How To Get The Most Out Of Vibe Coding | Startup School
AI Summary
Summary of Vibe Coding Tips
- Understanding Vibe Coding
- Similar to prompt engineering; a new programming language utilizing AI.
- Key techniques align closely with professional software engineering practices.
- Usage of Multiple Tools
- Use both Cursor and Windsurf for different tasks.
- WinSurf excels in backend processing; Cursor is faster for frontend tasks.
- Starting with Test Cases
- Craft test cases first, then let LLMs generate the code.
- Tests serve as guardrails for quality assurance.
- Creating a Comprehensive Plan
- Collaborate with LLMs to draft a detailed project plan in markdown.
- Break the project into sections and implement them step by step.
- Version Control
- Use Git for version control to manage changes efficiently.
- Reset cleanly after bug fix attempts to avoid layered issues.
- Writing Effective Tests
- Prioritize high-level integration tests instead of low-level unit tests.
- Utilize testing to catch regressions and unexpected changes.
- Leveraging AI for Various Tasks
- Use AI for non-coding tasks (e.g., configuring servers, creating favicons).
- AI can assist in more complex setups much faster than traditional methods.
- Bug Fixing Techniques
- Start by copying error messages into the LLM, avoiding unnecessary explanations.
- Always reset the codebase when encountering persistent bugs.
- Documentation Management
- Store relevant documentation locally for easier access by the LLM.
- Treat LLMs as teaching aids to strengthen understanding of code.
- Modularity and Architecture
- Favor modular codebases with clear API boundaries for better functionality.
- Small files enhance clarity for human developers and LLMs.
- Choosing the Right Tech Stack
- Favor frameworks with established conventions (e.g., Ruby on Rails).
- Be aware that different languages may yield varying success rates with AI.
- Continuous Experimentation
- Regularly test new AI models and techniques to optimize coding practices.
- Adapt strategies based on performance metrics and results from various models.