🚀 How to Get Started in Coding — Real Quick!

💻 Setting Up

I'm on Ubuntu. I followed this official setup guide:

🎮 Building a Game with C

I challenged Amazon Q to make a Flappy Bird clone — but in C. Why C? Because Python is too easy, and I wanted to see if an AI could handle a low-level language with graphical output.

The prompt I gave was super simple:

"Write me a game in C that is like flappy bird"

Initially, this prompt didn’t work. The AI gave a text-only version of the game. But once I added a simple follow-up — "I want it to be graphical" — it started pulling in graphical libraries and producing real output!

Amazon Q automatically pulled in the necessary dependencies like libsdl2-dev and scaffolded a working graphical prototype.

sudo apt update && sudo apt install -y libsdl2-dev libsdl2-ttf-dev

Simple bird + pipe overlay... and it runs!

Game over :(

🛠️ Takeaways

In the future, we’ve got to be more precise and clear when talking to LLMs.

Giving AI tools clear, well-defined instructions isn’t just a trick — it’s a real-world problem-solving skill. In fact, this is how we solve problems in reality too!

👨‍👩‍👧 How This Helps Kids Learn to Code

One thing that really impressed me is how clearly AI tools like Amazon Q explain classic programming problems. When I asked it to handle collision detection — one of the hardest parts in beginner game development — it not only generated the logic, but explained it too!

For example, detecting when the bird hits a pipe isn’t trivial. But Amazon Q broke it down using meaningful variable names and step-by-step reasoning. This makes it an excellent learning tool — even for kids!

Prompting Amazon Q to explain game logic like collision detection

// AI-generated collision check
if ((bird.x + bird.width > pipe.x) && 
    (bird.x < pipe.x + pipe.width) &&
    ((bird.y < pipe.gapY) || (bird.y + bird.height > pipe.gapY + GAP_HEIGHT))) {
    // Collision detected!
    gameOver = true;
}

This kind of output — clean, well-named, and easy to read — is exactly what we want beginners to see. It shows how to structure a solution and why it works. Looking at these examples and then trying to write your own is a great way to learn.

📦 Making It Portable

For future teaching use, I wanted this game to run anywhere. So I asked Amazon Q to:

• Cross-compile it for Windows
• Wrap it in a Dockerfile

It delivered both!

Now, I can double-click the Windows executable — no setup needed. And I have a Docker-based environment to recompile any time.

🧠 Final Thoughts

I’m genuinely impressed by how easy AI tools like Amazon Q make development.

With such low barriers, anyone can start building and learning — fast.

This experiment has already sparked ideas for more content and hands-on activities.

Stay tuned for the next blog where I’ll reverse engineer this game and crack it open 🔓😉

📁 Final Output

Once everything was done, I packaged the entire project — source code, compiled binaries, assets, and instructions — into a portable zip archive. This makes it easy for anyone to download and try it out without needing to set up a development environment.

I also recorded a quick gameplay video so you can see what the final result looks like in action:

A full build with binaries, source, and README included.