退隐3年后回归，周末写的AI一夜刷屏、一周拿下10万Star增速超Linux，Clawdbot之父首次长谈：如今几乎不看自己发布的代码

Core Insights - The article discusses the rapid rise of OpenClaw, a personal AI assistant project developed by Peter Steinberger, which gained significant traction in the developer community within a short period [3][8][10] - The project has undergone several name changes, initially starting as WhatsApp Relay, then Clawdbot, and finally settling on OpenClaw after facing legal challenges [5][10] - Steinberger's development approach leverages AI tools, allowing him to code at a pace comparable to a full team, raising questions about the future of software development and the role of AI in it [11][12] Group 1 - OpenClaw quickly became popular, achieving 100,000 stars on GitHub and 22,000 forks, surpassing established projects like Linux kernel, Vue, and React [1][3] - The project was primarily developed by a single individual, Peter Steinberger, who previously created PSPDFKit, a widely used PDF development tool [8][9] - Steinberger returned to development after a three-year hiatus, utilizing advanced AI models to enhance his coding efficiency, submitting over 600 code changes in January alone [10][12] Group 2 - The article features an interview with Steinberger, where he shares insights on his coding practices and the impact of AI on software engineering [11] - He emphasizes that traditional code review processes are outdated, suggesting that pull requests should be viewed as "prompt requests" in the context of AI-assisted development [12] - Steinberger's experience highlights a shift in software development dynamics, where AI tools enable developers to focus more on architecture and less on mundane coding tasks [56][62] Group 3 - The article outlines Steinberger's journey from creating PSPDFKit to developing OpenClaw, detailing his early experiences with programming and the evolution of his career [19][30] - It discusses the challenges he faced while transitioning from a traditional coding environment to one enhanced by AI, noting the importance of understanding AI's capabilities and limitations [75][78] - Steinberger's perspective on the future of coding suggests a blend of human creativity and AI efficiency, where developers can leverage AI to streamline processes and enhance productivity [62][68]