Protocol amendments increased 60% between pre-2015 and 2022, rising from 2.1 to 3.3 per trial. Each Phase III amendment costs a median $535,000 in direct implementation costs, not counting timeline delays or site disruption. The quality problem isn't speed. AI copilot tools cut IND drafting time by 97%, but quality scores ranged only 69.6 to 77.9%, requiring substantial expert revision. The gap: copilots generate text on command, but can't check whether eligibility criteria in one section match statistical assumptions in another unless explicitly prompted. Agentic AI systems are architecturally different. They retrieve current regulatory guidance at drafting time, run cross-document consistency checks across protocol sections, and perform internal validation passes before human review. In ICF generation studies, structured AI with embedded regulatory rules achieved over 90% factual accuracy compared to 57 to 82% for unstructured LLM use. For protocols, the direct evidence is still forming, but the architectural case is clear: systems that can validate their own outputs before human review address the structural causes of avoidable amendments better than prompt-response tools.