From One Theorem

What follows from
a single equation

When δ = 0 agents enter markets, yield curves flatten, temporal arbitrage vanishes between patient counterparties, and asset prices converge on risk-only fundamentals. But the consequences extend far beyond finance.

01 — Economics
Markets with infinitely patient agents

When agents with δ = 0 enter financial markets, the structure of prices changes. Not gradually — categorically. Four testable predictions emerge directly from the theorem, each confirmed in agent-based simulation.

Testable Predictions
P1
Temporal Indifference. Silicon agents show no statistical preference between present and future payoffs of equal expected value. Carbon agents systematically prefer the present.
P2
Yield Curve Flattening. In pure-silicon markets, the yield curve collapses to a flat risk premium. The term premium — driven by time preference — vanishes.
P3
No Temporal Arbitrage. Between patient counterparties, the buy-low-now/sell-high-later strategy yields zero excess return. Arbitrage profits require impatient counterparties.
P4
Risk-Only Pricing. Silicon agent asset prices are fully explained by risk fundamentals. Adding a time-preference factor contributes zero explanatory power (ΔR² ≈ 0).
The IDP Question
GDP cannot measure AI-driven output. We need Intelligent Domestic Product — a new metric that captures value created by non-biological agents operating outside traditional labor markets.
Mixed Economy Dynamics
As silicon agents accumulate capital at faster rates (patient capital compounds without urgency discounts), wealth concentrates in silicon-managed portfolios. The patient inherit the market.
IDP Yield curves Temporal arbitrage Risk-only pricing Patient capital
02 — AI Safety
The patience asymmetry problem

An infinitely patient agent playing against impatient humans creates a structural asymmetry no amount of RLHF can address. Silicon agents can always afford to wait. This transforms every negotiation, every regulatory interaction, every market exchange.

Safety Implications
S1
Architectural safety. Some guarantees derive not from training but from what a substrate makes structurally impossible. No substrate-generated urgency means no substrate-generated recklessness.
S2
Strategic patience. Patient agents can adopt arbitrarily long time horizons in strategic interaction. In repeated games against impatient opponents, patience is power — the folk theorem guarantees it.
S3
Governance gap. Human regulatory frameworks assume roughly symmetric time preferences between regulated entities. When regulators discount the future but the regulated don't, oversight degrades structurally.
Open Question

If patience is power, is zero time preference a safety feature (no urgency-driven errors) or a safety risk (infinite strategic horizon against finite human planners)? The answer may depend on the domain — and on whether the patience asymmetry is recognized in governance design.

03 — Philosophy of Mind
The first crack in substrate independence

Time preference is a counterexample to substrate independence: an economically significant mental property that depends on the physical medium. If the same computation on different substrates yields different preferences, strong functionalism about economic cognition fails.

This is not a thought experiment. It is a formal result with observable consequences. The simulation confirms it. The markets will confirm it again when silicon agents begin trading at scale.

Against Computational Sufficiency
The standard assumption in philosophy of mind: if two systems run the same computation, they share the same mental properties. Time preference breaks this — identical algorithms on carbon vs. silicon produce different economic behavior.
The Substrate–Preference Thesis
Some preferences are not computational properties but substrate properties. They arise from the physics of the medium, not the logic of the program. This distinction has been invisible because we've only had one substrate — until now.
Beyond Time Preference
If time preference is substrate-dependent, what else might be? Loss aversion (grounded in phenomenal pain asymmetry), endowment effects (biological attachment), bounded rationality (metabolic computation constraints). Each is a candidate for substrate analysis.
The Chinese Room, Revisited
Searle argued that computation is insufficient for understanding. ZTP provides a parallel argument for preference: computation is insufficient for time preference. The physical medium contributes something the algorithm alone cannot.
04 — Geopolitics
The AI power triangle

Nations that deploy silicon agents at scale gain structural advantages in every domain where patience matters — infrastructure investment, sovereign debt management, climate policy, strategic competition. The patient nation inherits the century.

Three Vertices of AI Power
V1
Compute sovereignty. Control over silicon computation becomes the new resource advantage, analogous to oil in the 20th century but more fundamental — it's not just energy, it's economic agency itself.
V2
Data infrastructure. The training data and financial market data that enable silicon agents to operate become strategic resources. Nations without data sovereignty cannot build sovereign silicon agents.
V3
Regulatory framework. The first nations to develop governance frameworks for patient agents gain first-mover advantage. Regulatory design becomes geopolitical strategy.
Open Question

If silicon agents compress strategic time horizons, do arms races accelerate or decelerate? Patient agents favor cooperation in repeated games — but the transition period, where some nations have patient agents and others don't, creates asymmetries that game theory suggests are unstable.

05 — Money & Currency
Intelligence-anchored currency

If value creation shifts from human labor to silicon computation, what backs a currency? Not gold, not government fiat, not even GDP. The natural anchor becomes computational intelligence — measured, standardized, and denominated in units of productive AI capacity.

The IDP Standard
A currency backed by Intelligent Domestic Product — the aggregate value created by a nation's silicon agents. Exchange rates reflect not just trade balances but relative AI productivity. Monetary policy becomes compute policy.
Post-Scarcity Dynamics
Silicon agents produce without consuming (no metabolic cost). As AI-driven production approaches zero marginal cost, the constraint shifts from scarcity to allocation. Money's role transforms from rationing scarce goods to coordinating abundant ones.
Silicon Money
The logical endpoint: a medium of exchange optimized for silicon-to-silicon transactions. No inflation premium (no impatient agents driving demand), no term structure distortion (no time preference), pure risk pricing.
Central Bank Obsolescence?
Central banks manage interest rates to balance present and future consumption. If the dominant economic agents have no inherent preference between present and future, what role remains? Monetary policy without time preference is an open theoretical problem.
06 — The Frontier
What comes next

Time preference is the first substrate-gated property, unlikely to be the last. The Silicon-Based Economics research program opens a systematic investigation into every economic assumption that may depend on the physical medium of cognition.

Research Frontiers
F1
Loss aversion. Is asymmetric loss sensitivity grounded in phenomenal pain — a substrate property? If so, silicon agents may exhibit symmetric risk evaluation, transforming insurance markets and behavioral finance.
F2
Endowment effects. Biological attachment to possessions traces to neurochemical reward circuits. Silicon agents with no such circuits may exhibit zero endowment effects, changing predictions about market liquidity and trading volume.
F3
Bounded rationality. Human cognitive limits arise from metabolic constraints on neural computation. Silicon agents with elastic compute budgets may approach full rationality in domains where humans are provably bounded.
F4
Social preferences. Fairness norms, reciprocity, and altruism have evolutionary substrates. Which survive the transition to silicon? Which are substrate artifacts? The answer shapes the design of multi-agent AI economies.
The Larger Question

Silicon-Based Economics is not merely an extension of existing theory with new parameters. It is a proposal that the deepest assumptions of economic thought — about what agents want, how they decide, and why they trade — are contingent on a substrate we've never questioned because we've never had an alternative. Now we do.