Day 4: Building Your First App with Kiro (Step-by-Step AI Development)

#kiro #ai #productivity #webdev

Over the last few days, I’ve been exploring Kiro and trying to understand what makes it different from the growing number of AI coding tools entering the market. At first, I thought it was simply another AI-powered IDE focused on faster development and better code generation.

But after building a real project with it, I realized the bigger idea behind Kiro is not just speed, it’s structure.

So for Day 4 of this series, I decided to build something more interactive and fun instead of another basic CRUD application. I chose to build a simple Flappy Bird clone using Kiro to properly test how spec-driven development actually feels in a real workflow. The goal wasn’t just to “build a game with AI.”

The real goal was to experience how spec-driven development in Kiro actually behaves in a real project. And this is where things started to feel different from traditional AI coding tools.

Why I Chose Flappy Bird

I intentionally picked Flappy Bird because it’s deceptively simple.On the surface, it looks like a small beginner game, but technically it includes several important development concepts:

Game physics
Collision detection
Animations
Rendering loops
User input handling
State management
Score systems

That makes it a perfect project for testing how well Kiro handles structured implementation and iterative development.

Most AI tools perform well when generating static pages or small components. But interactive systems are where workflows usually become messy. Context gets lost, features break, and the generated architecture slowly turns chaotic. That’s exactly what I wanted to test with Kiro.

Starting with Spec-Driven Development in Kiro

The first step was not coding at all.I started inside Kiro using its spec-driven development workflow, where you define system behavior first and only then move toward implementation. This is very different from traditional AI coding where you directly ask:

“Build Flappy Bird in Node.js”

Instead, Kiro pushes you to first define what the system is supposed to do.That shift alone changes how you think about development.

Writing the Node.js Game Specification

Inside Kiro, I created a structured spec for the Flappy Bird game. Here’s what I defined:

Build a Flappy Bird game using Node.js with the following behavior:

- Bird affected by gravity (physics simulation)
- Jump mechanic using key press input
- Pipe generation with random gaps
- Continuous movement loop
- Collision detection system
- Score increases when passing pipes
- Game over state when collision occurs
- Restart functionality
- Real-time game loop execution

Instead of thinking in terms of files or functions, I was thinking in terms of system behavior. That’s the key idea behind spec-driven development. You define what the system should do, and Kiro translates that into structure and implementation.

How Kiro Structured the Node.js Implementation

Once the spec was finalized, Kiro didn’t jump into dumping code. Instead, it broke the system into logical modules and components.The Node.js implementation was structured around:

game loop handling
physics engine logic (gravity + movement)
pipe generation system
collision detection module
score tracking system
input handling (keyboard events)

This separation was very important because it prevented the usual problem of AI-generated “single-file chaos.” In traditional vibe coding, Node.js projects often become messy quickly because everything gets merged into one script. Here, the structure stayed clean and understandable.

Generating the First Working Version

After processing the spec, Kiro generated the first working version of the game logic. Even though it was running in a Node.js environment, the core mechanics were already functional:

bird movement simulation
gravity behavior
pipe spawning logic
collision detection
score updates

What impressed me most was not just that it worked, but that it worked in a structured way. The system wasn’t random, it followed the spec I had defined earlier. That connection between intent → spec → implementation was very clear.

What Felt Different Compared to Vibe Coding

This project made the difference very obvious. In traditional vibe coding workflows:

you prompt repeatedly
code structure breaks over time
debugging becomes harder
context is often lost
Node.js files quickly turn messy

But with Kiro’s spec-driven approach:

structure stays stable
changes are intentional
system design remains consistent
iteration is predictable

Instead of constantly fixing broken outputs, you are refining a system definition. That is a completely different mindset.

Final Result

By the end of this project, I had a working Flappy Bird-style game logic built in Node.js using Kiro’s spec-driven workflow. It included:

gravity-based physics
pipe generation system
collision detection
score tracking
restart logic

But the real outcome was not just the game. It was understanding how structured AI development changes the entire workflow from coding to system design.