In this episode, a16z GP Martin Casado sits down with Sherwin Wu, Head of Engineering for the OpenAI Platform, to break down how OpenAI organizes its platform across models, pricing, and infrastructure, and how it is shifting from a single general-purpose model to a portfolio of specialized systems, custom fine-tuning options, and node-based agent workflows.

They get into why developers tend to stick with a trusted model family, what builds that trust, and why the industry moved past the idea of one model that can do everything. Sherwin also explains the evolution from prompt engineering to context design and how companies use OpenAI’s fine-tuning and RFT APIs to shape model behavior with their own data.

Highlights from the conversation include: 

• How OpenAI balances a horizontal API platform with vertical products like ChatGPT
• The evolution from Codex to the Composer model
• Why usage-based pricing works and where outcome-based pricing breaks
• What the Harmonic Labs and Rockset acquisitions added to OpenAI’s agent work
• Why the new agent builder is deterministic, node based, and not free roaming

Resources:

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Ben Horowitz reveals why the US already lost the AI culture war to China—and it wasn't the technology that failed. While Biden's team played Manhattan Project with closed models, Chinese developers quietly captured the open-source heartbeat of global AI through DeepSeek, now running inside every major US company and university lab. The kicker: Google and OpenAI employ so many Chinese nationals that keeping secrets was always a delusion, but the policy locked American innovation behind walls while handing cultural dominance to Beijing's weights—the encoded values that will shape how billions of devices interpret everything from Tiananmen Square to free speech.

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Marc Andreessen and Ben Horowitz sit down with Margit Wennmachers—the woman who turned two unknown entrepreneurs with $300 million and zero investing track record into the most talked-about firm in venture capital. She unpacks how they weaponized transparency in an industry built on secrecy, why Fortune's cover story triggered a cartel meltdown, and the exact moment a casual lunch conversation became "Software Is Eating the World." This is the origin story of how A16Z broke every unwritten rule, made enemies of every top-tier firm, and permanently rewired what it means to build companies in public.

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Half a billion people can access the world’s best AI on their phone. So why are most using it to write emails while only some are using it to build empires?

In this conversation with Mark Halperin from Next Up, Marc Andreessen reveals why small bakeries are beating Fortune 500 companies at AI adoption, how to turn ChatGPT into your personal board of directors, and why Silicon Valley just reversed five years of geographic dispersion overnight. He also shares the questions that unlock AI's real power—including one of his favorite prompts: "What questions should I be asking?"

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Epoch AI researchers reveal why Anthropic might beat everyone to the first gigawatt datacenter, why AI could solve the Riemann hypothesis in 5 years, and what 30% GDP growth actually looks like. They explain why "energy bottlenecks" are just companies complaining about paying 2x for power instead of getting it cheap, why 10% of current jobs will vanish this decade, and the most data-driven take on whether we're racing toward superintelligence or headed for history's biggest bubble.

Resources:

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Vlad Tenev built Robinhood by breaking every rule Wall Street wrote: zero commissions when competitors charged $10, mobile-first when "serious" investors demanded desktop, a brand that made finance feel like rebellion instead of a club you'd never join.

By 2021 they'd forced every major brokerage to slash fees and attracted millions who'd never owned a stock, but then GameStop happened: trading restrictions during the meme stock frenzy triggered congressional hearings, user fury, and a two-year brand crisis that nearly buried them despite the real culprit being antiquated clearing mechanics no one understood. 

Now Tenev's pushing an even more radical vision—tokenizing private company shares so retail investors can own stakes in AI giants before IPO, turning prediction markets into "truth machines" that beat polls and pundits, and building what he calls the end of financial nihilism: a platform where your seventy-year-old parents and your Gen Z cousin both manage everything from retirement accounts to election bets in one place.

The question isn't whether traditional finance survives this; it's whether Robinhood can move fast enough to own the entire wealth transfer before someone else does.

Timestamps:

0:00 - Introduction
3:52 - Financial Relationships vs. Pinterest Boards: The Higher Bar
5:27 - Building in a Regulatory Catch-22
7:53 - Three Simultaneous Contrarian Bets
12:15 - From Institutional HFT to Retail Revolution
17:40 - January 28th: The Day Trust Died
27:40 - “Simple Lie More Powerful Than Complicated Truth”
30:02 - Tokenization: The Antidote to T+1 Settlement
32:52 - IPO Access: From Asking For Favors to Everyone Wanting In
39:22 - “Series D Was Called an IPO”
43:06 - WTF Happened in 1971?
47:42 - Going Broad While Going Deep
53:26 - The $120 Trillion Wealth Transfer
58:16 - Debunking “Financial Nihilism”
58:40 - “Speculation Is Critical For Functioning Markets”

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The former bank regulator who invented deposit networks just revealed why SVB's collapse was inevitable—and why the solution that could have saved them is finally being rebuilt. 

Gene Ludwig ran the OCC during the Clinton administration, created a half-trillion-dollar market solving a problem his Aunt Betty faced riding buses between banks, then watched his invention fail to save Silicon Valley Bank because the technology, economics, and incentives were fundamentally broken. 

Now he's partnered with Paolo and ModernFi to build what could become America's eighth systemically important financial utility: a bank-owned consortium that's signing 25 institutions per week and racing to protect the 4.8 trillion in uninsured deposits that make the next crisis inevitable.

Resources:

Follow Gene on LinkedIn: https://www.linkedin.com/in/gene-ludwig/

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Palmer Luckey got fired from Meta for backing the wrong candidate—now he's the hero saving American defense, and that shift tells you everything about how fast the ground moved beneath Silicon Valley's feet. For decades, tech and defense were allies, then came 15 years of hostility so visceral that Google employees revolted over a Pentagon AI contract, and when leadership caved, only three people showed up to hear what border security actually involves. But something broke: COVID exposed our inability to make things, Ukraine revealed wars now iterate in days not decades, and suddenly the Harvard dorm room generation realized the people building satellites and drones weren't just necessary—they were the future, while legacy defense contractors still operate on Soviet-style five-year plans that guarantee cost overruns and obsolescence. Now the question isn't whether Silicon Valley returns to its Cold War roots, but whether America wins by becoming more like China's centralized system or doubles down on the chaotic creativity that built nine of the world's ten most valuable companies in 25 years—and the founders flooding into defense, energy, mining, and manufacturing suggest the second American century is just getting started.

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Emmett Shear, founder of Twitch and former OpenAI interim CEO, challenges the fundamental assumptions driving AGI development. In this conversation with Erik Torenberg and Séb Krier, Shear argues that the entire "control and steering" paradigm for AI alignment is fatally flawed. Instead, he proposes "organic alignment" - teaching AI systems to genuinely care about humans the way we naturally do. The discussion explores why treating AGI as a tool rather than a potential being could be catastrophic, how current chatbots act as "narcissistic mirrors," and why the only sustainable path forward is creating AI that can say no to harmful requests. Shear shares his technical approach through multi-agent simulations at his new company Softmax, and offers a surprisingly hopeful vision of humans and AI as collaborative teammates - if we can get the alignment right.

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Two venture capitalists dissect why biotech burns billions while China runs trials in weeks—and why the next Genentech won't look anything like the last one. Elliot Hershberg reveals the "three horsemen" strangling drug development as costs explode to $2.5 billion per approval, while Lada Nuzhna exposes how investigator-initiated trials in Shanghai are rewriting the competitive playbook faster than American founders can file INDs. When the infrastructure that built monoclonal antibodies becomes the commodity threatening to hollow out an entire industry, the only path forward demands inventing medicines that are literally impossible to make without tools that don't exist yet—and they're betting everything on which approach survives.

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