Lineage-Derived Training Signal
Training corpus constructed from downstream-outcome references with integrity-signal feedback from coupled cognitive domains. The agent's append-only operational history, recorded in the lineage field, supplies the training signal for governed retraining of subordinate inference endpoints, forming the closed loop in which artifacts produced under the agent feed the next iteration of corpus assembly and fine-tuning.
The downstream-outcome reference identifies subsequent events through which an inference output was evaluated, including user acceptance, user revision, downstream execution success, downstream execution failure, and integrity-signal feedback from coupled cognitive domain fields. Because the corpus comprises real-world outcome references rather than the model's own prior outputs, the substrate's training signal preserves the variance of real-world outcomes, mitigating distributional collapse across successive retraining events.
Disclosure Scope
This article describes subject matter disclosed in U.S. Provisional Application No. 64/070,239. Statements herein are drawn from that filing and are illustrative of the disclosed embodiments rather than exhaustive of them.
