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.
Choose AI coding tools based on their framework support - Bolt and v0 work better with React compared to Vue/Nuxt
Use AI tools to accelerate learning while actively developing coding skills
Start projects with generators like Bolt/v0 for scaffolding, then move to Cursor for detailed development
Don't use AI coding tools as a complete substitute for learning programming fundamentals
Avoid assuming AI generators can handle all aspects of complex projects
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.
A developer shares their positive experience switching from Sourcegraph's Cody to Cursor as their AI coding assistant. The user particularly highlights Cursor's superior code modification capabilities and well-designed interface, noting that it significantly improves their coding workflow compared to Cody's limitations with applying changes.
A developer shares their positive experience using new .mdc cursor/rules files for improved code generation in Convex projects. The implementation demonstrates significant improvement in one-shot code generation compared to previous methods, reducing the need for multiple prompts and showing enhanced effectiveness over traditional documentation-based approaches.
A software engineer and dev agency owner shares their experience using Cursor AI over two months, breaking down the strengths and limitations of three main features: Cursor Agents, Composer, and Chat. The post provides practical guidelines for when to use each feature effectively, based on real-world project implementation experience.
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.