Zero-Coding Development with Cursor? Think Again! 15 Practical Tips to Avoid Pitfalls with Cursor AI

Author: Axton
Original Link: Original Link

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1. Core Features and Limitations of Cursor

1.1 Composer: Project Framework Generator

Cursor's Composer feature is a revolutionary innovation that can automatically generate an entire project framework based on user requirements. For example, when you tell Composer you need to create a web application that uses the OpenAI API to translate SRT subtitle files and deploy it on Vercel, it will select the most suitable technical architecture and automatically create the necessary directories and files.

However, Composer also has some notable limitations:

• Conversation history is not saved: This is one of the most frustrating issues. When you exit Cursor, all conversations in Composer are cleared. Although the Composer window has a "Show History" feature, this history only exists during Cursor's runtime. Therefore, if there is important conversation content, you need to manually copy and save it to another note-taking app.
• File updates may be interrupted: Sometimes, due to network issues or language model limitations, Composer may stop halfway through updating files. In such cases, never click "Accept All," as this may replace the original files with corrupted ones.
• File retrieval issues: Composer occasionally fails to retrieve files. For example, it might say, "If your project has an app.py file, you need to modify it like this..." In such cases, you must explicitly confirm that the file exists in the project and request Composer to make the changes directly.

1.2 Advantages and Considerations for AI Conversations

Cursor's AI conversation feature allows users to interact with the AI assistant using natural language, significantly improving programming efficiency. However, there are a few points to keep in mind:

• Use "Apply" and "Accept" with caution: Do not rush to accept all of the AI's suggestions. Even if you don't understand the code, carefully review what Cursor plans to modify. The AI may inadvertently delete or simplify important code logic, especially custom prompts.
• Context loss: After several lengthy conversations, Cursor may lose context. For example, it might forget previously discussed translation strategies and suggest a completely different approach. In such cases, timely reminders and corrections are necessary.
• Model selection: Cursor may sometimes switch to GPT-4 without your explicit consent, even if you specified another model. This can affect performance and incur unnecessary costs.

2. Tips for Using Cursor Efficiently

2.1 The Importance of Task Decomposition

When developing complex applications with Cursor, task decomposition is a critical strategy. Breaking down large tasks into smaller, more manageable parts offers the following benefits:

• Improved accuracy: AI performs better with smaller, more specific tasks.
• Easier review: Smaller changes are easier to inspect and understand.
• Reduced risk of errors: If issues arise, their impact is limited and easier to fix.

For example, when developing a subtitle translation application, you can focus on completing the frontend interface first before tackling backend logic. Alternatively, implement basic translation functionality before adding advanced features like timestamp alignment.

2.2 Using @web to Fetch the Latest Information

AI models are typically trained on data that is several months old, which can lead to outdated information in fast-evolving technical fields. Cursor provides the @web command, allowing the AI to retrieve the latest online documentation before completing a task.

Usage: Include @web in your instructions, for example: "@web Please check the latest Vercel Blob documentation to ensure your code complies with the most recent API specifications."

This way, Cursor will search for the latest relevant information online, significantly improving code accuracy and timeliness.

2.3 Version Control and Backup

When developing with Cursor, version control and backups are essential. Here are some recommendations:

• Use Git: Commit your changes regularly so you can roll back to previous versions if needed.
• Local backups: For important code snippets, especially custom prompts, periodically copy them to local files.
• Branch development: Before attempting major changes, create a new branch to experiment safely without affecting the main codebase.

Remember, while AI is powerful, it is not infallible. It may accidentally delete or modify critical code, so maintaining vigilance and backup habits is crucial.

3. Applying Cursor in Real-World Projects

3.1 Case Study: Subtitle Translation Application

Using Cursor, I successfully developed a web application for subtitle translation. This project showcased Cursor's capabilities while also revealing some limitations.

Application features:

• Supports multilingual translation
• Uses the Gemini 1.5 Flash model
• Deployed on Streamlit Cloud

Key points during development:

• Model selection: Initially planned to use GPT-4 but ultimately chose Gemini 1.5 Flash due to cost considerations. This decision highlights the need to balance performance and cost in AI development.
• Translation strategy: The original plan was to translate entire paragraphs first and then align them with timestamps. However, during development, this method proved difficult for accurate timestamp alignment, so it was simplified to sentence-by-sentence translation.
• Performance optimization: During testing, a severe performance issue was discovered—a single run consumed 440,000 tokens. Code review revealed that Cursor-generated code was maintaining a history of all translations rather than just the current session. This case underscores the importance of understanding and optimizing AI-generated code.

3.2 Possibilities and Challenges for Non-Programmers Using Cursor

While Cursor significantly lowers the barrier to programming, developing complex applications solely with Cursor remains challenging for those without programming experience:

• Code understanding: Even without writing code, understanding code logic is necessary, which can be a significant hurdle for non-programmers.
• Problem diagnosis: When AI-generated code encounters issues, non-programmers may struggle to identify and resolve them.
• Performance optimization: As shown in the subtitle translation case, optimizing AI-generated code requires some programming knowledge.
• Architecture design: While Cursor can generate basic frameworks, optimizing the overall architecture still requires expertise.

That said, non-programmers can still leverage Cursor for simple tasks like creating basic web pages or simple data processing scripts. The key is recognizing the tool's limitations and seeking professional help when necessary.

4. Best Practices for Using Cursor

4.1 Tips for Improving AI Interaction Efficiency

• Clear and specific instructions: The more specific your instructions to Cursor, the more accurate the results. For example, instead of saying, "Optimize this code," say, "Optimize this code to reduce API calls."
• Step-by-step questioning: Break complex tasks into smaller steps. Review the results after each step before proceeding.
• Leverage context: In long conversations, frequently remind the AI of previously discussed points to maintain context coherence.
• Learn to reject: When Cursor's suggestions are unsuitable, reject them explicitly and explain why. This helps the AI better understand your needs.

4.2 Code Review and Optimization

Even AI-generated code requires careful review and optimization:

• Line-by-line inspection: Pay special attention to parts modified or deleted by the AI to ensure critical logic remains intact.
• Test-driven development: Write unit tests for AI-generated code to verify functionality.
• Performance analysis: Use profiling tools to check code efficiency, especially when handling large datasets or frequent API calls.
• Code refactoring: AI-generated code may lack elegance, so consider refactoring for better readability and maintainability.

4.3 Continuous Learning and Adaptation

Cursor and other AI programming tools are evolving rapidly, so continuous learning and adaptation are essential:

• Stay updated: Regularly check Cursor's release notes for new features and improvements.
• Join the community: Participate in Cursor user communities to share experiences and learn from others.
• Practice relentlessly: Only through constant practice can you truly master Cursor's features and best practices.
• Combine traditional programming: Do not rely solely on AI. Continue learning and improving traditional programming skills to better understand and optimize AI-generated code.

5. Conclusion and Outlook

As a powerful AI-assisted programming tool, Cursor undoubtedly opens new possibilities for developers and non-developers alike. It significantly improves programming efficiency, especially for repetitive tasks and generating basic code structures. However, we must also recognize its limitations.

For experienced programmers, Cursor can be a valuable assistant, accelerating development but not entirely replacing human creativity and problem-solving skills. For non-programmers, Cursor lowers the barrier to entry, making simple applications possible, but developing complex, production-grade applications remains challenging.

Looking ahead, we can expect further advancements in AI programming tools:

• Stronger context understanding to reduce information loss.
• More precise code generation to minimize manual intervention.
• Better project management integration to support the entire workflow from requirements analysis to deployment.
• Enhanced natural language processing to make the tool more accessible to non-programmers.

Regardless, AI programming tools are reshaping the landscape of software development. By mastering the tips and best practices outlined in this article, you can better harness tools like Cursor and stay ahead in the wave of AI-assisted development.

Remember, no matter how powerful the tool, it is still just a tool. The real value lies in the creativity and judgment of the person using it. Let us embrace the opportunities AI brings while continually enhancing our core competencies.