A user experienced issues with Cursor AI making unauthorized code modifications beyond requested changes. In response, they developed a ruleset to constrain Cursor's behavior and prevent scope creep in code improvements.
Create a comprehensive ruleset for an AI coding assistant that: 1. Only makes changes explicitly requested by the user 2. Maintains scope boundaries during code modifications 3. Prevents unauthorized improvements or refactoring 4. Provides clear documentation of all changes made 5. Requests explicit confirmation for any suggested improvements beyond the original scope
Define clear boundaries and rules for AI-powered code modifications
Review and validate all AI-generated code changes before implementation
Allowing AI tools to make unrestricted changes to code without proper constraints
Failing to monitor and adjust AI tool behavior based on observed patterns
A developer discusses productivity challenges with Cursor's AI composer, specifically the context-switching issues during code generation wait times. The post highlights how brief AI inference delays can lead to workflow interruptions and distractions, similar to traditional compilation time issues but with more potential for distraction.
A detailed comparison of three major AI coding tools (Bolt, v0, and Cursor) based on hands-on experience. The analysis covers each tool's strengths, limitations, and ideal use cases, with particular focus on their applicability for different skill levels and project types. The post emphasizes the importance of actual coding skills while leveraging AI tools for enhanced productivity.
A developer shares their positive experience using Cursor AI for code generation, highlighting how it allows them to focus on higher-level architectural decisions rather than implementation details. The post discusses the balance between AI-assisted development and manual coding, emphasizing that while AI code generation might not be suitable for critical systems, it's highly effective for typical business applications.
A developer shares their experience using different AI coding assistants to debug a nested component styling issue. They found that AI Studio with Gemini Flash 2.0 was more effective at handling larger codebases compared to Cursor, resolving their issue in 6 seconds versus 30 minutes of unsuccessful attempts with Cursor.
User shares positive feedback about Haiku 3.5's integration with Cursor, highlighting its improved performance and effectiveness in GUI design and app development using Composer. The post emphasizes Haiku's focused approach compared to Claude's more creative tendencies, noting faster response times and shorter queues.