OpenCode 中文乱码彻底解决，一个插件搞定，附完整排查过程
用 AI 编程工具写代码，最怕的不是它写错，而是它“看不见”。
把 GitHub 网址改几个字母，再庞大的开源项目也能看懂
于是团队内部开发了 Devin Wiki 和 Devin Search 两套核心组件，专门用来帮 AI 快速吃透复杂项目。
OpenCode从入门到好用：基础用法+5个必装插件
之前写过几个 OpenCode 的插件，后台收藏比点赞多不少，评论里也有人问：插件到底往哪装？刚装好的 OpenCode 该怎么用？干脆整理成一篇。
《中国消费品企业如何通过高端化价值创新打破“内卷式”竞争》
分享兴趣，传播快乐，增长见闻，留下美好！亲爱的您，这里是LearningYard新学苑。
AI越能写，研究者越头疼？他们破解了AI编码“失真”难题
In social science research， grounded theory is widely adopted to analyze and code textual data. While large language models open new possibilities for coding at scale， they complicate the GT workflow by generating excessive codes and introducing hallucinations， posing challenges for experts to audit and revise the coding results. To address these challenges， we conducted a two-year design study and derived a series of domain needs and design tasks via interviews with scientists in entrepreneurial management. Subsequently， we presented PROVA-GT， a visual analytics system facilitating the GT workflow by supporting both the forward process of code generation and the backward process of validation and refinement， which are interconnected and iterative. Specifically， our system features a provenance workflow that leverages the agentic LLM and novel visual designs to assist experts in the backward process. To evaluate the usefulness of PROVA-GT and its generalizability in different domains， we reported two in-depth expert studies on entrepreneurial inspirations and trust erosion， respectively. We also conducted a user study to assess the effectiveness of the agentic workflow.
凭什么？美国模型突破是人类之光，中国模型出圈就被骂“蒸馏”？
Kimi K3.1 Pro刚一发布，圈内有些人比谁都忙，模型没来得及测，技术报告也没看，脏水先泼上来了:“肯定是靠蒸馏吧?”
Agent 路由模式详解：从意图识别到动态模型选择
上一篇介绍了 Prompt Chaining（提示链模式），通过将复杂任务拆分为多个职责明确的步骤，配合结构化输出、中间结果校验和局部重试，提高多阶段模型调用的可靠性。但在实际 Agent 应用中，并不是所有请求都适合采用相同的处理流程。
OpenIDEA介绍
OpenIDEA 开源项目完整介绍在Vibe Coding化的今天，使用效果极佳，占用内存极小。已经使用半个月了。