原文:
"Like 'AI Coding Agents' such as Claude Code and Codex, which can deliver high-quality code is not new. But what are the real changes that this brings to software development? Silicon Valley top venture capital firm Andreessen Horowitz (a16z) recently published an article: 《Value of $Trillion in New "Battlefield" for AI-Driven Software Development》(The Trillion Dollar AI Software Development Stack). The focus of the article isn't on just using AI."
Image Description:
The image illustrates the process flowchart of AI-driven software development, highlighting how various roles interact with tools powered by humans or artificial intelligence throughout different stages:
Key Components:
Users → Aggregate Feedback
- Users provide feedback collected through platforms like Nexoro.
PM & Architecture
- Product Managers break down specifications into detailed stories and architecture plans.
Planning & Architecture Tools
- Platforms like Traycer assist in planning tasks based on user requirements.
High-Level Specification/Wiki/Jira
- High-level documentation stored here guides project progress.
Detailed Spec/Architecture/UI Design Tool
- Detailed specification documents created alongside UI design assets managed via Figma-like tools.
Prototype UI/Applications
- Early-stage prototypes developed before full-scale coding begins; Lovable might be used at this stage.
Software Engineer Workflow
- Engineers use IDEs/Cursors along with Agentic Devins during PR processes where Graphite or similar review systems come into play ensuring quality control over pull requests.
QA Engineering Role Integration w/AI Support Systems Like QAIDE Or AGENTIC
**Documentation Editors Utilizing Guidelines From Human Experts And Reviewers With Assistance Of AIDOC/MINTIFY TOOLS FOR USER DOCS AND API DOCUMENTATION RESPECTIVELY .COMPLIANCEDOCS GENERATED BY DELVE PROVIDE COMPREHENSIVE GUIDANCE ON REGULATORY REQUIREMENTS WHILE ITSECURITYANDCOMPILANCETOOLOFFERS ADDITIONAL SECURITY MEASURES INTEGRATED INTO THE DEVELOPMENT CYCLE .
中文:
类似Claude Code和Codex这样的“AIGC编码代理(AI Coding Agent)”能够生成高质量代码,并不算是什么新鲜事物。但它们到底会给软件开发带来什么样的实质性变革呢?最近,硅谷顶级风险投资公司AndreeseenHorowitz(a16z),发布了一份名为《万亿美元规模的人工智能驱动型软件开发生态系统(TheTrioDollarAISoftwareDevelopmentStack)的文章重点并不是单纯地讨论如何使用人工智能。

该图表展示了由人工智能力量推动下的整个软体研发流程中各个角色之间的互动以及他们使用的各种工具在不同阶段中的作用如下所示 :
关键组成部分 :
- 用户反馈收集平台如NexoRo等接收用户提供的聚合性意见。
- PM与架构师通过分解需求规格书并提出问题来制定详细的故事线及体系结构计划 , 并借助于诸如TraYceR之类的规划管理器完成任务分配等工作 .
- 高层次规范文档存储库例如Wiki或JIRA用于指导项目进展过程 ; 同时还包含详细的说明文件和技术设计蓝图等内容以便后续参考查询之需 。此外还包括UI设计师团队负责制作原型界面应用程序的设计工作 ,其中可能涉及到Lovable这类产品帮助实现初步概念验证目的 ;
- 开发人员则会运用集成式开发环境(Cursor), 结合智能化辅助功能(Devin )来进行提交请求(PR ), 在此期间Graphit e或者其他审查机制介入确保拉取申请的质量符合标准要求; 最后是质量保证工程师(QAE ngineer s)参与到测试环节当中去执行自动化检测操作以保障最终产品的稳定性和可靠性水平达到预期目标值范围之内同时还有专门针对API接口调用情况编写相应技术手册供开发者查阅学习从而提升整体工作效率降低出错率的可能性等等措施共同构成了完整的闭环管理体系让每一个细节都得到了充分的关注照顾到位无遗漏之处存在任何潜在隐患的风险点被彻底消除掉之后才能够顺利进入下一阶段继续推进下去直至顺利完成所有预定工作任务为止 !
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