Inspiration
Snake has always been a favorite of mine; it's a simple game but deeply satisfying. When I saw the hackathon, I immediately thought of recreating Snake, but this time leveraging Kiro to experiment with a new workflow. I wanted to explore how Kiro's AI-driven tools could speed up development, especially since I was working solo.
What it does
My Snake game is pretty straightforward. You control a snake moving around a grid, eating food, and getting progressively faster as you grow. The game tracks your score and ends when you collide with yourself or the walls. Simple, addictive, and very much in the spirit of the original.
How I built it
I started by laying out the game mechanics clearly in Kiro. I specified key components like the snake, food items, and collision rules. Once the specs were clear, I prompted Kiro to generate initial code snippets: Moving the snake around Spawning food in random, unoccupied locations Detecting collisions to trigger game overs Throughout development, I had ongoing conversations with Kiro—like asking it to adjust snake speed after every few points scored. I also set up Kiro’s agent hooks to automate the boring stuff, like bundling code and live reloading the page on every commit. This left me free to focus purely on gameplay tweaks.
Challenges I ran into
One of the main ones was getting acquainted with the functionality. The biggest challenge was probably writing a spec detailed enough for Kiro to understand all edge cases, like ensuring food never appeared under the snake’s body. Another hiccup was initially getting the hooks right—sometimes they triggered twice, causing redundant builds. It took some trial and error, but eventually, everything clicked into place.
Accomplishments that we're proud of
Finishing a fully functional Snake game on my own within two days felt pretty good. More than that, I’m happy with how I integrated Kiro’s spec-driven workflow and AI-generated code into my own process. Automating tedious build tasks was another highlight—no manual reloads meant faster iteration and smoother development.
What we learned
I quickly realized that a well-defined spec made a huge difference in AI output quality. It was also interesting to see how conversational coding could dramatically speed up my workflow. Learning to handle and anticipate edge cases with AI was another valuable takeaway. Overall, it was eye-opening to see how much the right tooling could streamline game development.
What's next for Snake
Continuous iteration of the game.
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