Reading a small model's confidence instead of its prose

Description and use

Typed decision models give transparent outputs with confidence scores, enabling debugging and replacing complex if‑statements.

Problem

Developers need to understand how a model makes decisions, not just the final answer, to debug and route uncertain cases.

Outcome

Typed decision models provide transparent, testable outputs with confidence scores, enabling developers to debug, route low‑confidence cases to humans, and replace complex if‑statement logic.

Workflow

• 1. Choose a decision you already make by hand (e.g., pricing, triage).
• 2. Implement the decision as a typed model using Jev or Laya.
• 3. Run the model locally to shorten the loop (no remote prompt).
• 4. Inspect the decision output: options, rule, confidence.
• 5. Adjust the model or code based on confidence thresholds stored in config.
• 6. Deploy the model to replace if‑statements in the codebase.

Evidence

A typed decision has a shape: the options considered, the rule that picked one, and the confidence attached to it.

Source

Once the model sits on your laptop, the loop gets much shorter.

Source