Hot Take: The US Government Banned Fable. SpaceX Bought Cursor. What’s Going On?

Hot Take: The US Government Banned Fable. SpaceX Bought Cursor. What’s Going On?

In a matter of days, the U.S. government blocked access to Anthropic’s advanced Mythos and Fable models, while SpaceX surpassed a $2 trillion valuation and announced its $60 billion acquisition of Cursor, one of the fastest-growing AI software companies in the world. These events may appear unrelated, but together they point to a fundamental shift in the AI landscape. Advanced AI is no longer just a commercial technology. It is increasingly being treated as strategic infrastructure, with implications for national security, global competitiveness, regulation, and capital allocation. In this episode, Nilanjana Bhowmik sits down with James Falkoff to unpack the controversy surrounding Anthropic’s restricted models, the cybersecurity concerns that triggered government intervention, and the broader debate around sovereign AI. They discuss whether frontier AI systems can realistically be controlled, what this means for countries dependent on foreign AI providers, and why governments around the world are paying close attention. The conversation then turns to SpaceX’s rapidly expanding AI ambitions. Beyond Grok, SpaceX is building a vertically integrated AI business that spans large-scale compute infrastructure, data center operations, and now Cursor’s rapidly growing developer platform. James explains why the Cursor acquisition could significantly strengthen SpaceX’s position in AI and how the company is pursuing a long-term strategy centered on infrastructure, energy, and lower-cost AI deployment. Inside the episode: • Why the U.S. government blocked Anthropic’s Mythos and Fable models • Whether the reported jailbreak justified government intervention • The debate over AI safety, cybersecurity, and frontier model access • Why many cybersecurity experts opposed the decision • The emergence of sovereign AI as a strategic national priority • SpaceX’s $60 billion acquisition of Cursor and what it means for the company’s AI strategy • How Cursor’s developer ecosystem could strengthen Grok and future SpaceX AI models • The economics of AI infrastructure, data centers, and compute • SpaceX’s vision for vertically integrated AI • The long-term implications for technology companies, governments, and global markets Watch Full Episode on YouTube About James Falkoff: James has over 16 years of experience investing in technology across public and private markets, including more than a decade in venture capital. He has led over 25 early-stage investments and is known for his thought leadership, strong exit track record, and hands-on work with portfolio companies to drive growth. Before joining Converge, he was a Principal at Longworth Venture Partners, where he partnered with Nilanjana Bhowmik to identify high-potential sectors and secure early access to top startups. His portfolio includes companies like Olapic (acquired by Monotype), RapidMiner (Altair), JIBE (iCIMS), and TrackVia (Primus Capital). Connect with James Falkoff:https://www.linkedin.com/in/jamesfalkoff/ [https://www.linkedin.com/in/jamesfalkoff/] Connect with Nilanjana Bhowmik:https://www.linkedin.com/in/nilanjanabhowmik/ [https://www.linkedin.com/in/nilanjanabhowmik/] Converge VC Website: https://converge.vc/ [https://converge.vc/] This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit postmoneypodcast.substack.com [https://postmoneypodcast.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

Everyone Is Building AI Agents. Smart Investors Are Building This Instead

Venture capital spent the last twenty years chasing software. Now some of Silicon Valley’s most experienced investors believe the next generation of trillion-dollar companies will be built in the physical world. In this episode of the Post Money Podcast, Bain Capital Ventures Partner Ajay Agarwal explains why AI is moving beyond chatbots and software into factories, warehouses, construction sites, logistics networks, and robotics systems that interact with the real world. Having backed robotics before it was fashionable, including Bain Capital Ventures' investment in Kiva Systems long before it became Amazon Robotics, Ajay explains why investors walked away from the category for nearly two decades, what has reignited interest today, and why the next wave of AI winners may emerge from the physical world rather than software. We discuss how AI is transforming manufacturing, construction, logistics, and consumer robotics, why proprietary real-world data may become the most valuable asset in AI, and how a new generation of founders is building companies far beyond the traditional software playbook. Finally, Agay shares his views on AI regulation, public anxiety around job displacement, and why healthcare, life sciences, and education may be among the most transformative AI opportunities still ahead. Inside This Episode * Why Bain Capital Ventures believes Physical AI could become a multi-trillion-dollar opportunity * The untold story of Kiva Systems and how Amazon Robotics was built * Why venture capital avoided robotics for nearly twenty years * The rise of the Industrial Renaissance and the return of hardware investing * How AI is transforming construction, manufacturing, logistics, and warehousing * Why proprietary real-world data may be more valuable than foundation models * The future of humanoid robots and consumer robotics * Why software incumbents must embrace AI or risk becoming irrelevant * The cultural challenges facing large software companies in the AI era * How founders should think about AI disruption inside existing products * Why healthcare, life sciences, and education may be the next major AI frontiers * The debate around AI regulation, innovation, and public trust Watch Full Episode on YouTube About Ajay Agarwal Ajay Agarwal is a Partner at Bain Capital Ventures, where he has spent more than two decades investing in category-defining technology companies. He invests across AI, enterprise software, robotics, logistics, industrial technology, and the emerging Physical AI landscape. Ajay led Bain Capital Ventures’ investment in Kiva Systems, the pioneering warehouse robotics company that was acquired by Amazon and became the foundation of Amazon Robotics. He has also backed companies including ShipBob, Vention, Gather AI, TerraFirma, and several next-generation robotics and automation businesses. Before venture capital, Ajay was an entrepreneur and operator, co-founding an enterprise software company while studying at Stanford University. About the Host Nilanjana Bhowmik is a General Partner at Converge and host of the Post Money Podcast, where she speaks with founders, investors, and industry leaders shaping the future of technology, innovation, and venture capital. Through in-depth conversations, Post Money explores the ideas, decisions, and trends driving the next generation of transformative companies. Connect with Ajay Agarwal: https://www.linkedin.com/in/ajay1agarwal [https://www.linkedin.com/in/ajay1agarwal] Connect with Nilanjana Bhowmik: linkedin.com/in/nilanjanabhowmik [https://www.linkedin.com/in/nilanjanabhowmik] Converge VC website: converge.vc [https://converge.vc/] This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit postmoneypodcast.substack.com [https://postmoneypodcast.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

She Started a VC Fund at 25, Here's What $500M Later Looks Like | Lu Zhang

When someone told me, “You have to invite Lu Zhang on the show because she’s fearless,” I was intrigued. That single word ended up shaping much of this conversation. Lu started investing in AI long before AI became the hottest topic in venture capital. She launched Fusion Fund when most people thought she was too young to be a venture capitalist, built the firm from less than $20 million to more than $500 million in assets under management, and spent the last decade backing founders across AI, healthcare, and industrial automation while much of Silicon Valley was focused elsewhere. In this episode, we explore what it actually means to have conviction before the rest of the market catches up. Lu shares how she evaluates market timing, why being too early can be just as dangerous as being too late, and how Fusion Fund built a unique advantage through deep networks of founders, researchers, CTOs, and industry leaders. We discuss why AI healthcare may finally be reaching a true inflection point, how major enterprises are accelerating AI adoption, and why the next generation of AI winners may look very different from what most investors expect. Inside the episode: * Why Lu Zhang started a venture fund when most people thought she was too young to be a VC * How Fusion Fund grew from less than $20 million to more than $500 million under management * The three sectors Fusion Fund has focused on for more than a decade * Why access to information has become a competitive advantage in venture capital * The turning point that is making AI healthcare finally take off * Why healthcare may become one of the biggest AI opportunities of the decade * The rise of vertical AI models in healthcare, finance, and insurance * The biggest opportunities in AI infrastructure, governance, and data management * What Lu looks for when evaluating AI founders Watch Full Episode on YouTube: About Lu Zhang Lu Zhang is the Founder and Managing Partner of Fusion Fund, a Silicon Valley venture capital firm focused on AI, healthcare, enterprise technology, and industrial automation. A Stanford-trained engineer, former entrepreneur, and investor, Lu is known for backing deep technology companies at the intersection of innovation and real-world commercialization. Originally from Inner Mongolia, Lu founded Fusion Fund in 2015 after building companies and conducting research in materials science. Since then, she has grown the firm into one of the leading early-stage investors in AI and frontier technologies. Her work has earned recognition from the World Economic Forum, Forbes, Business Insider, and Silicon Valley Women of Influence. Beyond investing, Lu is a frequent speaker at global conferences including Davos, Web Summit, and SuperReturn, serves on the boards of several technology and healthcare organizations, and is a guest lecturer at Stanford University. She holds an M.S. in Materials Science and Engineering from Stanford. Connect with Lu Zhang: https://www.linkedin.com/in/luzhangvc [https://www.linkedin.com/in/luzhangvc] Connect with Nilanjana Bhowmik: linkedin.com/in/nilanjanabhowmik [https://www.linkedin.com/in/nilanjanabhowmik] Converge VC website: converge.vc [https://converge.vc/] This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit postmoneypodcast.substack.com [https://postmoneypodcast.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

The Startup Exit Math Every Founder Should Know | Peter Walker, Head of Insights at Carta

Founders are constantly told to “think bigger,” raise more capital, and chase billion-dollar outcomes. But behind the headlines about AI unicorns and explosive growth lies a much harsher reality: most startups never IPO, most founders end up heavily diluted, and even successful venture-backed companies can take a decade or more to reach an outcome. In this episode of the Post Money Podcast, Nilanjana Bhowmik sits down with Peter Walker, Head of Insights at Carta, to unpack the actual numbers behind startup fundraising, dilution, exits, secondary sales, and the modern venture market. Drawing from data across tens of thousands of startups on Carta, Peter explains why AI companies are pulling away from traditional SaaS businesses, why many founders dramatically underestimate how long startup journeys really take, and why valuation alone often means far less than founders think. The conversation explores how venture capital has become increasingly concentrated around a tiny group of AI companies, why secondaries only benefit a very small slice of startups, and how most venture-backed exits still happen through acquisitions rather than IPOs. Inside the episode: * The real fundraising benchmarks founders need to hit in 2026 * Why “zero to $100M ARR” is distorting startup expectations * The reality behind startup valuations and dilution * The brutal math of venture capital ownership over time * Why down rounds are far more common than founders think * Why profitability no longer guarantees a successful exit * The truth about unicorns, secondary sales, and liquidity * Why most startups will never IPO * How raising too much capital can reduce exit opportunities * What founders should understand before taking venture capital at all Watch Full Episode on YouTube: About Peter Walker: Peter Walker leads the Insights team at Carta, where he analyzes one of the largest private startup datasets in the world to uncover trends shaping venture capital, fundraising, startup valuations, dilution, secondaries, exits, and the broader technology ecosystem. Over the past several years, Peter has become one of the most widely followed voices in venture capital data and startup market analysis. His research and visualizations are regularly referenced by founders, investors, operators, and financial media seeking a clearer understanding of how private markets actually function beneath the headlines. Before leading Insights at Carta, Peter worked across startup operations, venture analysis, and research roles focused on technology companies and private market ecosystems. Connect with Peter Walker: https://www.linkedin.com/in/peterjameswalker/ [https://www.linkedin.com/in/peterjameswalker/] Connect with Nilanjana Bhowmik: linkedin.com/in/nilanjanabhowmik [https://www.linkedin.com/in/nilanjanabhowmik] Converge VC website: converge.vc [https://converge.vc/] This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit postmoneypodcast.substack.com [https://postmoneypodcast.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

Investing in Civilization Scale problems at Lightspeed | Raviraj Jain

Inside top venture firms, investors are now funding frontier AI research labs before products exist, before revenue exists, and sometimes before there is even a clear path to monetization. The bet is no longer just on software companies, it’s on entirely new forms of intelligence. In this episode of the Post Money Podcast, Raviraj Jain from Lightspeed Venture Partners explains why some of Silicon Valley’s biggest capital pools are shifting toward self-learning systems, humanoid robotics, fusion energy, and AI infrastructure that could redefine how humans work, manufacture, discover new technologies, and generate power over the next decade. Raviraj breaks down why many investors now believe the next leap in AI will happen outside the digital world. Not in chat interfaces or productivity tools, but in machines that can operate in physical environments, understand motion, adapt to unfamiliar situations, and interact with the real world autonomously. He explains why robotics foundation models, reinforcement learning, and multimodal systems are advancing faster than most people realize, and why humanoid robots may arrive much sooner than the public expects. The conversation also gets into the hidden constraints behind the AI boom itself. As data centers become one of the fastest-growing consumers of global energy, technologies once considered unrealistic, including nuclear fusion, are suddenly becoming serious venture-backed bets again. The real question is no longer whether AI will change industries. It’s who will move fast enough to rebuild them before someone else does. Inside the episode: * Why venture firms are now funding pure AI research labs before monetization exists * The case for self-learning AI systems over human-trained models * Why humanoid robots may arrive faster than most people expect * The biggest bottleneck facing AI over the next decade: energy * Why nuclear fusion is suddenly investable again after decades of skepticism * The shift from consumer AI tools to enterprise-wide AI adoption * What early-stage investors now look for in founders during the AI era * Why domain expertise may soon outperform technical expertise again * How AI could completely reshape venture capital workflows and decision-making Watch Full Episode On YouTube About Raviraj Jain: Raviraj Jain is a Partner at Lightspeed Venture Partners, where he focuses on enterprise software, AI, cloud infrastructure, machine intelligence, and frontier technologies. Before joining Lightspeed in 2017, he worked across startups and large technology companies in both the US and India, including roles in product and strategy at LinkedIn and Fundbox. Having worked as an entrepreneur, operator, and investor, Raviraj brings a highly product-focused lens to early-stage investing. Raviraj holds an MBA from Harvard Business School and an engineering degree from IIT Bombay. Connect with Raviraj Jain: https://www.linkedin.com/in/ravirajjain/ [https://www.linkedin.com/in/ravirajjain/] Connect with Nilanjana Bhowmik: linkedin.com/in/nilanjanabhowmik [https://www.linkedin.com/in/nilanjanabhowmik] Converge VC website: converge.vc [https://converge.vc/] This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit postmoneypodcast.substack.com [https://postmoneypodcast.substack.com?utm_medium=podcast&utm_campaign=CTA_1]