3 game theory tactics, explained

Breaking a large adversarial interaction into many small, verifiable steps enables cooperation because limited concessions and observed reciprocation reduce mistrust and the incentive to defect, converting a social dilemma into mutual gains.

Designing interactions around outcomes that help both parties transforms perceived win–lose situations because explicitly seeking mutual benefits shifts choices toward cooperative strategies and institutions that avoid zero-sum tradeoffs.

Game theory applies across biology, international relations, and relationships because its core framework models how independent agents make decisions under uncertainty and respond to others' incentives, so the same strategic structures recur in different domains.

An interaction is strategic whenever each person pursues their own goals because each person's best choice depends on what the other wants and does, so outcomes arise from interdependent decision-making rather than isolated moves.

In zero-sum games against sophisticated opponents, the minimax strategy is optimal because it identifies the worst-case outcome an opponent can force and chooses actions that minimize that maximum loss, guaranteeing the best payoff you can secure regardless of their moves.

Poker trains decision-making under uncertainty because it forces choices without full information and requires balancing extracting value when strong with minimizing losses when weak, building probabilistic intuition and risk-managed rules you can apply elsewhere.

The sunk cost fallacy causes people to keep investing in losing courses of action because past time, money, or effort creates an emotional and cognitive pull to justify commitments, which overrides current assessments of future returns.