AI strategy & data scienceAI 策略與資料科學
Specializing in data science and AI consulting, I adhere to one core principle: every model must be built to drive tangible business decisions. Currently writing about AI strategy, data science project, and technical team leadership.專注於資料科學與 AI 顧問服務，我始終堅持一個核心：每一個模型都必須為了驅動實質的商業決策而生。這裡記錄了我對 AI 策略、資料科學專案評估方法與技術團隊領導實務。
A practical guide to designing and evaluating RAG through a LangChain complaint-triage case study—and deciding why the prototype is suitable for a controlled analyst-assistance pilot, but not autonomous deployment.本文透過一個以 LangChain 建構的申訴分流案例，說明如何設計與評估 RAG 系統，以及為何這項原型適合進入受控的分析師輔助試點，卻尚不足以支援自主部署。
38 min read閱讀約 66 分鐘
A practical guide to supervised fine-tuning, PEFT, LoRA, and QLoRA—covering dataset design, loss masking, leakage-resistant evaluation, and a hands-on experiment with SEC 10-K risk disclosures.一份關於監督式微調、PEFT、LoRA 與 QLoRA 的實用指南，涵蓋資料集設計、損失遮罩、可防資料外洩的評估方法，以及一項以 SEC 10-K 風險揭露為題的實作實驗。
23 min read閱讀約 44 分鐘
How do you serve 10,000 concurrent users? A deep dive into continuous batching, disaggregated prefill architectures, and multi-GPU parallelism to meet strict Service-Level Objectives in production, plus a troubleshooting quick-reference.要如何同時服務一萬名並發使用者？本文深入探討連續批次處理、分離式預填充架構，以及多 GPU 平行化，說明如何在正式環境中達成嚴格的服務等級目標，並附上疑難排解快速參考。
16 min read閱讀約 24 分鐘
Designed the retrieval, model-selection, and evaluation layers of a RAG system that helped managers identify evidence-backed candidates across an 8,000-person consultancy.設計 RAG (檢索增強生成) 系統的檢索、模型選擇與評估層，協助專案經理在一家擁有 8,000 名員工的顧問公司中，找出最合適人選。
Global Consultancy · AI Engineer · 2024-2025跨國顧問公司 · AI 工程師 · 2024-2025
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Built and shipped a production monitoring system from an undefined brief with no labelled data — later named “Best AML/CFT Data, Analytics & Visualisation Solution” at the Regulation Asia Awards for Excellence 2023.在需求未明、亦無標註資料的情況下，打造一套正式運作的交易監控系統，其後在《2023 Regulation Asia Awards》中榮獲「最佳洗錢防制/打擊資恐 (AML/CFT) 數據、分析與視覺化解決方案」獎項。
Financial Institution · Lead Data Scientist & Full-Stack Developer · 2022-2025金融機構 · 首席資料科學家暨全端工程師 · 2022-2025
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Need clarity on where AI can create real value — and what is actually worth building?想釐清 AI 能在哪裡創造實際價值，以及哪些方案真正值得投入嗎？
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