NorthFirn field guide

How to tell whether an AI workflow is worth keeping

A simple way to measure quality, staff review time, mistakes, cost, and whether an AI workflow should continue.

By NorthFirn · Published July 15, 2026

Record today's work

Measure volume, time, corrections, mistakes, and the effect of a wrong answer before the workflow changes.

Measure the complete job

Track output quality, staff review, escalation, security needs, integration work, and cost.

Primary source

NIST AI Risk Management Framework