在疫情结束后的 2023 年，经济并没有像人们预期的那样迅速复苏。所以，在 2023 年里，我并没有立下太多的 flag，只是在持续的实践与创造中度过了一年。
在过去的一年里，我大量的时间都花费在了 AI 辅助研发的调研、方案与落地实践上：
在 2024 年年底，终于将我之前想跟随的自定义多文件编辑功能发布了。在最新的版本里，你可以体验一系列的 AI IDE 智能体特性：
在经过多个项目上的试用后，我们进入了持续的修修补补，以及功能的增强阶段。终于，我们发布了 Shire 1.1 版本，这个版本带来了更强大的交互支持，
两周前受彭鑫老师邀请，在《智能化软件开发微访谈·第三十四期 基于大模型的软件智能化开发实践》分享了我们在 Thoughtworks
TL;DR：我们试验了将 AI 应用到基于 Protobuf 的微服务架构中，基于 ArchGuard 治理平台、Shire AI 助手、Team AI 三个工具中，构建了一套完整的
随着AI技术在软件开发中的普及，开发人员的角色正在从单一技术专家逐渐转向“超级个体”——即具备跨界、创新和自我迭代能力的多面手。生成式AI不仅简化了传统开发流程，更通过不断迭代的反馈机制让开发人员掌握新技术栈、快速适应需求变化，并能将复杂的业务知识融入代码。本文结合生成式AI的实践场景，解析如何高效运用AI辅助工具并适应技术转型。
流式 BFF（Streaming Backend for Frontend） 是一种适用于 AI 原生架构的后端模式，旨在解决智能体协同过程中的数据流处理和接口不一致问题。
年初，我们注意到国内几大 AI 辅助编程工具，通过提供礼品和购物卡等推广手段，迅速引起了众多开发者的关注和使用。这种市场变化逐渐影响了我们开源
- 2024 节点：在持续变化的环境中寻找竞争力
- 我的 2024 一线落地 AI 辅助研发的实践心得：从工程、工具到未来展望
- 智能体语言 Shire 1.2 发布：自定义多文件编辑、Sketch 视图、流式 diff、智能上下文感知
- Shire 1.1 发布：更强大的交互支持，升级 AI 智能体与 IDE 的整合体验
- ArchGuard 架构分析器发布：多语言、跨项目架构感知，助力 AI 生成知识
- AI 辅助研发的 2024 年的 6 个实践感受与思考
- 架构赋能 AI：知识工程推动下的架构数智化
- 成为超级个体：AI时代的研发人员编程技巧最佳实践
- 流式 BFF：LLM 优先架构下的智能体胶水层
- 可编排 AI 编程助手 Shire 1.0 发布：一键连接工具生态，重塑软件开发流程
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