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In this episode of Other People's Money, host Max Wiethe interviews James Wang, General Partner at Creative Ventures and author of "What You Need to Know About AI." The conversation explores the current state of venture capital, from the collision between public and private markets to the challenges facing VCs in an environment where exits have largely dried up. (00:50) Wang discusses how venture capital has evolved from its hardware roots to software dominance and now faces new challenges with AI investments that behave more like capital-intensive hardware businesses than traditional software models.
James Wang is a General Partner at Creative Ventures, a deep tech venture capital firm founded in 2016 that focuses on hardware and industrial technologies. Before entering venture capital, Wang worked at Bridgewater Associates, bringing a macro-economic perspective to investment analysis. He recently authored "What You Need to Know About AI," published in 2025, which takes a balanced approach to understanding AI's capabilities and limitations without falling into extreme predictions of either technological utopia or doom.
Max Wiethe is the host of Other People's Money, a podcast focused on alternative investments and fund management. He brings expertise in analyzing various asset management strategies and has experience working with wealth managers and RIAs who are expanding into alternative investment classes like venture capital.
Wang argues that venture capital has fundamentally changed from its Silicon Valley roots in hardware and semiconductors to become indistinguishable from private equity in many cases. (04:03) As VC funds have grown larger due to institutional demand and low interest rates, they've been forced to deploy increasingly large checks into later-stage companies, essentially competing in the same market as private equity firms. This evolution has created confusion about what VC actually is and what role it should play in investor portfolios. The challenge is particularly acute because many software VCs are now trying to invest in AI companies that have economics more similar to hardware businesses - high startup costs and meaningful marginal costs - which breaks their traditional investment model.
According to Wang, the venture capital industry's claims about adding value to portfolio companies are largely overblown, especially for smaller VCs without established track records. (33:27) In accelerator communities like Y Combinator, it's considered a "punchline joke" that VCs add value. Wang suggests that for many hot deals, founders would prefer VCs who can communicate clearly and close quickly rather than those promising nebulous future value-add. The most successful differentiation often comes from celebrity status or brand recognition rather than operational expertise, which is why athlete and celebrity VCs like Saquon Barkley can access deals that traditional VCs might struggle to enter.
The venture capital market is experiencing a liquidity crisis due to excessive dry powder accumulated during the low-interest-rate environment. (50:46) Many companies that raised at high valuations cannot exit through IPOs or acquisitions at their previous marks, but continued capital infusions from VCs with dry powder allow them to avoid necessary markdowns. This creates a cycle where companies don't face market reality, VCs maintain artificially high marks, and the entire ecosystem becomes disconnected from fundamental value. Wang compares this to Japan's prolonged economic stagnation, noting that without forced transactions, markets may not clear for years.
Traditional performance metrics like TVPI and MOIC can be misleading when evaluating venture capital funds, especially those still in their investment cycle. (35:53) Wang emphasizes that exits are what truly matter, but most VC funds won't show their real performance until 7-10 years into their lifecycle. He's seen funds completely flip in performance rankings when supposed winners fail and supposed losers produce breakout companies. For LPs evaluating managers, Wang recommends focusing on process, team composition, and detailed case studies of how VCs have actually worked with portfolio companies, rather than relying on paper marks or multiples.
Wang cautions against focusing too heavily on first-order AI effects and encourages investors to consider how AI-native businesses might emerge. (59:51) Drawing parallels to the internet boom, he notes that while newspapers initially thought global reach would help them, the real winners were internet-native companies like Google and Facebook that captured the advertising market. Similarly, while existing businesses may become more productive with AI, the biggest opportunities may come from entirely new AI-native business models. Wang particularly highlights the translation industry as an example, where basic translation jobs are disappearing while high-end translators using AI tools are seeing 10x increases in productivity.