When preparing an executive capstone presentation for Helpdesk Copilot, what is the primary risk of presenting only happy-path demonstrations where the assistant generates flawless drafts?
Day 30: Present the System and Plan Its Next Iteration
Present the System and Plan Its Next Iteration
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In the capstone evaluation summary above, the engineering team reports metrics with explicit numerators and denominators across 120 sampled tickets. Which of the four canonical iteration decisions (Expand, Revise, Pause, Stop) does this evidence support, assuming the agreed quality gate was at least 75 percent total acceptance with under 3 percent unsupported claims?
The Helpdesk Copilot team presents its 30-day capstone to the IT Steering Committee. Over a 3-week pilot covering 1,500 access-management tickets across 12 technicians: median time-to-first-reply dropped from 14.2 minutes to 8.6 minutes (39% reduction); fully-loaded inference and retrieval cost was $0.038 per accepted ticket (target: under $0.05); 81% of drafts were approved (62% verbatim, 19% minor edits); 19% were rejected or escalated (with 4% attributed to missing runbooks for newly migrated SaaS apps and 1% to input prompt injections caught by guardrails); and zero unauthorized tickets were dispatched, verified by the outbound audit log. The Support Director recommends immediately expanding Copilot to all 6,000 monthly enterprise tickets across all departments, including HR and Legal. Based on 30-day engineering principles, how should the Lead AI Engineer respond?