core replacement, Alex Immerman on multiplayer AI and execution boundaries, and David Haber on what makes these systems commercially defensible. Together, these perspectives define the enterprise orchestration layer: not a chatbot and not a standalone tool, but a coordinated system of agents that runs the workflow and delivers real outcomes across the business.

AI is moving from chat to action. In this episode of Big Ideas 2026, we unpack three shifts shaping what comes next for AI products. The change is not just smarter models, but software itself taking on a new form. You will hear from Marc Andrusko on the move from prompting to execution, Stephanie Zhang on building machine-legible systems, and Sarah Wang on agent layers that turn intent into outcomes. Together, these ideas tell a single story. Interfaces shift from chat to action, design shifts from human-first to agent-readable, and work shifts to agentic execution. AI stops being something you ask, and becomes something that does.

Fintech went from a full-blown surge to a near standstill in just two years. At its peak, about 25 percent of all venture dollars were pouring into the category. By late 2022, that number had collapsed to almost zero. In this conversation, a16z General Partner David Haber and Plaid cofounder and CEO Zach Perret unpack what actually happened during that cycle and why the market is heating up again. We explore how the industry moved from the explosive growth of 2020 and 2021 into a deep freeze, and why we are now seeing real momentum return. We also dig into the forces reshaping fintech today: AI’s outsized impact on fraud and underwriting, incumbents finally embracing external software, the renewed importance of deposits, and the rise of embedded finance across entirely new categories. Zach shares how Plaid has navigated these shifts, what the company is building now, and how he sees the next phase of fintech taking shape.

In this episode, we’re sharing a conversation with David George, General Partner at a16z on the firm’s growth investing team. David has been involved in backing many of the defining companies of this era and is now investing behind a new wave of AI startups. This discussion goes deep into how the a16z growth practice operates: how the team hires and develops a “Yankees-level” culture, how investment decisions get made without traditional committees, and how they build long-term relationships with founders years before investing. A major focus is AI. David talks through how the team is investing across the stack and why he believes this period could create some of the largest companies ever built. He also walks through the models that guide his thinking: why markets often misprice consistent growth, what makes “pull” businesses so durable, why many important markets become winner-take-all, and what he’s learned from studying exceptional founders — especially the “technical terminators” he’s drawn to.

What if America tried to eliminate crime instead of just reacting to it? Not with slogans, but with staffing, technology, and strategy scaled to the problem. In this episode, Erik Torenberg speaks with Garrett Langley, founder and CEO of Flock Safety, and Ben Horowitz, cofounder of a16z, about what is happening in the cities that are trying. Flock now works with over 5,000 communities to detect crime, recover missing children, and close cases faster than ever. Ben has been closely involved in Las Vegas, where Flock technology, drones, and community policing have raised clearance rates while reducing use of force. They outline what a real national crime-reduction strategy could look like: solving the police staffing crisis, using intelligence to make policing safer, understanding why clearance rates have collapsed, and how public–private partnerships are filling gaps cities cannot. They also tackle the hard questions around privacy, criminal justice failures, and the hidden role of organized crime in everyday offenses.

Ryo Lu spent years watching his designs die in meetings. Then he discovered the tool that lets designers ship code at the speed of thought: Cursor, the company where Ryo is now Head of Design. In this episode, a16z General Partner Jennifer Li sits down with Ryo to discuss why "taste" is the wrong framework for understanding the future, why purposeful apps are "selfish," how System 7 holds secrets about AI interfaces, and the radical bet that one codebase can serve everyone if you design the concepts right instead of the buttons.