From Coding Challenges to Real-World Solutions: My Journey with AI Pair Programming

Ever wonder how a holiday coding challenge could lead to revolutionizing your work processes and even launching your first app? That's exactly what happened to me, and I'm excited to share how my exploration of AI assistants evolved from solving puzzles to building production-ready cloud infrastructure and practical applications that solve real-world problems.

The Holiday Challenge That Started It All

It all began with Advent of Code, a series of daily programming challenges that pop up every December. While my colleagues were grinding through the problems the traditional way, I decided to take a different approach. Why not use this as an opportunity to evaluate various Large Language Models (LLMs) and coding assistants? It was the perfect testing ground — contained problems with clear success criteria, but enough complexity to really push these AI tools to their limits.

From Puzzle Solving to Practical Applications

As I worked through the Advent of Code challenges with different AI assistants, something interesting happened. I started seeing patterns in how these tools could help beyond just solving puzzles. The way they approached problems, suggested optimizations, and explained their thinking got me wondering: "Could this help with my actual work as a Cloud Engineer?"

That's when it hit me — I had this nagging issue with AWS Health alerts that needed solving. You know, those JSON notifications that look like they were written by robots, for robots? What if I could apply what I learned from my AI coding challenge experiments to a real-world problem?

Meet My AI Pair Programmer

Enter Claude, an AI assistant that turned out to be way more than just another chatbot. While most people think of AI tools as glorified spell-checkers or email drafters, I decided to push the boundaries and see if it could hang with some serious cloud infrastructure work.

The Project's Evolution

What started as "I just want better-looking notifications" quickly turned into:

• "Hey, why not manage this properly with Terraform?"
• "Well, if we're using Terraform, we should have a proper CI/CD pipeline…"
• "And if we're doing CI/CD, we might as well do it right with GitHub Actions…"

Before I knew it, I was building a full-fledged infrastructure pipeline, with Claude suggesting improvements I hadn't even thought of!

The Connection Between Puzzles and Production

Looking back, the progression makes perfect sense. Advent of Code taught me:

• How to effectively prompt AI assistants
• When to trust their suggestions and when to be skeptical
• How to iterate on solutions with AI help
• The importance of understanding the code, not just accepting it

These lessons proved invaluable when tackling my AWS Health notifications project. The same patterns of problem decomposition, solution iteration, and code review that worked for puzzle-solving translated perfectly to building production infrastructure.

The Cool Stuff We Built

The end result? A pretty sweet setup that:

• Catches AWS Health Events (you know, the important stuff)
• Makes them actually readable for humans (revolutionary, I know!)
• Deploys everything through a proper CI/CD pipeline
• Keeps everything in check with version control and approval processes

Want to check it out yourself? The whole project is available at my GitHub repo. Feel free to fork it and make it your own!

Working with an AI Partner: The Good, The Better, and The Surprising

The Good

Claude turned out to be like that really detail-oriented colleague who never gets tired. Every time I hit a wall with an error message, it was like:

Me: "Help, GitHub Actions is complaining about something…"

Claude: "Ah, let me help you fix that and explain why it happened…"

The Better

The documentation game was STRONG. You know how developers (myself included) usually treat documentation as an afterthought? Claude was that voice of reason:

• "Hey, shouldn't we write a proper README for this?"
• "How about a better commit message than 'fixed stuff'?"

The Surprising

Every time we got warnings about deprecated features or needed updates, Claude was on it faster than I could Google the issue. When GitHub warned us about artifact version deprecation or Ubuntu runner updates, solutions were just a prompt away.

What I Actually Built

For those interested in the technical bits, the system:

• Monitors AWS Health Events (because uptime is king)
• Formats notifications so they don't look like computer vomit
• Uses Terraform for infrastructure management (because clicking in consoles is so 2010)
• Runs everything through GitHub Actions with proper checks and balances

From Lawn Care to AI: The Unexpected Connection

But the AI journey didn't stop with AWS infrastructure. In a twist that perfectly combines two of my passions — maintaining my lawn and exploring how AI can transform our daily work — I recently launched my first app: Lawn.Smart.

What started as a weekend project to better manage my own lawn care has evolved into a comprehensive Progressive Web App that provides USDA zone-specific recommendations, intelligent task scheduling, and personalized guidance. The most exciting part? I built the latest features over just a few nights since Claude Code was released on the Pro plan — pure vibe programming with AI assistance.

The Speed Revolution

This is where things get really interesting. The technology is evolving at breakneck speed. What took weeks before now takes days, sometimes hours. The development velocity with AI assistance is truly remarkable, and it's changing not just how we build software, but how we think about what's possible in the time we have available.

Lessons Learned

Here's the real talk:

• AI isn't going to replace us Cloud Engineers or Developers anytime soon
• BUT… it's an incredibly powerful tool when used right
• Always review the code (seriously, don't just copy-paste blindly)
• The future of cloud infrastructure work might be a lot more interesting with AI assistants in our toolkit

The Professional Reality: Your Job Will Change

But here's the key insight from this entire journey: AI isn't here to replace us — it's here to amplify our capabilities and transform how we work. Your job WILL change with AI. The question isn't whether, but how quickly you'll adapt and leverage these tools to enhance your productivity, creativity, and problem-solving abilities.

If you're ready to start your own AI journey, here's my advice:

• ✅ Experiment with AI tools in your field
• ✅ Identify repetitive tasks that could be enhanced
• ✅ Build small projects to learn hands-on
• ✅ Focus on human-AI collaboration, not replacement

The intersection of AI, cloud technologies, and practical business solutions is where the magic happens. Whether you're building infrastructure automation or creating apps that solve real-world problems like lawn care, the principles remain the same.

What's Next?

Claude suggested some pretty interesting improvements I might tackle next:

• Cost estimation (because budgets matter, ask your CFO)
• Slack notifications (because who doesn't love more notifications?)
• Multi-environment support (because production should be special)
• Drift detection (because infrastructure has a mind of its own sometimes)

The Bottom Line

What started as a fun holiday coding challenge with AI assistants has evolved into a new way of approaching cloud infrastructure development. You can check out the results of this journey in my GitHub repository, where I've documented everything from the initial problem to the final solution.

Remember: AI is like a really knowledgeable intern — great at helping out and suggesting ideas, but you still need to be the one making the final calls!

A Meta Twist

Here's a fun fact to wrap things up: This entire article was crafted with the help of Claude, the same AI assistant that helped build the project it describes. I provided the context, experiences, and direction, while Claude helped structure and articulate the story. It's a perfect example of how AI can help with both technical and creative tasks when used as a collaborative tool.

Got questions or want to share your own experiences with AI-assisted infrastructure work? Feel free to reach out! Let's explore this brave new world of AI-assisted cloud engineering together.