# Compute-aware admission control

Adapting a protein foundation model to one laboratory's assay is an expensive, failure-prone step, and existing agents treat fine-tuning as a reliable tool call whose feasibility is estimated and whose infeasibility surfaces only after compute is spent. CAPO reframes adaptation as a gated decision: it measures feasibility on the target accelerator, admits or rejects a configuration against a budget, runs a 200-step canary inside the real training loop, and may decline. One unchanged system chose partial fine-tuning of ESM-2 8M, refused to fine-tune Boltz-2 in favor of a calibrated head over frozen representations, and applied rank-4 low-rank adaptation to ESM-2 150M across three protein tasks.

Adapting a protein foundation model to one laboratory's assay is an expensive, failure-prone step, and existing agents treat fine-tuning as a reliable tool call whose feasibility is estimated and whose infeasibility surfaces only after compute is spent. CAPO reframes adaptation as a gated decision: it measures feasibility on the target accelerator, admits or rejects a configuration against a budget, runs a 200-step canary inside the real training loop, and may decline. One unchanged system chose partial fine-tuning of ESM-2 8M, refused to fine-tune Boltz-2 in favor of a calibrated head over frozen representations, and applied rank-4 low-rank adaptation to ESM-2 150M across three protein tasks.