How toAgents & ToolsThe Neuron · 2h ago

Filter AI Workflow Decisions Using Confidence Thresholds

This technique forces an AI model to output a probability score alongside its decision so your system can catch uncertain outputs. Routing low-confidence responses to human reviewers reduces errors in automated software workflows.

Try it yourself

1Define a fixed list of allowed categorization choices for the model.
2Require the model to return a numerical confidence score between 0 and 1 with every response.
3Establish an escalation rule, such as flagging any confidence score below 0.85.
4Route low-confidence results to a human moderator or a more powerful AI model for secondary evaluation.

Copy this prompt

Classify the following request into one of these categories: [CATEGORY_1], [CATEGORY_2], or [CATEGORY_3]. Return only the decision, a confidence score between 0 and 1, and a single sentence explaining the key uncertainty. If your confidence score is below [0.85], select [CATEGORY_2] for secondary review.

Request content:
[INSERT_TEXT_HERE]

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