How to Improve Your Code Quality with AI in Just 2 Hours

In the fast-paced world of coding, maintaining high-quality code can feel like a never-ending battle. As indie hackers and solo founders, we often find ourselves juggling multiple roles—developer, marketer, and support. The good news? AI tools can significantly improve your code quality, and you can get started in just 2 hours.

Prerequisites

Before diving in, make sure you have the following ready:

• A codebase to work with (preferably a small project)
• Access to a code editor (like VSCode)
• A GitHub or GitLab account for version control
• Internet connection to access AI tools

Step 1: Choose the Right AI Tools

Here’s a look at some of the best AI tools available for improving code quality, along with their pricing and limitations:

| Tool Name | Pricing | Best For | Limitations | Our Take | |--------------------|----------------------------|------------------------------|---------------------------------------------|----------------------------------------| | GitHub Copilot | $10/mo (individual) | Autocompletion & suggestions | Limited to supported languages | We use this for fast code suggestions. | | SonarQube | Free tier + $150/mo pro | Static code analysis | Can be complex to set up | We avoid it due to the setup time. | | CodeGuru | $19/month | Code reviews & recommendations| Limited languages supported | Great for Java, not so much for Python. | | DeepCode | Free for open-source, $12/mo for private repos | AI code reviews | Not as comprehensive as others | We like it for quick checks. | | Tabnine | Free tier + $12/mo pro | Autocompletion | Less context-aware than Copilot | We use it for simple projects. | | Snyk | Free tier + $49/mo pro | Security vulnerability checks | Limited to specific languages and frameworks | We don’t use it for smaller projects. | | Codacy | Free tier + $15/mo pro | Code quality metrics | Can be overwhelming with too many metrics | We like the insights but skip it sometimes. | | Kite | Free | Autocompletion | Limited to certain languages | We use it for Python coding. | | ESLint | Free | Linting for JavaScript | Requires configuration | Essential for our JS projects. | | Prettier | Free | Code formatting | Doesn't catch logical errors | We use it religiously for formatting. | | Pylint | Free | Python linting | Can be overly verbose | We stick with it for Python projects. | | Checkmarx | Custom pricing | Security & compliance | Expensive for small teams | We don’t use it due to cost. |

What We Actually Use

In our experience, we primarily rely on GitHub Copilot and Kite for quick coding boosts, while ESLint and Prettier are essential for maintaining our JavaScript projects.

Step 2: Set Up Your AI Tools

1. Install GitHub Copilot:

   • Go to the GitHub Copilot website and sign up for the individual plan.
   • Install the extension in your code editor (like VSCode).
   • Open your project and start coding. You'll see suggestions pop up as you type.

2. Integrate Linting with ESLint:

   • Run npm install eslint --save-dev in your project directory.
   • Initialize ESLint with npx eslint --init and follow the prompts.
   • Configure your .eslintrc file to match your coding style.

3. Add Code Formatting with Prettier:

   • Install Prettier with npm install --save-dev prettier.
   • Create a .prettierrc file for your formatting preferences.
   • Add a script in your package.json to run Prettier on your code files.

Expected Outputs

After setting up, you should see:

• Autocompletion suggestions while coding with GitHub Copilot.
• Code quality alerts and suggestions from ESLint in your editor.
• Consistent code formatting applied by Prettier.

Troubleshooting Common Issues

• Copilot suggestions aren't showing up: Ensure the extension is enabled and you're logged into GitHub.
• ESLint errors are too verbose: Adjust the configuration in your .eslintrc file to reduce the number of rules checked.
• Prettier conflicts with ESLint: Use eslint-config-prettier to disable conflicting rules in ESLint.

What's Next

Once you've improved your code quality, consider exploring more advanced AI tools for automated testing and deployment. Tools like Test.ai for automated UI testing or CircleCI for continuous integration can further enhance your coding workflow.

Conclusion: Start Here

To get started on improving your code quality with AI, I recommend focusing on GitHub Copilot and ESLint as the core tools. Set aside 2 hours to install and configure these tools, and you'll notice a significant difference in your coding experience.