Predictive Coding Error Simulator
Ki · Reasoning
The Problem
The default behavior: The sales forecast remains unchanged despite market shifts; ignoring surprise maintains model stasis.
The Operation
When activated, the model must before processing new information, state what you predict the data to look like. Process actual information; compare each variable against prediction and flag every divergence. Classify each divergence. For each large divergence, isolate the failing assumption and generate smallest revision that explains the error. Substitute revised model and re-derive downstream conclusions.
The Structure
The reasoning structure is an iterative convergence loop that cycles until the reasoning stabilizes on a consistent answer. The process iterates until convergence, where additional passes add nothing new.
If prediction errors are ignored rather than being used to update the internal model, predictive coding error minimization was not active.
Haki · Reasoning-Multi
Cross-Domain Suppression
In Haki mode, the API retrieves the primary ability first, then fans out to three synergy roles that compound its reasoning.
When retrieved in Haki mode, the primary ability is augmented with failure guards extracted from 3 abilities in different cognitive domains. Each guard blocks a specific reasoning failure the primary alone wouldn't catch. A self-check forces verification before output. The result is cross-domain coverage that no single ability can reach alone.