Decision Models: From a Typed Prediction to an Accountable Action

A model can return probabilities and a recommendation. A product still needs to decide what action is allowed, what evidence is sufficient, and who remains accountable. This 13-chapter guide introduces Jev and other decision models through that boundary between prediction and action.

A chapter map:

• Chapters 1–3: tickets and the decision-model idea: work through a ten-ticket example, then define what a decision model is and is not.
• Chapters 4–6: read the numbers and inspect a measured case: interpret an output, follow one real call, and see what the reported experiments establish.
• Chapters 7–9: alternatives and limits: compare the cascade that regressed and examine what changes around the model.
• Chapters 10–13: policy, accountability, and what to build: place policy between prediction and action, then consider extensions and a first implementation.
• Appendix A: what was and was not validated: separate the reproduced work from reported measurements and unvalidated claims.

The reading edition includes chapter mind maps and synthetic narration. The guide takes about 114 minutes to listen to. Its offline workflow uses synthetic tickets, not measured model performance. Read or listen to the complete guide.