Abstract
<title>Abstract</title> <p>AI coding assistants can now produce production-quality code within seconds, and by 2025 more than 84% of professional developers were either using or actively planning to use such tools [19]. That shift compresses delivery timelines but does not resolve the harder problem: placing generated code safely into systems that pre-exist with their own history, established constraints, and unwritten rules. This paper reports practitioner observations from two professional roles in the financial services sector over a two-year period, documenting a consistent pattern: the engineers trusted with the most consequential work were not the most fluent prompt engineers. They were the most capable code readers. The gap separating them from their peers is formalised here as the Integration Premium, and the conditions that produce it are captured in the Comprehension-First Model (E = C × I × G) and a five-layer Integration Skill Stack. As AI generation quality (G) commoditises across the profession, code comprehension (C) and integration skill (I) emerge as the scarcest and most durable forms of professional capital a software practitioner can hold. The paper further examines the governance gap that AI-generated code introduces in regulated financial environments, where existing audit trails and provenance standards were not designed for distributed human-machine authorship.</p>