With information now ubiquitous, the primary source of market inefficiency is no longer informational but behavioral. The most durable edge is "time arbitrage"—exploiting the market's obsession with short-term results by focusing on a business's normalized potential over a two-to-four-year horizon.

Historically, investment tech focused on speed. Modern AI, like AlphaGo, offers something new: inhuman intelligence that reveals novel insights and strategies humans miss. For investors, this means moving beyond automation to using AI as a tool for generating genuine alpha through superior inference.

VCs generate outsized returns by backing 'alpha'—fundamentally different ways of solving a problem. Many funds in the 2020-2021 ZIRP era mistakenly chased 'beta'—backing slightly better execution of known models. This operational bet is not true venture capital and rarely produces foundational companies.

For breakthrough technologies like AI and quantum, traditional valuation is less important initially. Investors must buy into the narrative, long-term potential, and quality of the management team, much like early-stage seed investing. Near-term earnings are secondary to the transformative vision.

The pace of AI-driven innovation has accelerated so dramatically that marginal improvements are quickly rendered obsolete. Founders must pursue ideas that offer an order-of-magnitude change to their industry, as anything less will be overtaken by the next wave of technology.

Alex Sacerdote's investment thesis identifies technologies at their adoption inflection point (S-curve), finds companies with strong competitive advantages within that trend, and capitalizes on the resulting exponential, often overlooked, earnings growth. This three-part framework guides their entire investment process for technology stocks.

Traditional market sizing, which analyzes existing demand, is useless for true technological breakthroughs. A fundamental change on the supply side (e.g., GPUs for AI, cloud for software) unlocks markets that are orders of magnitude larger than their predecessors (e.g., gaming, on-prem software).

Companies like Tesla and Oracle achieve massive valuations not through profits, but by capturing the dominant market story, such as becoming an "AI company." Investors should analyze a company's ability to create and own the next compelling narrative.

As quantitative models and AI dominate traditional strategies, the only remaining source of alpha is in "weird" situations. These are unique, non-replicable events, like the Elon Musk-Twitter saga, that lack historical parallels for machines to model. Investors must shift from finding undervalued assets to identifying structurally strange opportunities where human judgment has an edge.