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Operations Guide

AI Quality Calibration Framework (2026) - Operations Guide

Thresholds drift fast when calibration is untracked. This framework aligns quality ops, product, and engineering teams on baseline-driven calibration with fixed review cadence.

Direct answer

Thresholds drift fast when calibration is untracked. This framework aligns quality ops, product, and engineering teams on baseline-driven calibration with fixed review cadence.

Fast path

  1. Collect baseline quality scores for each dimension with historical variance bands.
  2. Set threshold adjustment triggers based on drift detection and user feedback correlation.
  3. Track false-positive and false-negative rates per criterion with owner-assigned root cause.

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Implementation Steps

  1. Collect baseline quality scores for each dimension with historical variance bands.
  2. Set threshold adjustment triggers based on drift detection and user feedback correlation.
  3. Track false-positive and false-negative rates per criterion with owner-assigned root cause.
  4. Feed calibration outcomes into scoring framework updates and escalation policy refinement.

Related Guides

Use these adjacent playbooks to keep the same workflow connected across discovery, conversion, and execution.

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