How to Write Your First 100 Lines of Code Using AI Assistants

If you’re a beginner trying to break into coding, the thought of writing your first 100 lines of code can feel daunting. But what if I told you that AI coding assistants can make this journey smoother and faster? In 2026, these tools have evolved significantly, offering incredible support for new coders. However, it's essential to know how to leverage them effectively.

In this guide, I’ll walk you through using AI coding assistants to write your first 100 lines of code. I’ll share the tools we’ve used, their pricing, strengths, and limitations, so you can choose what fits your needs best.

Prerequisites: What You Need Before Starting

Before you dive into the world of coding with AI, here are a few things you should have ready:

• Basic Understanding of Programming Concepts: Familiarity with concepts like variables, loops, and functions will help.
• An AI Coding Assistant Account: Choose one from the tools listed below.
• A Text Editor or IDE: Install something like VS Code or any other code editor you prefer.

Time Estimate: How Long Will It Take?

You can expect to complete your first 100 lines of code in about 2-3 hours. This includes time spent experimenting with the AI tools and debugging your code.

Step-by-Step Guide to Writing Your First 100 Lines of Code

1. Choose Your AI Coding Assistant

Here’s a list of AI coding assistants you can use:

| Tool Name | Pricing | Best For | Limitations | Our Take | |-------------------|-----------------------------|------------------------------|--------------------------------------|-------------------------------| | GitHub Copilot | $10/mo; Free trial available| General coding assistance | Requires GitHub account | We use it for quick code snippets and suggestions. | | OpenAI Codex | $0-20/mo (API usage) | Complex problem-solving | Can be expensive based on usage | Great for brainstorming solutions. | | Tabnine | Free tier + $12/mo pro | Autocompletion | Limited to syntax suggestions | We don’t find it as helpful for learning. | | Codeium | Free | Fast code generation | Limited language support | We use this for quick prototypes. | | Replit | Free tier + $7/mo pro | Collaborative coding | Performance issues with large projects| It's nice for learning in teams. | | AI Dungeon | Free | Creative coding exercises | Not focused on traditional coding | Fun for storytelling in code! | | Sourcery | Free tier + $19/mo pro | Code optimization | Focused on Python only | Useful for refining existing code. | | Ponic | Free | Beginners and non-coders | Limited advanced features | We don’t recommend for serious projects. | | Codeium | Free | Fast code generation | Limited language support | We use this for quick prototypes. | | Jupyter Notebook | Free | Data science and visualizations| Not a traditional coding tool | Excellent for learning Python basics. |

2. Set Up Your Environment

Once you’ve chosen a tool, install it and set up your coding environment. For instance, if you’re using GitHub Copilot, integrate it with your IDE. This integration allows the AI to suggest code as you type, significantly speeding up your workflow.

3. Start Coding

Now, it’s time to write code. Here’s a simple project idea: create a basic calculator. You can break this down into the following 100 lines:

• Define Functions: Addition, subtraction, multiplication, and division functions.
• User Input: Use input functions to get user data.
• Display Results: Print the results of calculations.

As you write, let the AI assistant suggest code snippets. For example, if you type def add(a, b):, Copilot might suggest the complete function.

4. Debugging

Inevitably, you’ll run into errors. Here’s how to troubleshoot effectively:

• Read Error Messages: They often point you to the line of code that’s causing the issue.
• Ask the AI for Help: If you’re stuck, describe your problem to the AI, and it can suggest fixes.
• Test Incrementally: Write and test small pieces of code to avoid overwhelming yourself.

5. Review and Optimize

Once you’ve written your 100 lines, review the code for efficiency. Use tools like Sourcery or Tabnine to help refine and optimize your code. This step is crucial as it teaches you best practices in coding.

What Could Go Wrong

Here are a few common pitfalls:

• Over-reliance on AI: While AI can suggest code, make sure you understand what it’s doing. Blindly accepting suggestions can lead to poor coding practices.
• Ignoring Documentation: AI tools may not always provide the best solution. Refer to official documentation for better context.

What's Next?

Once you’ve completed your first project, consider moving on to more complex projects. Try integrating APIs, working on web development, or even contributing to open-source projects. Each of these steps will build your skills further.

Conclusion: Start Here

If you’re ready to write your first 100 lines of code, start by choosing an AI coding assistant from the list above. I recommend GitHub Copilot for its versatility and ease of use. Remember, the goal is to learn and grow, so don’t hesitate to experiment and make mistakes along the way.