How to Use AI Tools to Write 100 Lines of Code in 30 Minutes

As indie hackers and solo founders, time is our most precious resource. If you’re anything like me, you’ve stared at a blank screen, wishing for a magic wand that could just conjure up the code you need. Well, in 2026, AI coding tools are here to help you write code faster and more efficiently. In this article, I’ll break down how to leverage these tools to generate 100 lines of code in just 30 minutes.

Prerequisites: What You Need to Get Started

Before diving into the tools, here’s what you’ll need:

• Basic coding knowledge: Familiarity with the programming language you're working in (Python, JavaScript, etc.).
• An AI coding tool: I’ll cover several options below.
• A code editor: Such as VSCode or Sublime Text.
• Internet access: Most of these tools require online connectivity.

Step-by-Step Process to Generate 100 Lines of Code

Step 1: Choose Your AI Tool

You’ll want to pick an AI coding tool based on your specific needs. Here are 12 tools to consider:

| Tool Name | Pricing | Best For | Limitations | Our Take | |--------------------|------------------------------|------------------------------|--------------------------------------|------------------------------------------| | GitHub Copilot | $10/mo | General coding assistance | Limited to GitHub ecosystem | We use it for quick code snippets. | | OpenAI Codex | $0-20/mo (depending on usage)| Complex code generation | Can struggle with context retention | Great for more complex tasks. | | Tabnine | Free tier + $12/mo pro | Code completion | Less effective for niche languages | We use it for JavaScript projects. | | Replit | Free, $7/mo pro | Collaborative coding | Performance issues with large code | Good for team projects. | | Codeium | Free, $19/mo pro | Fast code generation | Limited language support | Works well for Python and Java. | | Sourcery | Free, $19/mo pro | Code refactoring | May not catch all edge cases | Useful for improving existing code. | | Polygot AI | $29/mo, no free tier | Multi-language support | Pricing can add up | Good for diverse coding environments. | | CodeGPT | Free tier + $15/mo pro | Quick coding tasks | Context limits can be frustrating | Great for small scripts. | | AI21 Labs | $0-30/mo based on tokens | Natural language processing | API limits can be restrictive | Ideal for data-heavy applications. | | Ponic | $19/mo, no free tier | Specialized coding tasks | Limited community support | Good for specific frameworks. | | Cogram | Free, $20/mo pro | AI-assisted pair programming | Can be slow with large data | We don’t use it often due to speed. | | Codeium | Free, $19/mo pro | Rapid prototyping | Limited integration options | Good for quick experiments. |

Step 2: Set Up Your Environment

1. Install your chosen AI tool: Follow the installation instructions provided by the tool.
2. Open your code editor: Make sure it’s ready for coding.
3. Create a new file: Name it according to the project you’re working on.

Step 3: Define Your Task

Clearly outline what you want the AI to generate. For example, if you need a simple REST API in Python, write down the endpoints and functionality.

Step 4: Input Your Request

Use the AI tool to request code generation. For instance, you could type, "Generate a Flask REST API with endpoints for user registration and login." The better your prompt, the better the output.

Step 5: Review and Edit the Code

Once the AI generates the code:

1. Test it: Run the code in your environment.
2. Debug: Look for any errors or inefficiencies.
3. Refactor if necessary: Clean up the code for better readability.

Step 6: Document Your Code

Don’t forget to add comments and documentation. This is especially important if you plan to revisit the code later or share it with others.

What Could Go Wrong: Troubleshooting Tips

• Incomplete Code: If the AI doesn’t generate enough lines, try breaking your request into smaller parts.
• Errors During Execution: Review the error messages carefully; they often indicate where the problem lies.
• Performance Issues: Some AI tools may lag, especially during peak usage times. Be patient and try again later.

What’s Next?

Now that you’ve generated your code, consider:

• Adding features: Build on the foundation you’ve created.
• Testing: Implement unit tests to ensure your code works as expected.
• Deployment: Get your project live and start gathering user feedback.

Conclusion: Start Here

Using AI tools to write code can dramatically speed up your development process. Start by choosing one of the tools from the list, set up your coding environment, and follow the outlined steps. You’ll be amazed at how quickly you can generate 100 lines of code in just 30 minutes!

If you're looking to streamline your coding process even further, consider listening to our podcast, Built This Week, where we dive into tools we’re testing and the lessons we’re learning while building in public.