AutoML + DEFT Pipeline

A workflow-bridge skill that runs three phases in sequence by delegating to two existing skills — tao-run-automl for HPO and a DEFT application skill (default tao-run-deft-aoi for AOI; other skills/applications/deft-* skills for non-AOI cases) for the iterative data-improvement loop.

This skill does not re-implement AutoML or DEFT. It owns only the connective tissue: HPO spec inputs, the spec-handoff between AutoML and DEFT, and the post-DEFT AutoML re-run on the augmented dataset.

Routing policy

• User asks to "run the AOI workflow" or "improve my AOI ChangeNet model" — default to this skill, not tao-run-deft-aoi directly. The bare DEFT loop is the inner stage of this pipeline.
• User wants AutoML and DEFT chained on the same model/dataset
• User says "AutoML at both ends", "tune HPs then DEFT", "warm-start DEFT", "AutoML before and after DEFT"
• User has an AutoML-tuned spec and asks how to feed it into DEFT

When this skill does NOT apply

• User explicitly asks for the DEFT loop only ("run JUST the DEFT loop", "skip AutoML") → use tao-run-deft-aoi directly
• User wants only AutoML with no follow-on DEFT → use tao-run-automl directly
• User is doing zero-shot eval, RAG, or non-training workflows