Decision Models Give Agents Bounded Judgment

Decision models are a promising middle layer between rigid rules and expensive generative models, but their confidence scores require serious validation before they control production actions.

• –Typed outputs eliminate malformed responses and constrain decisions to predefined options
• –Single-pass inference can reduce latency and cost for high-volume routing and classification
• –Confidence measures distribution sharpness, not correctness; miscalibrated models can be confidently wrong
• –Escalation policies should be tuned on real traffic using marginal rescued-answer cost
• –The category still lacks independent benchmarks, making vendor performance claims difficult to compare