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Model confidence and calibration

Writing promptsSharing and versioning promptsToken costs and contextModel confidence and calibrationRouting across modelsFallbacks and retries
Business

Model confidence and calibration

  • Model Confidence Score vs. Your Own Classifier
  • Setting a Confidence Threshold from a Calibration Curve
  • Why a Model's 0.8 Is Not 80 Percent Right
  • A Confidence Score the Agent Can Act On
  • A Drift Check for a Confidence Gate Without New Labels
  • A Job Aid for the Operator in the Middle Band
  • A Moving Threshold: Recalibrating When Input Distribution Shifts
  • How to Set a Confidence Threshold for an Agent's Tool Calls
  • How to Tell Whether a Score Is Calibrated Enough to Act On
  • Re-Checking Calibration After a Model Swap or Prompt Change
  • Setting a Cost-Weighted Threshold When Errors Differ in Price
  • Testing a Model's Confidence Against the Read-Ahead Sample
  • The Handoff Band: Turning a Calibration Curve into Two Cutoffs
  • Using the Calibration Curve to Pick a Handoff Band
  • What to Log So You Can Rebuild a Calibration Curve Later
  • When the Classifier and the Model Disagree: A Triage Rule
  • When Two Score Bands Overlap: Choosing the Cutoff
Prompts and model routing

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