F4 (Tradeoffs) provides the frame for investment decisions: every engineering investment is a choice between two or more uses of engineering capacity, each with different costs, different returns, and different timelines. Naming the tradeoff — we are investing in streaming infrastructure instead of customer-facing feature X — makes the economic comparison possible.
F9 (Empirical Grounding) provides Little’s Law: throughput equals arrival rate times residence time (L = λW). In capacity planning, this law constrains the economics: if residence time (latency) increases, throughput decreases without adding capacity. Capacity planning that does not model latency growth will underestimate the infrastructure cost at scale.
T12 (Tradeoffs) frames the meta-decision: engineering economics is the vocabulary that makes technical tradeoffs legible to non-technical decision-makers. AT2 (Latency vs Throughput) is not just a systems tradeoff — it is an economic tradeoff. Higher throughput means lower cost per unit at scale. Lower latency means higher infrastructure cost for the same throughput. The economic consequence of AT2 is a cost curve, and the cost curve is what the board can evaluate.