I lay out a repeatable workflow to make my AI runs token‑efficient as pricing climbs, packaging the process into free prompts (AustinBelcak.com/Tokens).
Add Run Summaries to every workflow – creates an auditable trail and centralizes cost data.
Add Token Estimates To Your Run Summaries
Let your workflows run 5-10 more times.
Review the token costs and content from the past 10 runs. Identify the average cost per run, then perform an analysis across our entire workflow with the goal of reducing token consumption without sacrificing output quality. Then share a plan with your recommendations.
The seven‑step process (Run Summaries, token estimates, sample‑size execution, token audit, feedback loop, test period, comparison) lets me measure average token savings and verify quality before scaling.