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.

Cliff Asness argues that quant strategies like value investing persist through all technological eras because their true edge is arbitraging consistent human behaviors like over-extrapolation. As long as people get swept up in narratives and misprice assets, the quantitative edge will remain.

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.

All-AI organizations will struggle to replace human ones until AI masters a wide range of skills. Humans will retain a critical edge in areas like long-horizon strategy and metacognition, allowing human-AI teams to outperform purely AI systems, potentially until around 2040.

In an unpredictable AI-driven job market, the most reliable path to financial security is not a specific skill but owning assets. This allows individuals to participate in the massive wealth generated by the technology itself, providing a hedge against inflation and potential job displacement, and avoiding a future of dependency on government assistance.

In a world where AI can efficiently predict outcomes based on past data, predictable behavior becomes less valuable. Sam Altman suggests that the ability to generate ideas that are both contrarian—even to one's own patterns—and correct will see its value increase significantly.

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.

Advanced AIs, like those in Starcraft, can dominate human experts in controlled scenarios but collapse when faced with a minor surprise. This reveals a critical vulnerability. Human investors can generate alpha by focusing on situations where unforeseen events or "thick tail" risks are likely, as these are the blind spots for purely algorithmic strategies.

The narrative that AI will disadvantage retail day traders is flawed; they are already being systematically beaten by sophisticated firms like Citadel. AI merely changes the identity of the winner who extracts value from the retail gambler, not the outcome for the gambler.