Custody, Yield, and Strategy: A Game-Theoretic Framework for AI and Cyber-Farming

Custody, Yield, and Strategy

A Game-Theoretic Framework for AI, Cyber-Farming, and Sunset-Governed Assets

Modern digital enterprises operate in environments defined by intangible assets, distributed contribution, regulatory ambiguity, and adversarial competition. Traditional ownership-centric models—optimized for control and permanence—are increasingly brittle under these conditions.

This article proposes an alternative framework: a custodial, yield-oriented, sunset-governed model, enabled by AI and structured through principles drawn from bailee law, asset governance, and game theory. Rather than maximizing capture, the strategy optimizes for survivability, continuous yield, and low adversarial attractiveness.

1. Single-Point Custodianship as a Risk Primitive

Single-point custodianship occurs when one individual or entity holds exclusive control over an asset. While legally efficient, it concentrates liability, creates leverage asymmetries, and produces predictable attack surfaces.

In game-theoretic terms, single-point custody represents a pure strategy—easy to model, easy to target, and easy to exploit. Much of the framework that follows exists to deliberately disrupt this predictability.

2. Bailee Assignments and Proportional Custody

A bailee assignment formalizes custody without transferring ownership. Applied to multi-contributor environments, it enables proportional responsibility, bounded retention rights, and enforceable but time-limited claims.

Each contributor becomes a temporary steward rather than a permanent owner, allowing custody to be layered, divisible, and auditable.

3. Sunset Provisions as Governance Infrastructure

Sunset provisions impose automatic expiration on custody, retention, or lien-like rights. Rather than a legal afterthought, sunsets function as risk dampeners, equity stabilizers, and strategic commitment devices.

A conceptual grading model:

Sunset Grade = (Contribution × Enforceability × Priority) / (1 + Fork Factor)

Higher grades justify longer retention; lower grades decay quickly. This prevents indefinite leverage and aligns incentives across contributors.

4. AI and Cyber-Farming: From Products to Yield

Cyber-farming treats digital assets as renewable fields rather than static products. Inputs include data, prompts, behavioral signals, and creative fragments. AI performs cultivation, pruning, and recombination, producing yield streams instead of permanent artifacts.

The business shifts from deliverables to output flow, and from ownership events to custodial cycles.

5. AI as Bailee, Not Owner

AI systems operate as bailees—labor and equipment—not authors or owners.

This framing avoids authorship disputes, permanent title claims, and concentrated liability. AI improves assets under bounded authority, while outputs remain sunset-governed and custodially managed.

6. Forking as Strategic Randomization

Forking is not a loss of control; it is a strategic move. Forks dilute exclusive leverage, create parallel yield streams, reset sunset clocks, and increase adversarial uncertainty.

In game-theoretic terms, forking introduces controlled randomness into the state space, raising the cost of hostile action without escalating conflict.

7. The Game Being Played

The environment is a repeated, multi-player game with asymmetric information and partial observability. No actor has full visibility into asset value concentration, sunset timing, or fork lineage. This uncertainty is intentional and strategically valuable.

8. Yield vs Capture Payoffs

Strategy	Short-Term	Long-Term	Adversarial Risk
Capture / Ownership	High	Fragile	High
Yield / Custody	Moderate	Durable	Low

Capture strategies resemble one-shot defection. Cyber-farming resembles iterated cooperation with bounded defection. The firm deliberately avoids becoming a static, high-value target.

9. Custodial Layering as Mixed Strategy

Rather than committing to openness or secrecy, the system reveals selectively, expires information, and rotates custody. This produces a mixed-strategy equilibrium that adversaries cannot reliably model.

10. AI as Bounded-Rational Agent

AI introduces procedural noise and bounded intent. From a strategic standpoint, this reduces attribution, limits liability, and dampens adversarial precision. Friction becomes a feature, not a bug.

11. Adversarial Scenarios

Capture attempts are diluted by forks and sunsets. Legal probes encounter time-boxed exposure. Platform hostility is mitigated by portability and non-centralized custody. Each hostile move faces high cost and low expected reward.

12. Equilibrium Outcome

The system converges on a low-attractiveness, high-yield equilibrium: profitable without being extractable, productive without being monopolizable, innovative without being brittle.

Conclusion

A cyber-farming strategy governed by custodial logic, sunset provisions, and game-theoretic discipline represents a shift from ownership to stewardship, from products to yield, and from capture to survivability.

In adversarial, AI-saturated markets, strategic humility becomes a competitive advantage.