AI Coding使用Tips与使用心得分享[匠说Vol.6]

随着“AI Coding”与 **Vibe Coding** 越来越成为开发者日常工作的一部分，传统的“逐行写代码”已经逐步向“用 AI 快速把想法跑起来、迭代再迭代”的新模式升级。本次 **匠人学院（JR Academy）** 举办的线上研讨会 **《匠说Vol.6：Vibe Coding 实用技巧与使用心得分享》**，集中呈现了真实工程师在 AI Coding 实践中的经验、技巧与踩坑复盘。活动由多位来自行业一线的工程师与技术领袖共同对谈，围绕如何更高效、更可控地将 AI 辅助编程融入实际开发展开深入讨论。 本次研讨会不仅探讨 **Vibe Coding 在不同场景下的最佳实践**，例如新功能开发、修复 Bug、重构老项目、编写测试、做 PoC（概念验证）与搭建脚手架等，还着重分析了 AI Coding 工作流的构建方式，如 IDE/插件/终端/PR 流程之间如何协同，以及如何在AI生成代码后保证结构合理、可维护和可上线。嘉宾们还分享了如何写好需求与上下文，使 AI 不会产生“幻觉代码”、如何避免常见的翻车模式（如误改、隐性 Bug、依赖混乱与安全风险），以及在团队协作中如何保持代码质量、责任边界与 review 流程。 活动阵容包括匠人学院创始人 Lightman Wang、多位资深软件工程师和 AI 工程实践者，他们从工程师实际使用角度出发，带来一场以经验分享为核心的圆桌式讨论。此次活动特别适合正在使用或准备开始使用 AI Coding 的开发者、Tech Lead/Senior 工程师、技术管理者，以及想了解真实一线工程师如何用 AI 写代码、如何避坑并转化为生产力的技术学习者。参与本次分享，你将带走一套**可复用的 AI Coding 工作流**、一份**真实的踩坑地图**，以及对“哪些任务适合用 AI 加速、哪些必须依靠基本功”的稳健判断。 As AI-assisted development becomes an increasingly integral part of modern software engineering, the paradigm of “writing line-by-line code” is evolving into a more dynamic workflow where AI tools help developers rapidly prototype, iterate, and refine ideas. The online seminar **“CraftTalk Vol.6: Practical Vibe Coding Tips & Experience Sharing”** hosted by **JR Academy** brings together seasoned engineers and industry practitioners to share real-world insights, tips, and lessons learned from practicing *AI Coding* and *Vibe Coding* in real projects. This session delves into practical applications and strategies for integrating AI into the development process. Rather than focusing on abstract theory, the discussion highlights concrete use cases such as accelerating new feature builds, fixing bugs, restructuring legacy systems, writing tests, performing proofs of concept, and generating scaffolding code with AI assistance. A key part of the talk explores how to build effective AI Coding workflows — from IDE and developer plugins to terminal tools and Pull Request processes — in ways that minimize context switching and maximize productivity. Participants also learn how to craft clear requirements and contextual prompts so that AI outputs remain reliable and useful rather than producing “hallucinated” or flawed code. Additionally, veteran developers share their experiences with common pitfalls — including unintended code changes, subtle bugs, dependency chaos, and security vulnerabilities — and how to anticipate and mitigate these risks. Of particular importance in collaborative environments, the seminar examines how teams can maintain consistency, uphold code quality standards, and define clear ownership and review responsibilities when multiple contributors interact with AI-generated content. Featuring insights from Lightman Wang (Founder of JR Academy) and a panel of senior developers and AI engineers, this event offers an interactive, experience-driven roundtable format. It is ideal for engineers already using or planning to adopt AI Coding tools, technical leads and senior engineers concerned with maintainability and review overhead, and students or career changers who want to understand *how professional developers really use AI* — beyond simple tutorials. Attendees will take away a **reusable AI Coding workflow**, a **practical risk map** of common pitfalls, and a grounded understanding of *which tasks AI accelerates and which require traditional engineering fundamentals*.