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TRAE 如何思考 AI Coding :未来的 AI IDE,是构建真正的「AI 工程师」
Founder Park· 2025-06-25 10:19
Core Viewpoint - The article discusses the increasing interest and development in AI coding tools, emphasizing the evolution of programming languages and the potential of AI to transform software development processes [1][8][10]. Group 1: AI Coding Landscape - More players are entering the AI coding space, from low-code platforms for general users to IDEs for professional programmers [1][2]. - TRAE, as the first AI Native IDE in China, aims to integrate AI into the entire software development workflow, proposing an "AI + tools" model [3][5]. Group 2: Evolution of Programming Languages - The development of programming languages has been a process of abstraction and simplification, evolving from machine and assembly languages to high-level languages like C, Java, and Python [9][10]. - The number of global developers has grown exponentially, from around one million in the 1990s to over 100 million registered developers on GitHub by 2023 [10]. Group 3: TRAE's AI IDE Features - TRAE's AI IDE combines product, engineering, and model capabilities to enhance developer efficiency and foster innovation [11][13]. - The IDE features include code completion (referred to as "cue") and natural language programming, allowing developers to interact with AI in a conversational manner [17][19]. Group 4: User Experience and Adoption - TRAE has achieved over one million monthly active users and generated over 60 billion lines of code, indicating strong user engagement and adoption [24]. - The article highlights a case study of a non-technical product manager who successfully developed an app using various AI tools, showcasing the potential for AI to empower users without coding backgrounds [25][29]. Group 5: Future Development and Integration - The future vision for TRAE includes creating a unified workspace where AI can manage various tools and tasks, enhancing collaboration between users and AI [31][32]. - The company aims to evolve from "AI writing code" to "AI doing development," focusing on integrating tools into a cohesive AI-driven environment [32].