Streamlining Your Code with AI: A Deep Dive into Cursor's Capabilities
AI tools like Cursor are changing the way developers work. By automating mundane and repetitive tasks, they allow us to focus on the more interesting and creative parts of our job. The key is to understand how to prompt the AI effectively, providing it with the right context.
Introduction: Reclaim Your Time with AI-Powered Code Refactoring
Are you tired of spending countless hours on tedious, repetitive coding tasks? In this post, we'll explore how AI-powered tools, specifically Cursor, can revolutionize your development workflow. We'll cover various use cases, from simple library changes to complex refactoring involving multiple files and type changes. This post aims to showcase how AI can significantly reduce grunt work, letting you focus on the creative and challenging aspects of software development.
Who is this for? This guide is for developers who are looking for ways to optimize their coding process and want to learn how to integrate AI into their workflow. If you're dealing with large codebases, frequent refactoring, or tedious updates, then this blog post is for you!
Time investment: ~10 minutes Prerequisites: Basic understanding of software development concepts and version control.
Diving into the Details
Time Zones: A Necessary Evil
Before we dive into coding with AI, let's discuss time zones, a topic every developer must grapple with eventually. Time zones aren’t geometric; they’re political. This fact explains why a country like China with a huge population has only one time zone, while the US has five.
When working with time in your applications, you need to consider three time-related values:
Database Time: This is the source of truth for your application's time and should always be stored in UTC. In Postgres, this can be handled using
timestamp with time zone, which, despite its name, internally stores the value in UTC.Local Time: This refers to the time zone of the machine that is connected to the system.
Session Time: This is tied to the user’s machine for the duration of the session.
Understanding this distinction is vital for handling time-related issues in any application, particularly calendar-based systems.
Cursor: Beyond Just an Editor
As mentioned earlier, this post is not sponsored. It focuses on real-world usage of Cursor and showcases how it can significantly enhance your coding workflow through its new tricks, especially the composer. The composer allows you to edit multiple files, leveraging both inline editing and the chat interface.
Test Case 1: Library Changes and Simple Refactoring
In this first test, the objective is to make a library change, including function changes and dependency updates. This demonstrates a basic refactoring use case. Cursor handled this task very well, which highlighted its potential for streamlining code updates.
Test Case 2: Type Changes and File Additions
The second test takes things a step further. This test focuses on changing multiple types and adding new files.
Test Case 3: Complex Refactoring across Multiple Files
This is where Cursor truly shines. The third test involves 10 files, different directories, type changes, and library updates. It’s a complex scenario that would typically require significant manual effort. Here are the specific steps we took:
Swapping Out Custom Types: Replace custom types with the definitely-typed library using Calendar V3.
Type Analysis: Check if we have any custom types that we may have added that is not part of the library.
Calendar Component Audit: Read through all the calendar components to ensure we are only using the calendar types from Google.
No Custom Date Parsing: Verify we are not using custom date parsing logic.
UTC Time Storage: Ensure that the calls for storing values are stubbed out as UTC.
Amazingly, Cursor nailed it, completing all the specified changes across all files. It was a complex refactor that handled with impressive accuracy.
Code Example: Calendar Event Refactor
To give you a concrete example, consider this real world scenario of handling all day calendar events. The goal was to remove legacy code for fetching and processing all-day events from Google Calendar and switch to using server actions.
Problem: The initial implementation scattered the logic across three different files. The legacy code used a custom date utility and not the V3 Google calendar types.
Solution: Using the composer, we feed Cursor examples of the shapes for all day and non all day events. Cursor analyzed the Google calendar types and generated the necessary schema, handling the all-day event logic by checking for the presence of an "allDay" property.
Outcome: The original three files were condensed into a single file, streamlining the code, and making it much more efficient.
Composer Workflow: How It Works
Here's how you can work with Cursor’s composer:
Start a Thread: The left side of the composer panel shows your thread, where you provide context to the AI.
Define Your Requirements: Use the floating to-do list (on the right side of the panel) to define the steps needed and the changes that you want made.
Provide Context: Feed the composer with context of the files you need changed.
Review Code Changes: The composer will provide you with code diffs and updated full files.
Accept or Adjust: Accept changes as necessary, and update your cursor rules as required.
Cursor Rules
Cursor Rules are located in .cursorrules file in the root of your project. These rules allow you to define your preferences for how Cursor generates code. For example, you can specify that you prefer export default over const. This level of customization lets you have better control over the code that the AI is providing.
Practical Applications
Here are some potential real-world use cases of cursor that can significantly enhance your daily coding workflows:
Library Upgrades: Replace deprecated libraries with their updated alternatives.
API Migration: Update a bunch of endpoints by refactoring a legacy API in your application.
Type Refactoring: Enforce stricter typing standards by updating existing types.
Codebase Modernization: Introduce new best practices across your codebase.
Database Schema Changes: Streamline the process of modifying database access layers.
Conclusion: The Future of Coding with AI
AI tools like Cursor are changing the way developers work. By automating mundane and repetitive tasks, they allow us to focus on the more interesting and creative parts of our job. The key is to understand how to prompt the AI effectively, providing it with the right context.
Next Steps
Explore Cursor: Dive in and begin using Cursor on your codebase.
Refine Your Prompts: Continue to work on refining your prompts to get the most out of Cursor's AI.
Share Your Insights: Continue learning, explore other AI tools and discuss your findings with others.
By embracing these tools, you can significantly reduce grunt work and unlock new levels of productivity and creativity. The journey has just started. There will be more advanced AI tooling in the future.
This concludes our exploration of Cursor and its capabilities. Let’s embrace the future and use these tools to their fullest potential!