The adoption ceiling on agentic AI is not a marketing failure — it is a workflow compatibility problem that autonomous systems cannot resolve by improving. When a practitioner documents that TDD-trained developers encounter agentic tools differently than those who never enforced tight feedback loops [1], the implication is that the tool's behavior is constant but the developer's capacity to supervise it is not. Autonomous agents require someone to design the task, validate the output, and catch the errors that confident generation produces — and those skills are unevenly distributed in…