企業 AI 需求盤點Enterprise AI needs mapping
和團隊一起看客服、營運、內容生產與知識管理流程,先找出痛點、資料條件和 owner,再決定哪個場景值得優先導入 AI。Review customer-service, operations, content-production, and knowledge-management workflows with the team, then identify pain points, data conditions, owners, and practical AI starting points.
AI Agent 工作流程設計AI Agent workflow design
把 agent 的角色、權限、交接、稽核紀錄與人類 review 點寫清楚,讓 AI 工作不是一次性 demo,而是能被日常接住的流程。Define agent roles, permissions, handoffs, audit trails, and human review points so AI work is not a one-off demo, but a workflow daily operations can absorb.
AI 工具與廠商評估AI tool and vendor evaluation
協助團隊把 AI 解決方案放回自己的資料、流程、權限與預算條件裡比較,避免只看 demo 效果就做採購決策。Help teams compare AI solutions against their own data, workflows, permission model, and budget conditions, instead of buying from the demo alone.
AI 開發避險與技術檢核AI development risk review
協助新創與產品團隊判斷哪些情境適合用 Vibe Coding 快速試錯,哪些只要牽涉金流、資安、資料品質或長期維護,就必須設下工程檢核點。Help startup and product teams decide where vibe coding is useful for rapid experiments, and where payments, security, data quality, or long-term maintenance require explicit engineering review points.
AI 治理與 TAEA 導入AI governance and TAEA adoption
把 Transparent、Auditable、Explainable、Agentic 四個原則,轉成角色分工、紀錄格式、升級規則與定期 review 節奏。Turn Transparent, Auditable, Explainable, and Agentic principles into role design, record formats, escalation rules, and regular review cadence.
Vibe Coding 工作坊Vibe-coding workshops
帶非工程團隊用 AI 做出小型可運作原型,同時練習怎麼描述需求、檢查輸出、判斷風險與交接給工程或營運 owner。Guide non-engineering teams to build small working prototypes with AI while practicing requirements, output review, risk judgment, and handoff to engineering or operations owners.