improve-openui-harnesses

Maintain SLM training harnesses by enforcing strict architectural invariants and deterministic decode constraints during modifications. This ensures experiment pipelines, data synthesis, and promotion gates remain consistent and reproducible across iterative updates without breaking lineage tracking or version-stamp contracts.

Update OpenUI evaluation pipelines by verifying schema compliance, bumping version stamps, and adding regression tests when adding new training data sources. This structured approach enforces non-negotiable decode invariants and deterministic bypass requirements while maintaining strict lineage tracking.

Enforce decode invariants in model-build scripts by using a fail-closed framework that validates all changes against non-negotiable deterministic decode constraints. This ensures schema compliance, updates version stamps, and includes necessary regression tests before any modification is promoted.

Yes, this approach supports training, evaluation, distillation, and RL harness lifecycle management. It safely updates all harness types while enforcing strict architectural invariants, version-stamp contracts, and deterministic decode constraints to maintain experiment reproducibility and compliance.

Version-stamp contracts are required whenever modifying training, evaluation, or research harnesses, adding data sources, or changing model-build scripts. They ensure strict schema compliance, maintain lineage tracking, and enforce deterministic decode constraints across all experiment pipeline updates.