a16z AI Policy Brief

a16z Policy

Your guide to AI public policy from the team at a16z. Each conversation bridges Washington and Little Tech, bringing together policy leaders, researchers, and builders to explore how the U.S. stays ahead in AI. a16zpolicy.substack.com

  1. AI is How America Builds Again

    6d ago

    AI is How America Builds Again

    Policymakers have spent years talking about rebuilding America’s industrial base, reshoring critical supply chains, strengthening defense production, and reducing U.S. dependence on China. But recognizing the need to build is not the same as having the ability to do it. Erin Price-Wright, general partner on Andreessen Horowitz’s American Dynamism practice, joins the AI Policy Brief to make the case that AI isn’t just a software story. It’s the defining factor in the sectors that determine whether the U.S. can build, power, and defend itself in the decades ahead. She and Matt Perault discuss how AI can help make the math work for building in the U.S. again—from accelerating mine permitting and coordinating complex industrial projects to designing factories, lowering the cost of automation, and bringing robotics to more factory floors. They also discuss where policy needs to catch up: the laws and regulations that make it too hard and slow to build new factories in the U.S. and defense procurement that still favors incumbents over startups. Finally, they discuss how the debates over data centers and jobs will shape whether America’s reindustrialization effort succeeds. The takeaway: if the U.S. gets the policy environment right, AI can strengthen the industrial base, help create new kinds of jobs, and give America a powerful competitive advantage. Topics covered: 00:00: Intro 00:54: Erin’s work investing in AI for the physical world 01:47: Why AI and reindustrialization are converging now 03:07: Applying AI to mining and critical minerals 08:28: What Ukraine reveals about defense production 18:13: How startups are breaking into government markets 20:16: Bringing a factory mindset to critical sectors and complex systems 24:39: How robotics can expand factory automation 30:22: What still makes it too hard to build in the U.S. 32:49: Using AI to design better, cheaper manufactured goods 35:05: Why data centers matter for reindustrialization 39:46: How compute could help modernize the grid and lower costs for consumers 42:50: Why AI could create new industrial jobs Resources: Subscribe to the a16z AI Policy Brief: https://a16zpolicy.substack.com/ Follow Matt Perault: https://x.com/MattPerault Follow Erin Price-Wright: https://x.com/espricewright Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit a16zpolicy.substack.com

    44 min
  2. Fixing the Front Door to Government

    May 19

    Fixing the Front Door to Government

    For AI startups, the policy landscape is expanding faster than most small teams can reasonably track. This creates a practical challenge for Little Tech: even when a startup wants to engage constructively, it may not have the resources to follow every debate in every jurisdiction. Ben Supple, head of global policy at ElevenLabs, joins Matt Perault to talk about his experience running a public policy function at a company that is scaling rapidly. ElevenLabs is a leader in voice AI, building products for creators, enterprises, and governments, while its public policy function is still small enough to count on one hand. The conversation offers a look at how a fast-growing AI company prioritizes policy work, builds relationships with governments, and makes the case for clear, consistent rules that startups can implement. They also discuss how voice AI can improve citizen services and outcomes: replacing rigid, menu-based phone trees with more intelligent conversational agents that can resolve issues, switch languages live, and offer greater accessibility. Topics covered: 00:00: Intro 01:42: What is ElevenLabs? 04:59: Voice AI use cases, from dubbing to customer service 06:59: The competitive landscape for voice AI 10:51: Building a policy function at ElevenLabs 12:00: Prioritizing policy work with a small team 15:13: Engaging policymakers across jurisdictions 18:11: Growing and shipping at startup speed 20:19: Human oversight and AI agents 22:54: Key policy issues for voice AI 25:42: Scaling into new regulatory obligations 30:17: State AI rules and the need for clear goalposts 32:25: ElevenLabs’ expansion in New York 34:10: Fixing the front door to government 36:22: Government use cases for voice AI 38:55: The social value of voice AI, One Million Voices, and accessibility Resources: Subscribe to the a16z AI Policy Brief: https://a16zpolicy.substack.com/ Follow Matt Perault: https://x.com/MattPerault Follow Ben Supple: https://www.linkedin.com/in/ben-supple-a900695/ Learn more about ElevenLabs for Government: https://elevenlabs.io/chatbot/government Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit a16zpolicy.substack.com

    41 min

  3. May 14

    A Guide to Crafting a Liability Regime for AI

    How should we hold people responsible when AI causes harm? That's the job of a liability regime. In this conversation, Jai Ramaswamy, chief legal and policy officer, joins Matt Perault, head of AI policy at a16z, to unpack the role of liability in AI policy: how to protect people from real harms without slowing innovation, limiting competition, or punishing the wrong actors. They discuss why trust is essential to long-term AI adoption, why liability should focus on harmful uses rather than general-purpose development, and how policymakers can design rules that hold bad actors accountable while giving startups room to build. The conversation also explores what a workable AI liability regime should prioritize: accountability, proportionality, enforcement of existing laws, and targeted updates where current law falls short. For founders, policymakers, and anyone tracking the future of AI regulation, this episode offers a guide for thinking about responsibility, risk, and innovation in the AI era. Topics covered: 00:00: Intro 01:00: Why AI liability is on the table now, and why it's been on Jai's mind for years 02:00: Why this matters — trust, long-term ecosystems, and the equities at stake 04:00: Failure modes at both ends — crushing liability vs. blanket immunity, and why neither serves Little Tech 08:00: The proposals we're concerned about — SB 1047, strict developer liability for downstream misuse, AI as an automatic aggravating factor in criminal law 14:00: The Little Tech lens — focusing on wrongdoing, not building, and why "paperwork favors the powerful" 18:00: The least-cost avoider principle and how it maps onto AI 23:00: Building a better regime — presumption of user liability for AI outputs, procedural safeguards, and well-designed safe harbors 31:00: Protecting good behavior — information sharing, incident reporting, and getting incentives right 32:00: Federal vs. state roles — the constitutional allocation as a guide to liability design Resources: Subscribe to the a16z AI Policy Brief: https://a16zpolicy.substack.com/ Follow Matt Perault: https://x.com/MattPerault Follow Jai Ramaswamy: https://www.linkedin.com/in/jai-ramaswamy-85a77675/ Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit a16zpolicy.substack.com

    36 min
  4. Inside Little Tech

    May 12

    Inside Little Tech

    Andrew Chen spends his time with the founders policymakers almost never hear from: two-and three-person teams, often before incorporation when a company is still a project. As general partner on a16z speedrun, he works at the earliest edge of Little Tech, backing founders at day one and helping them turn ambition into an actual business. In this conversation, Andrew joins Matt Perault to talk about what life looks like for small teams working at kitchen tables, operating on short runways, and simultaneously trying to build, find customers, and survive in competitive markets. They also discuss why so many startups are effectively absent from the policy process. The conversation widens to the question of what makes startup ecosystems work in the first place. Andrew shares lessons from building the Tech Week ecosystem, including what local markets need to foster entrepreneurship and why supporting innovation is ultimately a choice. Topics covered: 00:00: Intro 00:39: What is a16z speedrun? 02:08: The average profile of an early stage company 06:15: Why a16z built speedrun 08:36: A day in the life of a speedrun founder 13:22: What happens when startups do not work out 17:41: The cumulative burden of regulation for startups 21:49: Why Little Tech is absent from policy debates 25:05: How policy shapes where startups build 27:46: What makes startup ecosystems work 29:55: The idea behind Tech Week 32:52: How Tech Week surfaces future founders 33:23: Policy’s presence at Tech Week 34:38: Why policymakers should engage with Little Tech Resources: Subscribe to the a16z AI Policy Brief: https://a16zpolicy.substack.com/ Follow Matt Perault: https://x.com/MattPerault Follow Andrew Chen: https://x.com/andrewchen Learn more about a16z speedrun: https://speedrun.a16z.com/ Check out Tech Week event calendars: https://www.tech-week.com/calendar Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit a16zpolicy.substack.com

    40 min
  5. Catching Up on the Current Moment in AI Policy

    Apr 21

    Catching Up on the Current Moment in AI Policy

    In this conversation, Matt Perault, head of AI policy, and Collin McCune, head of government affairs, take stock of the current AI policy moment. As AI policy moves beyond rhetoric and into a more consequential phase, Matt and Collin separate signal from noise. They unpack where momentum is building in Washington, how state activity continues to drive the policy environment, and what it all means for Little Tech. Along the way, they dig into some of the most active debates including proposals focused on protecting kids, workforce disruption, data centers, benchmarking and licensing regimes, and the evolving balance between federal and state action. Enjoy. Topics covered: 01:14: The current AI policy moment 03:45: The White House National AI Framework: what’s new and what’s next 11:49: Kids, AI access, and the case against bans 17:49: Data centers, communities, and energy policy 19:56: Workforce disruption, retraining, and labor policy 25:32: Copyright, censorship, and other key debates 26:55: The Democrat perspective and response 32:27: Benchmarking, testing, and startup access 33:23: Licensing regimes and regulatory capture risks 38:16: What’s next in Congress? 44:00: States at the center of AI policymaking 48:22: Preemption, federalism, and the state-federal divide 55:27: Dormant Commerce Clause implications 58:59: Why Little Tech needs to stay engaged now Resources: Subscribe to the a16z AI Policy Brief: https://a16zpolicy.substack.com/ Follow Matt Perault: https://x.com/MattPerault Follow Collin McCune: https://x.com/Collin_McCune Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit a16zpolicy.substack.com

    57 min
  6. Open Models, Measurable Safeguards

    Apr 16

    Open Models, Measurable Safeguards

    Black Forest Labs has established itself as a pioneer in visual intelligence, with its open-weight FLUX models reaching over 50 million downloads on Hugging Face and rivaling models from Google, OpenAI, and DeepSeek in developer adoption. The company has distinguished itself not only through technical capability, but through a strong commitment to open research. In this conversation, Black Forest Labs’ Adam Chen and Ben Brooks, who lead the company’s legal and policy work, join Matt Perault to discuss what it means to build frontier visual AI openly. They explain the role of open models in advancing transparency, driving down the cost of innovation for developers, and strengthening security and sovereignty by reducing the world’s reliance on a handful of closed APIs. They also outline the unique policy challenges facing open-weight model developers. For policymakers, their message is clear: supporting open innovation does not require abandoning oversight. It requires targeted rules, analysis of where harms arise, and a better understanding of how proposed regulations land on smaller frontier labs, not just the largest incumbents. The conversation also offers a window into what it looks like to build a policy function at a startup. Adam and Ben offer a candid view into how they enable their small team to have outsized impact, rather than trying to match Big Tech’s playbook. Topics covered: 00:48: Intro 01:57: What is Black Forest Labs? 03:13: The makeup of a legal team at a frontier AI startup 07:14: The role of visual intelligence in the AI ecosystem 09:49: Core risks and baseline safeguards for visual models 10:34: Unique policy challenges of open-weight models 12:25: Restricting access to general-purpose technology should be a last resort 15:52: What’s at stake: open models as soft power and the China dynamic 20:07: BFL’s approach to being open and responsible 22:26: BFL’s model testing results 24:59: How a four-person legal team approaches disclosure and compliance 28:32: What works and what doesn’t in transparency proposals 31:07: Navigating the state, federal, and international patchwork as a startup 33:47: BFL’s advocacy goals 37:13: The Little Tech voice as a competitive advantage in the policy ecosystem This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit a16zpolicy.substack.com

    41 min
  7. Early Signals on AI, Hiring, and the Workforce

    Mar 31

    Early Signals on AI, Hiring, and the Workforce

    How is AI changing work? In this episode, Matt Perault sat down with Nick Catino, global head of policy at Deel, to better understand what today’s data can already tell us. Through its HR and payroll platform, Deel works with 35,000 customers and 1.5 million workers across more than 150 countries, giving the company a broad view across employers, geographies, and job categories as AI begins to change hiring and work. Nick walks through what Deel is seeing firsthand. That includes a 40% increase in the share of companies opening new AI roles in 2025. Deel’s recent global hiring report also found more than 70,000 AI trainer roles across 600-plus organizations, with nearly 60% of those roles located in the U.S., and AI trainer positions emerging as the fastest-growing global role on Deel’s platform. The conversation also explores what these shifts mean for policy. If AI is going to change how people work, Nick argues smart policy should focus on helping workers build AI fluency and new skills, supporting students as they prepare to enter the workforce, and giving startups the clarity they need as they hire and scale. Nick brings a valuable Little Tech perspective, drawing on his experience building public policy functions at fast-growing startups. For founders thinking about why startups need a seat at the table, along with when and how to engage with policymakers, this conversation is especially worthwhile. Topics covered: 03:14: Deel’s global hiring view 04:27: Building a startup policy function 09:12: Data as a policy tool 12:20: Early signals on AI and the workforce 14:47: Job shifts and emerging roles 17:30: Policy levers to support workers 24:22: Why regulatory certainty matters for Little Tech 27:01: Scaling Deel’s data insights 29:20: The rise of AI trainer roles 31:36: Lessons from building policy functions at fast-growing startups 35:05: Why policymakers want to hear from Little Tech Resources: Read Deel's global hiring report: https://www.deel.com/global-hiring-report-2026/ Learn more about Deel's HR and payroll platform: https://www.deel.com/partners/a16z.ecosystem?utm_source=podcast&utm_medium=partner-sourced&utm_content=a16z.ecosystem&utm_place=organic-community Subscribe to the a16z AI Policy Brief: https://a16zpolicy.substack.com/ Follow Matt Perault: https://x.com/MattPerault Follow Nick Catino: https://x.com/CatinoNick Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit a16zpolicy.substack.com

    37 min
  8. Cyber Resilience in an AI World

    Mar 24

    Cyber Resilience in an AI World

    The cybersecurity landscape is moving to an AI-vs-AI world where both attackers and defenders can operate at machine speed. In this conversation, Anne Neuberger and Sam Jones join Jai Ramaswamy to go deeper on what this shift looks like in practice. Neuberger draws on nearly two decades in government—including serving as deputy national security advisor for cyber and emerging technology—to explain how AI is transforming the threat landscape, most notably making attacks faster, cheaper, and continuous at scale. Jones brings the builder’s perspective as CEO and cofounder of Method Security, where his team is building autonomous cyber systems for both offense and defense observing firsthand how AI is accelerating everything from routine tactics to exploit development. Together, they discuss what “cyber resilience” means in an AI world: continuous testing and red-teaming that was previously cost-prohibitive, clearer benchmarks for critical infrastructure, and faster recovery when disruptions happen. They also walk through the policy measures that can help defenders keep pace. Topics covered: 03:16: How AI changes the threat landscape 07:38: Net new risks in an AI-vs-AI cyber world 11:21: Building trust to deploy new technology in no-fail systems13:55: Cybercrime at machine speed 17:18: Who benefits more from AI: attackers or defenders?1 9:29: Tactics to remove friction for defenders 22:26: Real examples of incidents where AI could have changed outcomes: Colonial Pipeline and Change Healthcare 27:18: What cyber resilience means in an AI world30:57: Measuring resilience 36:59: Information sharing and antitrust: lessons from financial services and telecom compromises 44:59: The builder’s view: what Method Security is building for offense + defense 49:27: Little Tech realities of building with a small team and selling into government 52:53: The role of procurement in ensuring defensive systems keep pace with adversaries 55:32: What’s next: in-year buying flexibility and closing thoughts Resources: Subscribe to the a16z AI Policy Brief: https://a16zpolicy.substack.com/ Follow Jai Ramaswamy: https://www.linkedin.com/in/jai-ramaswamy-85a77675/ Follow Anne Neuberger: https://www.linkedin.com/in/anne-neuberger-13b4491b/ Follow Sam Jones: @___sjones Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit a16zpolicy.substack.com

    56 min
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About

Your guide to AI public policy from the team at a16z. Each conversation bridges Washington and Little Tech, bringing together policy leaders, researchers, and builders to explore how the U.S. stays ahead in AI. a16zpolicy.substack.com

Information

  • Creator
    a16z Policy
  • Years Active
    2025 - 2026
  • Episodes
    17
  • Rating
    Clean
  • Copyright
    © a16z
  • Show Website
    a16z AI Policy Brief

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