分析AI学习者的四道流失阶梯，提出用工程化平台消除配置、实验、部署等摩擦，让学员专注于核心技能练习。介绍AI Builder Space如何通过统一API、一键部署和MCP自动化实现这一目标。
Why AI Education Should Go Beyond Content Creation to Engineering Infrastructure
Analyzes the four-step attrition ladder in AI learning and proposes using engineering platforms to eliminate configuration, experimentation, and deployment friction. Introduces AI Builder Space's unified API, one-click deployment, and MCP automation.
使用Nano Banana Pro生成整套PPT：疯狂，挑战和工作流
从拼凑到整体渲染的PPT制作范式转移，以及如何用代码骨架、资产约束和延迟渲染构建解决风格混乱、幻觉和成本问题的Generative Kernel。
Generating Entire Slide Decks with Nano Banana Pro: The Madness, The Challenges, and The Workflow
Exploring the paradigm shift from assembling slides to holistic rendering with NBP, and building a Generative Kernel workflow to handle visual consistency, hallucination, and cost.
当AI陷入鬼打墙：一次关于协作策略的复盘
记录通过迭代式问题解决开发自动截图功能的经历。关键经验：优化问题定义而非仅优化提示词、从"最小可行真相"出发锚定工作流、根据任务需求匹配合适的AI模型能力边界。