AI agents can already own multi-step workflows that would take a human engineer minutes to an hour or more, but most organizations should deploy them as first-pass systems rather than final decision-makers. In this model, an agent performs an initial review and flags potential issues — such as ambiguous notes, title block inconsistencies, or standards violations — and the design owner then reviews those findings and decides what to address, override, or accept. No steps are skipped, humans remain accountable for trade-offs, and the agent improves efficiency by catching basic or easily missed issues early. The result is a cleaner design entering human review, allowing engineers to focus their time on nuanced engineering decisions instead of basic checks.