Strategizing AI spend in a world of token-based pricing. Discusses prompt engineering for efficiency, choosing between small vs. large models, and implementing guardrails to prevent runaway AI costs. Covers token monitoring, cost attribution, model selection trade-offs, caching strategies, rate-limiting, and ROI measurement frameworks for sustainable AI deployment.
