The complex effects of AI are causing traditional market relationships, like yields reacting to economic surprises, to break down. In this new regime, broad diversification and passive strategies are ineffective as winners and losers become more distinct and dispersion explodes.

Contrary to popular belief, the market may be getting less efficient. The dominance of indexing, quant funds, and multi-manager pods—all with short time horizons—creates dislocations. This leaves opportunities for long-term investors to buy valuable assets that are neglected because their path to value creation is uncertain.

In hyper-competitive fields, the emergence of dominant strategies that seem "insane"—like the Fosbury Flop or AI's aggressive poker bets—signals evolution to the highest level. For investors, this means strategies that appear bizarre may represent the new, optimal approach in a market saturated by traditional thinking, rather than being mere anomalies.

Investors try to apply lessons from past market cycles, but this collective awareness changes their behavior. This creates a self-reinforcing loop that alters timelines and dynamics, ensuring history only rhymes, not repeats.

David Kaiser of Methodical Investments posits a contrarian view on AI's market impact. Instead of creating perfect efficiency, he argues AI and the data it processes might actually create more mispricings and inefficiencies. This provides opportunities for disciplined, rules-based strategies that don't constantly adapt to short-term noise.

Contrary to classic theory, markets may be growing less efficient. This is driven not only by passive indexing but also by a structural shift in active management towards short-term, quantitative strategies that prioritize immediate price movements over long-term fundamental value.

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.

Quoting G.K. Chesterton, Antti Ilmanen highlights that markets are "nearly reasonable, but not quite." This creates a trap for purely logical investors, as the market's perceived precision is obvious, but its underlying randomness is hidden. This underscores the need for deep humility when forecasting financial markets.

The dominance of passive, systematic investing has transformed public equities into a speculative "ghost town" driven by algorithms, not fundamentals. Consequently, financing for significant, long-term industrial innovation is shifting to private markets, leaving public markets rife with short-term, meme-driven behavior.