1. Start with a Structural Analogy

Identify a complex system in one domain (LLMs in language) and map it to a well-understood system in another (index funds in finance). Ensure the analogy is not superficial—seek systemic parallels in behavior, incentives, and emergent dynamics.

2. Establish Historical Precedent

Introduce a real-world, data-backed precedent (baby name diversification) to show how similar pressures (homogenization vs. individuation) have played out under earlier technological regimes (broadcast media → internet).

3. Define Conceptual Currency

Coin or adopt precise terms to ground the analogy:

Linguistic alpha = surplus expressive or conceptual value

Beta language = average, LLM-produced fluency

IPO of language = public release of original work

4. Frame a Two-Tier System

Articulate how the new environment bifurcates into:

A public, LLM-saturated layer (standardized, low-variance)

A private, experimental layer (risky, creative, context-rich)

5. Loop the Analogy Recursively

Describe how alpha becomes beta: how original language gets commodified by models, mirroring market cycles of innovation and assimilation.

6. Subtly Anchor in Existing Theory

Minimalistically reference concepts like the cozyweb and dark forest as locations for hidden, non-indexed value without diluting the main analogy.

7. Maintain Clean, High-Energy Prose

Keep tone neutral but alive—avoid manifesto or personal voice shifts. Let the ideas carry the charge.

8. Terminate on a Conceptual Open Loop

Conclude not with resolution, but with a hint at future discovery. Signal that this pattern (alpha → beta → renewed alpha) is ongoing, and that the edge belongs to those who can stay ahead of the flattening.

Venkatesh Rao • LLMs as Index Funds