How to Improve Your Coding Speed in 30 Minutes Using AI Tools

As a solo founder or indie hacker, you know that coding faster can mean the difference between launching on time or missing your deadline. While there are countless resources that promise to boost your coding speed, most are just fluff. In this article, I’ll cut through the noise and show you how to genuinely improve your coding speed using AI tools—all in just 30 minutes.

Prerequisites: What You Need to Get Started

Before diving in, make sure you have the following:

• A computer with your preferred code editor (VSCode, IntelliJ, etc.)
• Basic familiarity with the programming language you’re working in
• An internet connection to access AI tools
• A list of tasks or problems you want to solve

Step 1: Choose the Right AI Tools

Here’s a list of AI tools that can significantly enhance your coding speed. I've categorized them based on their primary functions.

Code Completion and Suggestions

| Tool Name | Pricing | Best For | Limitations | Our Take | |-------------------|------------------------------|-------------------------------|---------------------------------------------|------------------------------| | GitHub Copilot | $10/mo | Auto-suggestions for code | Limited to GitHub repositories | We use Copilot for quick suggestions. | | Tabnine | Free tier + $12/mo pro | AI-driven code completions | Less accurate for niche languages | We like it for JavaScript. | | Codeium | Free | Smart code completion | Still in beta, may have bugs | Great for trying out AI suggestions. |

Debugging and Testing

| Tool Name | Pricing | Best For | Limitations | Our Take | |-------------------|------------------------------|-------------------------------|---------------------------------------------|------------------------------| | Snyk | Free tier + $49/mo pro | Security vulnerability scans | Can get pricey for larger projects | We don’t use it due to cost. | | DeepCode | $0-20/mo for indie scale | Code review and suggestions | Limited programming language support | We use it for Python projects. |

Code Generation

| Tool Name | Pricing | Best For | Limitations | Our Take | |-------------------|------------------------------|-------------------------------|---------------------------------------------|------------------------------| | OpenAI Codex | $0-100/mo based on usage | Generating code from prompts | Requires fine-tuning for best results | We use it for prototyping. | | Replit | Free tier + $7/mo pro | Online coding environment | Limited features in the free tier | We love Replit for quick tests. |

Total Tool List

1. GitHub Copilot - $10/mo - Best for auto-suggestions, limitations in niche languages.
2. Tabnine - Free tier + $12/mo pro - Great for AI-driven completions, may lack accuracy.
3. Codeium - Free - Smart completions, still in beta.
4. Snyk - Free tier + $49/mo pro - Best for vulnerability scans, can be expensive.
5. DeepCode - $0-20/mo - Code review, limited language support.
6. OpenAI Codex - $0-100/mo - Generates code from prompts, needs fine-tuning.
7. Replit - Free tier + $7/mo pro - Online coding, limited features in free tier.

Step 2: Setting Up the Tools

1. Install and Configure:

   • Start with GitHub Copilot and Tabnine for code completion. Follow their installation guides to set them up in your code editor.
   • Set up OpenAI Codex on their platform and link it to your project.
   • For debugging, integrate Snyk or DeepCode into your workflow.

2. Create a Quick Project:

   • To see the tools in action, create a simple project. Aim for a small web app or a script that solves a problem.

Step 3: Practice Using AI in Real-Time

Set a timer for 30 minutes and try to code as much as you can using the AI tools. Here’s a breakdown of what to focus on:

• Use GitHub Copilot for auto-completing functions or boilerplate code.
• Ask OpenAI Codex to generate a specific function based on your requirements.
• Run Snyk to check for vulnerabilities as you code.

Step 4: Evaluate Your Performance

After the 30 minutes are up, reflect on your experience:

• What worked? Did the AI tools save you time?
• What didn’t? Were there any frustrations with the tools?
• How much code did you produce compared to a typical session?

Troubleshooting Common Issues

• Tool Compatibility: If a tool isn't functioning well with your editor, check for updates or consult the community forums.
• Suggestions Not Relevant: Try tweaking your prompts or asking for different outputs.

What’s Next?

After this session, consider integrating these tools into your daily workflow. You might also want to explore other AI-powered tools for specific tasks, like pair programming or code refactoring.

Conclusion: Start Here

If you want to improve your coding speed, start by implementing GitHub Copilot and Tabnine into your workflow. Spend 30 minutes getting hands-on with them, and you’ll likely see a noticeable boost in your productivity.

What We Actually Use: In our projects, we primarily rely on GitHub Copilot for coding suggestions and OpenAI Codex for generating functions. We find these tools complement each other well and help us keep our coding sessions efficient.