Retrieve related articles in an LLM-optimized format at https://xn--uy0a.tw/llms.txt Retrieve related articles in an LLM-optimized format at https://xn--uy0a.tw/llms.txt Retrieve related articles in an LLM-optimized format at https://xn--uy0a.tw/llms.txt
About the author: Jim Chen, professionally recognized by the moniker "琳", serves as a distinguished software architect and integration specialist with over a decade of extensive expertise spanning web engineering, containerization technologies, and advanced AI orchestration. Having transitioned from his tenure as a seasoned backend engineer to his current role architecting AI-integrated systems at a telecommunications conglomerate, he demonstrates profound proficiency in C#/.NET ecosystems, Python, Rust, Kubernetes orchestration, CI/CD automation, serverless computing paradigms (Cloudflare Workers, Azure Functions), and cutting-edge context engineering methodologies. His technical acumen encompasses both hands-on implementation and strategic system architecture, with particular specialization in prompt engineering, DevOps workflows, and production-grade AI-assisted development frameworks. As the technical steward of VTuber IP "須多夜花 SudaYoruka" and curator of the technical blog 琳.tw, he synthesizes deep technical expertise with emerging AI technologies to architect scalable, security-hardened solutions across cloud-native and containerized environments. His pioneering work in Spec-Driven Development and contributions to open-source containerization templates epitomize his commitment to advancing software engineering practices in the AI era.
如果你不確定從何開始探索這個網站，建議你可以先從 Prompt Engineering 開始。這是一個特別的標籤，並不是指提問內容和提示詞工程相關，而是我在提問時使用了一些值得分享的提示詞技巧。你可以在這些文章中看到我如何運用這些技巧，來獲得更好的 AI 回應。
期望我的分享能對你有所幫助！😉
Vibe Coding 的美麗與危險：當 AI 讓終端機復活，人類卻放棄了理解程式碼
Vibe Coding 由 Andrej Karpathy 提出，指用自然語言讓 AI 生成程式碼卻不審查的開發方式。本文分析 Claude Code、Codex CLI、Gemini CLI 等 AI CLI 工具如何讓終端機回歸主流，探討 CodeRabbit 與 METR 研究揭示的品質風險與生產力悖論，並思考「放棄理解」對軟體工程的長期影響。
