Investment Insights and Trends

The long-standing divide between public and private markets is breaking down, as Wall Street confronts a new reality: the most meaningful growth and value creation now happen well before IPOs. This post examines how shrinking public markets, abundant private capital, and institutional shifts are redefining where and when investors capture returns.

Jensen Huang recently suggested that “AI is about to change everything.” Whatever changes AI may bring to investment management, the regulatory standards remain the same. Those familiar rules mean that AI’s new frontiers in financial advertising include pitfalls and traps for the unwary.

For as long as humans have been human, we have been investors — not in the financial sense, but in the way we allocate our time, attention, belief, and collective effort. Before capital markets existed, we poured resources into the experiences that mattered most: temples to sport and skill, theaters to story and song, forums to gather and debate, libraries to learn and preserve, gardens to restore and delight. These were not just cultural institutions. They were the earliest marketplaces of human experience. Across every culture and era, the same instincts have shaped human progress: the desire to move, to express, to belong, to grow, and to savor life. Technology evolves. Capital evolves. Human nature does not.

AI doesn’t just change interfaces — it rewrites cognition. The companies that embed into daily routines and earn behavioral lock-in will become the next category-defining platforms. This is our thesis on why experience ↔ behavior fit creates the modern moat.

In the world of venture capital, our reality is governed by a mathematical principle that defies the intuition of the broader financial markets: the Power Law. While traditional equity investors often cite the “80/20 rule,” venture capital operates on a far more extreme distribution, typically closer to 95/5.

If you opened Google, scrolled on Instagram, streamed a YouTube video or a Netflix show last night, or ordered lunch on DoorDash, you’ve touched the Stanford ecosystem. The world knows the legend of the “PayPal Mafia.” Early PayPal employees went on to found generational companies like Tesla, LinkedIn, YouTube, Yelp, and Palantir. But there’s a deeper pattern at work. The most prolific “mafia” in tech history didn’t emerge from a single company. It emerged from a single campus: Stanford University.

Why old VC signals fail for GenAI & agentic AI startups. Discover a new framework prioritizing user behavior, engagement & workflow adoption to scale AI ventures.

I love the optimism of early-stage investing. New ideas, fresh energy, big markets. But optimism without guardrails is how you end up explaining to your investors why a “can’t-miss” deal missed so completely. This isn’t about being cynical. It’s about being clear-eyed. Most great companies had plenty of hair on the deal. The question isn’t “are there red flags?” — there always are. The question is: When things go wrong — and they will — will this founder figure it out? Hold that thought.

Walking the halls of HLTH 2025, the paradox was unmistakable. AI has officially conquered healthcare — every booth, every headline, every whispered deal. Yet behind the glow of demos and jargon, one question echoed in every conversation: Can AI actually fix healthcare — or will the system let it? For founders, operators, and especially investors, that tension defines the decade ahead. We’re past the hype cycle. Now it’s about translating AI’s promise into health — tangible outcomes, durable business models, and investable returns.

Why Supply Chain Our 21st-century American lives — accustomed to a seemingly endless and instantaneously accessible consumerism — are powered by an often-forgotten, rarely disrupted mega-network of transportation and logistics. Only when our packages begin to show up late do we remember. Shaken from our bliss, we watched when the Ports of LA/Long Beach ground to a halt during COVID, the Suez Canal was blocked for six days in March 2021, and US shipping was brought to a standstill last October by once-in-a-generation dockworker strikes. All of these bring back the nightmare of a world where the things we need (or want) don’t show up, even when we select “Next Day” or “Priority Shipping.”

In 2022, U.S. companies posted nearly 68,600 openings for cybersecurity analysts — a common entry-level role in Security Operations Centers (SOCs). Three years later, that number has dropped nearly 50% to just 36,000. That shift is not the result of a recession or hiring freeze. It’s happening during a time of elevated cyber risk and persistent workforce shortages. The underlying reason is something more structural: AI has begun to automate away the first layer of cybersecurity work.

The foundational bottlenecks of technology have shifted from software layers to physical constraints like energy, critical minerals, and manufacturing capacity — now the true rate-limiters to AI and reindustrialization. As megawatts and metals become the new protocols of progress, venture-scale opportunities lie in upgrading power infrastructure, securing domestic mineral supply chains, and accelerating extraction, refining, and recycling. The Energy & Strategic Minerals Syndicate is backing the founders building solutions for this new industrial frontier, where power availability and resource resilience define the future of innovation.