How to Prompt Cursor, Windsurf & Copilot to Get Reliable Output
AI Summary
Summary of AI Code Editors Workflow Improvement Video
Prompt Detail Level
- AI code editors work well for prototyping but struggle with complex codebases.
- Detailed prompts are crucial as the codebase grows and becomes more complex.
- Constraints like libraries, databases, and frameworks must be specified to guide the AI.
- Example: For adding a settings display, explicit file names had to be mentioned in the prompt.
- For authentication, specify the stack (e.g., Superbase), user info, and login types.
Task Size
- Task complexity should be inversely proportional to codebase complexity.
- Smaller tasks are recommended for complex codebases to manage context limits.
- Smaller tasks are easier to review and validate, similar to reviewing a GitHub PR.
Breaking Down Tasks
- Breaking down tasks into detailed specs is beneficial for clarity.
- Use advanced reasoning models like A1 to help with initial breakdowns.
- Example: Use VS Code with a subscription to get free prompts for task breakdown.
- A1 can generate a spec that can be tweaked for specific requirements.
Iterating on Prompts
- Avoid long sessions trying to fix prompts; it’s better to start a new session.
- If after multiple iterations the AI fails, the task might be too complex or the prompt unclear.
- For minor tweaks, it’s okay to continue with the existing context.
- For significant issues, start a new prompt session.
Language Choice
- Use typed languages for production projects for better AI assistance.
- Typescript is recommended due to its popularity and the quality of AI-generated code.
- Explicit types help AI produce higher quality and more accurate code.
Future of AI Coding
- In the future, AI may autonomously test and iterate on code, requiring different interaction strategies.
- Prompting strategies and mental frameworks are still critical for current AI coding tools.
Tools Mentioned
- VS Code with a subscription for task breakdown prompts.
- AI reasoning models like A1 for initial spec generation.
Final Thoughts
- The key to effective AI coding is providing better context through detailed prompts and task breakdowns.
- Typed languages like Typescript offer advantages in AI-assisted coding.
- Current strategies will evolve as AI coding tools become more autonomous.