Developers Ditch AI Tools, Return to VS Code for Reliability

In the dynamic landscape of software development, a notable trend is emerging: developers are increasingly returning to Microsoft's Visual Studio Code (VS Code), often moving away from newer, AI-first coding tools like Cursor. This shift is primarily driven by VS Code's relentless evolution in features and reliability, coupled with a more nuanced understanding of AI coding tools' practical limitations.

For years, Visual Studio Code has maintained its position as a dominant and highly favored code editor, celebrated for its robust performance, cross-platform compatibility, and an exceptionally rich ecosystem of extensions. Its intuitive user interface, powerful editing features like IntelliSense for code completion, integrated debugging, and seamless Git integration have made it an indispensable tool for developers across various programming languages. The platform's continuous improvement model, with monthly updates and an active community, ensures it remains at the forefront of developer needs.

While AI-centric editors like Cursor initially captured significant attention by promising a revolution in coding productivity through deep AI integration, their adoption has faced challenges. Cursor, built upon VS Code's open-source foundation, aimed to provide an AI-first experience with features such as inline AI chat, natural language refactoring, and bug fixing. However, reports from 2025 indicate a growing backlash among users, citing performance issues, particularly with larger codebases where UI lag, increased crashes, and memory leaks have been observed. Concerns have also been raised regarding its pricing model, which some developers find less competitive compared to the combination of VS Code and AI extensions like GitHub Copilot. Furthermore, issues like the AI "refusing" to generate code or exhibiting "undesirable" edits have eroded trust and highlighted the limitations of AI in handling complex or nuanced tasks. Compatibility quirks with Linux and less effective support for specific workflows, such as Jupyter Notebooks, have further contributed to developer dissatisfaction.

Conversely, VS Code has not only maintained its core strengths but has also aggressively integrated sophisticated AI capabilities, often surpassing the practical utility offered by specialized AI editors. Recent updates in 2025 have introduced a native AI assistant, powered by GitHub Copilot and VS IntelliCode, providing inline code suggestions, natural language-to-code commands, and advanced refactoring tips directly within the editor. The "AI Toolkit for Visual Studio Code" extension offers a comprehensive environment for building and testing generative AI applications, supporting various models and streamlining AI development workflows. Features like "Agent Mode" enable Copilot to autonomously complete complex tasks, while "Copilot Vision" allows interaction with images in chat prompts, and "Next Edit Suggestions" predict developers' next coding actions. These enhancements, coupled with robust remote development capabilities that seamlessly integrate AI, mean that developers can leverage powerful AI assistance without sacrificing the stability, customization, and vast extension ecosystem that VS Code offers.

This trend aligns with broader developer sentiment regarding AI tools. The 2025 Stack Overflow Developer Survey indicates a paradox: while AI tool usage has increased, overall positive sentiment and trust in their accuracy have declined. A significant portion of developers report frustrations with AI solutions that are "almost right, but not quite," leading to time-consuming debugging of AI-generated code. This suggests that while AI is valued as a starting point, developers increasingly recognize the need for human verification and the limitations of AI in complex problem-solving.

In conclusion, the quiet return of developers to Visual Studio Code underscores a preference for reliable, feature-rich, and customizable environments. VS Code's ability to seamlessly integrate advanced AI features while maintaining its core strengths has made it a more compelling choice than dedicated AI coding tools that, despite initial promise, have struggled with performance, reliability, and cost-effectiveness in real-world development scenarios. As the industry matures, the emphasis appears to be shifting from "AI-first" to "AI-integrated," where AI serves as a powerful enhancement within a stable and trusted development platform.