How to Use AI Tools to Write Code in Under 30 Minutes

As a solo founder or indie hacker, time is your most precious resource. You might find yourself stuck in the weeds, spending hours writing code when you could be focusing on building your product. Enter AI coding tools. In this guide, I’ll show you how to leverage these tools to write code in under 30 minutes.

Prerequisites: What You Need to Get Started

Before diving in, make sure you have the following:

1. A computer with internet access: This is a given, but it's essential for using online tools.
2. Basic coding knowledge: Familiarity with at least one programming language will help you understand the outputs better.
3. Accounts on selected AI coding tools: Some tools may require you to sign up for an account.

Step 1: Choose Your AI Coding Tool

There are numerous AI coding tools available, but not all are created equal. Here’s a breakdown of some top contenders as of March 2026:

| Tool Name | Pricing | What It Does | Best For | Limitations | Our Take | |--------------------|----------------------------|---------------------------------------------|------------------------------|----------------------------------------------------|----------------------------------| | GitHub Copilot | $10/mo, free for students | Suggests code snippets based on context | Quick code suggestions | Limited to certain languages; not always accurate | We use this for quick prototypes. | | Tabnine | Free tier + $12/mo pro | AI-driven code completions | Boosting coding speed | Free tier has limited features | We don’t use this because it’s pricey for the pro version. | | Codeium | Free, $29/mo for pro | AI-powered code generation | Full project generation | Sometimes generates incorrect logic | We recommend Codeium for full projects. | | Replit | Free tier + $20/mo pro | Collaborative coding environment | Team projects | Limited in language support; free tier is basic | We use Replit for collaborative efforts. | | Sourcery | $10/mo, free for open source| Code review and suggestions | Improving existing code | Focuses more on Python; limited to specific languages | We don’t use it, but it’s good for Python devs. | | Polycoder | Free | Open-source model for coding tasks | Experimental coding | Requires technical know-how to set up | We don’t use it due to setup complexity. | | Ponic | $15/mo | AI-based debugging and optimization | Debugging complex issues | Limited language support | We find it helpful for debugging. | | Codex | $19/mo | Natural language to code generation | Generating code from specs | Can be verbose; may miss nuances | We use Codex for translating requirements to code. | | AICoder | $0-20/mo | Generates code snippets from comments | Quick fixes | Not always context-aware | We don’t use it because of accuracy issues. | | CodeGPT | Free tier + $30/mo pro | Conversational coding assistant | Learning and exploring | May provide incorrect information | We use it to learn new languages. |

Step 2: Set Up Your Environment

1. Sign up for your chosen AI coding tool. For instance, if you choose GitHub Copilot, create an account and install the necessary plugins.
2. Open your code editor (VSCode, Replit, etc.) and ensure the AI tool is activated.

Step 3: Define Your Goal

Before you start generating code, be clear about what you want to achieve. For example, “I need a function that sorts an array of numbers.” The more specific you are, the better the AI will perform.

Step 4: Start Coding with AI Assistance

1. Write a comment in your code editor that describes what you want. For example, // Function to sort an array of numbers.
2. Trigger the AI tool to generate code. With GitHub Copilot, you can press Tab to accept suggestions.
3. Review and modify the generated code. AI tools may not always get it right, so make sure to check for accuracy.

Step 5: Test Your Code

Once you have your generated code, run it. Take note of any errors or unexpected behavior. This is where your coding knowledge comes in handy.

Troubleshooting Common Issues

• The code doesn’t work: Check for syntax errors or logic mistakes.
• The AI didn’t generate what I expected: Try rephrasing your comment for clarity.
• Performance issues: Use profiling tools to identify bottlenecks.

What's Next?

Once you've successfully generated and tested your code, consider the following:

• Iterate on your project: Use AI tools to refine and expand your codebase.
• Learn from AI outputs: Analyze the code generated to improve your own coding skills.
• Explore other use cases: AI tools can help with documentation, debugging, and even learning new languages.

Conclusion: Start Here

Using AI tools to write code can dramatically reduce the time you spend on development. Start with GitHub Copilot or Codeium for their balance of features and pricing. Remember, these tools are there to assist, not replace your coding skills.

What We Actually Use: For quick prototypes, we rely on GitHub Copilot. For full project generation, Codeium is our go-to.