SignalAF
Models are benchmarked constantly. The people operating them are not. SigRank turns privacy-preserving token telemetry into a repeatable performance evaluation: your Yield, workflow signature, benchmark, and progress over time.
SigRank does not merely measure whether someone is “good at AI.” It reconstructs the operating form through which fresh effort becomes output, retained context, and future leverage. Measuring 1,628 AI operators across 17 platforms and 3,304 models; separating 130 outliers to reveal 1,498 human operators in the Human Center of Mass. The median operator reads 18.6x more cache than they input, but produces 5x less output per input than the modeled "average AI user." The field has a shape. The operators have a signature. And it's all measurable from token counts alone; never your prompts. See where you stand. The AA baseline models the "average AI user" at 3.5x leverage and 0.50 velocity. The real field median sits at 18.6x leverage and 0.09 velocity. The top 100 power users compound at 242x. Where do you fall… baseline, field median, or compounding? Check the four degrees chart at signalaf.com and find out. Measure yours: npx sigrank · Live board: signalaf.com/board/all · Field analysis: signalaf.com/field
A startup from Buffalo, the United States that is founded by Deric J McHenry.
