Vibe Coding Tutorial and Best Practices (Cursor / Windsurf)

1. Vibe coding utilizes AI for efficient coding.

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Vibe coding, or agentic coding, leverages AI agents to automate coding tasks, significantly reducing the need for manual code writing.

• This method allows for the creation of entire applications with minimal human input.
• Using tools like Cursor or Wind Surf enhances the coding experience.
• AI can assist in generating specifications and code structures.

2. Setting up AI models is crucial for effective coding.

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Choosing the right AI model, such as CLA 3.7, is essential for supporting agentic behavior and function calling in coding tasks.

• Cursor and Wind Surf allow customization of models to fit specific needs.
• Models must support agentic behavior for optimal performance.
• Using a well-suited model can prevent coding errors and inefficiencies.

3. Establishing coding rules enhances project management.

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Implementing specific coding rules helps guide AI behavior and maintain project consistency, especially in larger codebases.

• Rules can dictate technology usage and coding workflows.
• Clear rules prevent the AI from introducing unwanted changes or technologies.
• Maintaining a clean codebase is essential for long-term project success.

4. Testing and refactoring are vital in AI-assisted coding.

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Regular testing and refactoring of code are necessary to ensure functionality and maintainability when using AI coding agents.

• End-to-end testing is preferred over unit tests for real-world application scenarios.
• Refactoring should occur before code files exceed manageable sizes.
• Avoiding mock data in production environments is crucial for accurate results.

5. Managing context is key for AI performance.

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Providing the right amount of context to the AI is essential for maintaining its performance and effectiveness in coding tasks.

• Too much context can hinder the AI's ability to perform well.
• Starting new chats can help manage context but may require reintroducing important information.
• Balancing context is a skill that improves with practice.

6. Always monitor test results closely during development.

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When tests fail, it's essential to fix them carefully to avoid unintended impacts on production code.

• Fixing tests can sometimes lead to changes that don't align with expected functionality.
• Use integration tests or manual checks to ensure everything works as intended.
• Keep an eye on the context of changes to avoid bloating the context window.

7. Choose popular technology stacks for better AI performance.

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Using widely adopted stacks like Python, HTML, and JavaScript enhances AI's ability to assist in coding.

• Common stacks have more documentation available for AI to reference.
• Less popular technologies may not yield optimal AI performance.
• SQL and Elastic Search are recommended for database and search functionalities.

8. Utilize version control and commit changes frequently.

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Regular commits allow for easy rollback and better management of code changes.

• Versioning through tools like Cursor or Windsurf helps maintain a history of changes.
• Rolling back to previous states can save time and effort in case of issues.
• Frequent commits ensure that you can recover from unfixable states.