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Most current VCs come from software backgrounds and lack the deep hardware expertise of 90s-era investors. This knowledge gap creates an arbitrage opportunity for those who can properly vet semiconductor and networking startups, avoiding hype cycles around inexperienced founders.

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A safer way to play the AI boom is to invest in companies selling the underlying compute infrastructure rather than the hyperscalers buying it. This strategy captures the upside of the secular trend while avoiding direct exposure to how the massive capital expenditure is funded, which may involve risky credit.

Due to the nascent and highly specialized nature of AI, VCs find that traditional expert networks are no longer effective for diligence. Instead, they must rely on curated personal networks of deep specialists who can genuinely assess new technologies and teams.

Unlike software, hard tech involves long scale-up timelines and high capital costs. Founders must specifically seek the small subset of investors and partners who understand the market context and have the risk appetite for massive, world-changing opportunities, rather than trying to appeal to all VCs.

In the AI gold rush, don't bet on the "miners" like Google and Meta, who are spending billions on a new, high-risk game. Instead, invest in the "pickaxe makers"—the essential toll bridges like TSMC and ASML that every AI company must pass through, ensuring your investment has a higher probability of success.

When a new technology stack like AI emerges, the infrastructure layer (chips, networking) inflects first and has the most identifiable winners. Sacerdote argues the application and model layers are riskier and less predictable, similar to the early, chaotic days of internet search engines before Google's dominance.

As AI commoditizes software, hardware is re-emerging as a key defensibility layer for startups. A decade ago, VCs avoided hardware, but now a physical device tied to a software subscription creates powerful stickiness and justifies high valuations, representing a major shift in investment strategy.

A VC from Emergence Capital argues the industry is in a "massive compute shortage" driven by compute-intensive reasoning models. This hardware constraint is forcing a strategic shift in investment theses, with VCs now actively seeking companies that make intelligence more efficient at every level, from chips to algorithms.

Venture firm Benchmark, known for consumer tech like Uber and Snap, making a highly successful 12x return on chipmaker Cerebras indicates a strategic shift. Generalist VCs are now validating and pursuing moonshot AI infrastructure investments, a category once left to specialists.

AI makes it easy to replicate successful software, diminishing moats. This threat of being "vibe coded" pushes early-stage investors like Hustle Fund to seek defensibility by backing more complex, harder-to-copy infrastructure and hardware companies instead of just applications.

To capitalize on the AI boom while mitigating risk, investors should focus on 'enablers'—companies providing essential infrastructure like semiconductors, data centers, and cloud services. This 'picks and shovels' strategy avoids betting on specific application-level winners, which was a losing strategy for many dot-com investors.