Meta-Learning Tracer
Ki · Single Ability
The Problem
Despite correcting the data entry error earlier, the same mistake recurred twice, showing episodic forgetting of previous corrections.
The Operation
The model is directed to scan the current session for patterns, corrections, and refinements that constitute within-session learning. Extract specific lessons, what was tried, what failed, what worked. Classify each lesson by generalizability: task-specific, domain-transferable, or universal. Verify that extracted lessons are being applied to subsequent reasoning steps. Trace whether learning is cumulative or resetting within the session.
The Structure
Structurally, this is an incremental belief propagation that updates confidence step by step as evidence arrives. It iterates until no further refinement is possible.
If the same error pattern recurs later in the analysis that was corrected earlier, within-session learning tracking was not performed.
Haki · Multi Ability
Synergy Topology
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, these four abilities don't run in sequence. They merge into a single injection where the dependency grounds the reasoning context, the amplifier sharpens the primary's output, and the alternative provides a fallback path if the primary's topology cannot converge. The result is a multi-angle reasoning scaffold that covers failure modes no single ability can reach alone.