Wright's Law Cost Reduction

Applied Learning Rate

Using observed parameters from the learning pipeline:

Cost per finding at experience level n:
C(n) = C₁ × n^(-0.35)

Progress ratio: 2^(-0.35) = 0.785
→ 21.5% cost reduction per doubling of cumulative findings

Projected Cost Trajectory

Year	Cumulative Findings	Est. Cost/Finding	Reduction from Baseline
Y1	50	$45	Baseline
Y2	500	$18	-60%
Y3	5,000	$7	-84%
Y5	50,000	$3	-93%

Why This Matters

Traditional platforms don't learn — each new bounty program starts from zero. Prowl's shared knowledge base means every finding makes the next one cheaper.

Competitors starting from zero face Prowl's Year 1 costs while Prowl is at Year 3+. The learning pipeline is the moat.

See also: Learning Curve (Wright's Law) for the full mathematical treatment.