[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-llmops":3},{"tag":4,"articles":10},{"id":5,"name":6,"slug":7,"article_count":8,"description_zh":9,"description_en":9},"e9f42735-d72f-4077-95cf-a8a33b192508","LLMOps","llmops",0,null,[11],{"id":12,"slug":13,"title":14,"summary":15,"category":16,"image_url":17,"cover_image":17,"language":18,"created_at":19},"bf65e913-62a5-4ac6-bfdb-5d4dd7ab3527","mlops-in-2026-architecture-strategy-guide-zh","2026 年 MLOps 架構與策略指南","2026 年的 MLOps 重點在治理、LLMOps 整合與成本控制。企業已把 AI 放進 production，但多數還卡在試點到擴張的落差。","industry","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778610668465-auam.png","zh","2026-05-12T18:30:46.602039+00:00"]