Dr. Neil's Notes
Software > Development > AI in Delivery Systems
Metrics that matter
Introduction
Counting prompts, sessions, or model calls can create the illusion of progress. Outcome-oriented teams measure changes in delivery performance, quality, and team effectiveness.
Track flow and quality together
Measure cycle time, lead time, and throughput alongside defects and rework. Faster without safer is fragile, safer without faster may not get further investment.
Measure cognitive load
If AI introduces more review overhead than value, teams will feel slower even if some metrics improve. Track time spent in manual verification and context switching as signals.
Use metrics to decide, not decorate
Metrics should drive continuation, redesign, or retirement decisions for each new change. A metric that does not influence a decision is reporting noise.
Part of the AI in Delivery Systems series.
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