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.

Technology's share of the economy will grow as it underpins every industry. Conversely, the services sector, which sells human intelligence for repetitive tasks, is fundamentally threatened by AI that can automate processes and commoditize expertise.

In stable markets, answering established questions works. During systemic shifts, like today's geopolitical and monetary changes, investors must first identify new, relevant questions. The greatest risk is perfecting answers to outdated problems, a common pitfall highlighted by financial history.

Instead of betting on unknowable AI winners, a better strategy is to find quality companies the market has written off as "losers" due to AI fears. Similar to the unloved "old economy" stocks during the dot-com bubble, these perceived victims could offer significant upside if the disruption threat is overblown.

As AI becomes capable of improving itself, capital may concentrate on these systems, seeking exponential returns. This creates a new paradigm where traditional value investing strategies, which rely on mean reversion, could fail as certain sectors get permanently disrupted while others achieve sustained, compounding growth.

Investor uncertainty about the long-term viability of software business models due to AI is causing a fundamental shift in valuation. Instead of paying a premium for future growth, investors are now demanding immediate returns like dividends, effectively treating established software firms as value stocks rather than growth stocks.

During periods of low interest rates, investors flock to dividend stocks seeking income. This concentrated buying pressure inflates their valuations relative to fundamentals. Investors who buy during these waves of high demand are purchasing at inflated prices, setting themselves up for significant underperformance when the trend inevitably reverses.

Traditional value stocks face an existential threat from AI. The HALO strategy mitigates this by focusing on companies AI cannot replace but can make more efficient, such as railroads or copper mines. This provides a modern framework for finding undervalued assets without the risk of technological obsolescence.

The era of constant central bank intervention has rendered traditional value investing irrelevant. Market movements are now dictated by liquidity and stimulus flows, not by fundamental analysis of a company's intrinsic value. Investors must now track the 'liquidity impulse' to succeed.