IDE消亡之年？Steve Yegge两句狠话：2026年还用IDE就不行，每天烧500~1000美元Token才合理

Core Viewpoint - The traditional IDEs may become obsolete by 2026, as engineers who do not adapt to new AI development methods will fall behind in productivity and competitiveness [1][5]. Group 1: Future of Development Tools - The transition from traditional IDEs to new AI-driven development tools is likened to moving from handheld tools to CNC machines, emphasizing the need for precision and automation in coding [2][11]. - Current AI models are inefficient, akin to sending a single diver into a vast codebase, suggesting a need for multiple specialized roles to enhance productivity [3][19]. - The future of software development will involve task decomposition, gradual refinement, and collaboration among multiple intelligent agents rather than relying on a single AI model [22][24]. Group 2: Productivity Disparities - There is a significant productivity gap among engineers, with those using AI tools like Codex potentially being ten times more productive than their peers who do not [5][27]. - Management is concerned about the implications of this productivity divide, fearing that they may need to reduce their workforce by up to 50% if engineers do not adapt [5][27]. - The situation mirrors the decline of the Swiss watch industry, where traditional craftsmanship was rapidly overtaken by quartz technology [8]. Group 3: New Development Paradigms - The concept of "Vibe coding" is introduced, where coding is driven by dialogue and AI-generated outputs, moving away from traditional manual coding practices [29][35]. - The economic implications of Vibe coding are significant, allowing for more modular and experimental approaches to development, thus increasing the value of options available to teams [38]. - Examples from companies like Travelopia and Capital One illustrate how AI-driven development can drastically reduce the time and resources needed for project completion [41][49]. Group 4: Organizational Transformation - The integration of AI tools is reshaping technical organizations, enabling non-developers to contribute to coding and deployment processes, thus democratizing software development [44][47]. - Trust in AI increases with usage, suggesting that engineers need to practice and engage with these tools to fully leverage their capabilities [42]. - The rapid pace of code submission and the ability to resolve legacy system issues with AI-generated solutions indicate a transformative shift in how teams operate [49].