Iteration Velocity
The speed at which a human-AI pair can move from idea to tested output.
Iteration Velocity measures end-to-end cycle time: from the moment the user has an idea to the moment that idea is implemented, tested, and verified. High Iteration Velocity means the human-AI pair can try ideas quickly, learn from results, and iterate rapidly. Low Iteration Velocity means each cycle is slow — bogged down by re-onboarding, debugging agent errors, or waiting for retries. Iteration Velocity is the compound metric that reflects everything else working well: good Context Continuity, low Reasoning Tax, high Execution Fidelity, and efficient Selective Recall.
More in Measurement
Context Efficiency
Useful retained state per token consumed.
Token ROI
The measurable value produced per token consumed. The business metric for Context Efficiency.
Context Utilization Rate
The percentage of input context that the model actually uses for its output. Low rate = waste.
Recall Cost Ratio
The cost of retrieving stored context vs. the cost of re-generating it from scratch.
Waste Ratio
The proportion of tokens consumed that produce no useful output. The metric behind Token Bleed and Token Burn.
Recovery Cost
The time and tokens required to get a session back on track after a failure — State Loss, Execution Hallucination, or Plan Drift.
Quality-Per-Token
A measure of output quality relative to tokens consumed. Distinct from Token ROI (value) — this measures correctness, completeness, and relevance per unit of cost.