Engineering the Path from Question to Judgment

Artificial intelligence can generate increasingly capable answers, but an answer is not the same thing as a durable judgment. This paper treats the path from question to judgment as an engineering object spanning both human and artificial intelligence. The FISE / LimFlex Judgment Ecosystem separates intelligence, judgment, authority, and execution. A question is treated as a specification for the judgment to be formed; information is not promoted directly into evidence; unresolved states are preserved rather than collapsed into false certainty; and completion requires a positive finite basis rather than the mere absence of detected objections. The persistent object is not the model answer but an externalized judgment structure: a bounded representation of what the judgment concerns, what basis supports it, what remains unresolved, what dependencies and conditions apply, how its validity may change over time, and what authority boundary constrains its use. The LimFlex Judgment Terrarium provides an environment for forming, preserving, inspecting, and requalifying such structures. JEZ, or Judgment Ecosystem ZIP, is the public portable-package concept for carrying them across compatible systems, times, teams, or environments. Portability does not imply current applicability, qualification, or authorization; those properties must be reassessed at the destination. The paper develops Judgment Capital as an engineering asset concept: accumulated judgment structures that can be inspected, challenged, requalified, and selectively reused rather than repeatedly reconstructed from scratch. A recurring FDA public-enforcement example is used throughout the manuscript to show how a public record can be transformed into a bounded judgment without transferring execution authority. The empirical section reports only bounded, public-safe results. These include qualified-boundary stability under tested AI-process variation, authority-separation controls, lifecycle continuity, portability, long-horizon replay, representative fault recovery, specification-based reconstruction, external public-record judgment formation, and Positive Finite Closure. Aggregate implementation measurements are reported separately from provider latency and are not presented as production end-to-end TCO evidence.