mechanism-design

Design API rate limits by structuring quotas and retry policies so the best individual client strategy also supports overall service stability. This involves modeling player actions, payoffs, and Nash equilibria to ensure cooperative behavior dominates.

Mechanism design creates rules and incentive structures for multi-agent systems where participants act on private information. It models equilibria and manipulation vectors to make cooperative behavior the dominant strategy for self-interested actors in quotas, scheduling, and voting.

Stress-test auctions and scheduling APIs by evaluating them against sybil attacks, collusion, misreporting, tie-break exploitation, and side markets. This adversarial robustness analysis identifies manipulation risks and verifies implementation invariants before rollout.

Use equilibrium analysis to design fair internal chargeback and capacity allocation by modeling independent actors' payoffs and strategies. This evaluates individual rationality and stability, ensuring the allocation mechanism remains effective even when tenant teams optimize for their own advantage.

Apply game theory to API design when standard throttling fails because users, teams, or tenants are rewarded for behavior that harms the overall outcome. If independent actors can exploit retry budgets or side markets, equilibrium analysis is needed to align incentives by design.