The a16z Show

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.

Resources:

Follow Ryan McEntush on X: https://x.com/rmcentush

Follow Erin Price-Wright on X: https://x.com/espricewright

Follow Zabie Elmgren on X: https://x.com/zabie_e

Follow Will Bitsky on X: https://x.com/willbitsky

Read more all of our 2026 Big Ideas

Part 1: https://a16z.com/newsletter/big-ideas-2026-part-1

Part 2: https://a16z.com/newsletter/big-ideas-2026-part-2/

Part 3: https://a16z.com/newsletter/big-ideas-2026-part-3/

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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.

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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.

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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.

Resources:

Follow Olivia Moore on X: https://x.com/omooretweets

Follow Bryan Kim on X: https://x.com/kirbyman01

Follow Julie Yoo on X: https://x.com/julesyoo

Read more all of our 2026 Big Ideas

Part 1: https://a16z.com/newsletter/big-ideas-2026-part-1

Part 2: https://a16z.com/newsletter/big-ideas-2026-part-2/

Part 3: https://a16z.com/newsletter/big-ideas-2026-part-3/

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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.

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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.

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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.

Resources:

Follow Angela Strange on X: https://x.com/astrange

Follow David Haber on X: https://x.com/dhaber

Follow Alex Immerman on X: https://x.com/aleximm

Follow Seema Amble on X: https://x.com/seema_amble

Read more all of our 2026 Big Ideas

Part 1: https://a16z.com/newsletter/big-ideas-2026-part-1

Part 2: https://a16z.com/newsletter/big-ideas-2026-part-2/

Part 3: https://a16z.com/newsletter/big-ideas-2026-part-3/

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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.

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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.

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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.

Resources:

Follow Marc Andrusko on X: https://x.com/mandrusko1

Follow Stephanie Zhang on X: https://x.com/steph_zhang  

Follow Sarah Wang on X: https://x.com/sarahdingwang

Read more all of our 2026 Big Ideas

Part 1: https://a16z.com/newsletter/big-ideas-2026-part-1

Part 2: https://a16z.com/newsletter/big-ideas-2026-part-2/

Part 3: https://a16z.com/newsletter/big-ideas-2026-part-3/

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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.

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 http://a16z.com/disclosures.

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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.

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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.

Resources:

Find Zach on X: https://x.com/zachperret

Find David on X: https://x.com/dhaber

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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 http://a16z.com/disclosures

.

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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.

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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.

Resources:

Follow Harry Stebbings on X: https://twitter.com/HarryStebbings

Follow David George on X: https://twitter.com/DavidGeorge83

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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](http://a16z.com/disclosures.

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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.

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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. 

Timecodes: 

0:00 — Introduction and the Cost of Crime

1:09 — Technology, Privacy, and Trust in Policing

1:22 — Eliminating Crime: A National Strategy

2:54 — People: Staffing, Culture, and Recruitment

8:45 — Products: Technology in Modern Policing

9:41 — Policy: Accountability and Prosecution

20:11 — Community Policing and Clearance Rates

25:16 — Case Study: Las Vegas and Public-Private Partnerships

32:00 — Criticisms, Privacy, and Trust

35:23 — Economic Mobility, Safety, and Social Impact

36:44 — Reform, Recidivism, and Alternative Approaches

52:14 — Organized Crime and Policy Challenges

54:32 — The Future of Policing: Intelligence and Precision

57:24 — Success Stories and Conclusion

Resources: 

Follow Garrett on X: https://twitter.com/glangley 

Follow Ben on X: https://twitter.com/bhorowitz 

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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.

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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.

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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.

Timecodes:

00:01:45 - Design Becomes Approachable to Everyone

00:02:36 - From Years to Minutes: Product Feedback Loops Collapse

00:07:54 - "Each role used their own tool...their own lingo"

00:13:15 - "If you don't have an opinion, you’ll get AI slop"

00:17:18 - The Lost Art of Being a Complete Builder

00:21:42 - Design Is Not About Aesthetics

00:28:57 - User-Centric vs System-Centric Philosophy

00:34:00 - AI as Universal Interface, Not Chat Box

00:38:42 - "Simplicity is the Biggest Constraint"

00:43:42 - "I Don't Sit in Figma All Day Making Mocks"

00:46:33 - RyoOS: Building A Personal Operating System

00:48:45 - "We've been doing the same thing since 1984"

Resources:

Follow Ryo Lu on X: https://x.com/ryolu_

Follow Jennifer Li on X: https://x.com/JenniferHli

Follow Erik Torenberg on X: https://x.com/eriktorenberg

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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.

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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.

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AI models feel smarter than their real-world impact. They ace benchmarks, yet still struggle with reliability, strange bugs, and shallow generalization. Why is there such a gap between what they can do on paper and in practice

In this episode from The Dwarkesh Podcast, Dwarkesh talks with Ilya Sutskever, cofounder of SSI and former OpenAI chief scientist, about what is actually blocking progress toward AGI. They explore why RL and pretraining scale so differently, why models outperform on evals but underperform in real use, and why human style generalization remains far ahead.

Ilya also discusses value functions, emotions as a built-in reward system, the limits of pretraining, continual learning, superintelligence, and what an AI driven economy could look like.

Resources:

Transcript: https://www.dwarkesh.com/p/ilya-sutsk...

Apple Podcasts: https://podcasts.apple.com/us/podcast...

Spotify: https://open.spotify.com/episode/7naO...

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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](http://a16z.com/disclosures.

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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.

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AI is reshaping the tech landscape, but a big question remains: is this just another platform shift, or something closer to electricity or computing in scale and impact? Some industries may be transformed. Others may barely feel it. Tech giants are racing to reorient their strategies, yet most people still struggle to find an everyday use case. That tension tells us something important about where we actually are.

In this episode, technology analyst and former a16z partner Benedict Evans joins General Partner Erik Torenberg to break down what is real, what is hype, and how much history can guide us. They explore bottlenecks in compute, the surprising products that still do not exist, and how companies like Google, Meta, Apple, Amazon, and OpenAI are positioning themselves.

Finally, they look ahead at what would need to happen for AI to one day be considered even more transformative than the internet.

Timestamps: 

0:00 – Introduction 
0:17 – Defining AI and Platform Shifts
1:50 – Patterns in Technology Adoption
6:04 – AI: Hype, Bubbles, and Uncertainty
13:25 – Winners, Losers, and Industry Impact
19:00 – AI Adoption: Use Cases and Bottlenecks
24:00 – Comparisons to Past Tech Waves
32:00 – The Role of Products and Workflows
40:00 – Consumer vs. Enterprise AI
46:00 – Competitive Landscape: Tech Giants & Startups
51:00 – Open Questions & The Future of AI

Resources:

Follow Benedict on LinkedIn: https://www.linkedin.com/in/benedictevans/

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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 http://a16z.com/disclosures.

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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.

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