After building a project using Kiro’s spec-driven development workflow and comparing it with tools like Cursor and GitHub Copilot, one thing became very clear: AI coding itself is not the issue. The real problem is how we approach it.
Most developers today are unintentionally practicing what is now called “vibe coding”, a workflow where you rely heavily on AI prompts, quick iterations, and instant code generation without properly designing the system beforehand. It feels fast, flexible, and even powerful in the beginning. But when you try to take that same approach into production-level systems, the cracks start to show.
What Vibe Coding Actually Looks Like
Vibe coding usually starts with a simple prompt. You ask the AI to build something like a game, a dashboard, or a backend system, and it immediately generates working code. From there, you keep improving it step by step using follow-up prompts such as “fix this bug,” “add this feature,” or “make it cleaner.”
At first, this feels like rapid development. You are building fast, seeing instant results, and constantly moving forward. But the issue is that there is no real system design behind the code. Everything is being added reactively instead of being designed intentionally.
Why Vibe Coding Breaks in Production
The biggest problem with vibe coding is that it works only in the early stage. As the project grows, structure starts to break.
First, architecture becomes unclear because features are added through separate prompts, leading to inconsistent code organization. Second, context starts to degrade, and AI may lose track of earlier decisions. Third, complexity increases uncontrollably because everything is patched together instead of being designed properly. This is the point where projects start becoming hard to maintain.
My project Experience
I noticed this clearly while building Flappy Bird in Node.js. At the start, everything was smooth and fast. But as more features were added, the logic started overlapping, debugging became harder, and small changes affected other parts of the game. It felt productive at first, but over time, the lack of structure started creating problems.
How Kiro Changes the Workflow
Kiro solves this by introducing spec-driven development. Instead of jumping straight into prompts like “build Flappy Bird,” you first define a structured specification describing how the system should work.
In my case, I defined gameplay rules like gravity, pipes, scoring, and collision before any code was generated. Kiro then built the implementation based on that structure. This shifts development from reactive coding to intentional system design.
From Reactive to Structured Development
In vibe coding, you fix problems after they appear. In Kiro, you define the system first, and most issues never appear in the first place. This makes development more controlled, predictable, and structured.
Why Structure Matters More Than Speed
Most AI tools focus on speed, but speed without structure does not scale. Vibe coding works well for prototypes and experiments, but breaks down in larger systems because complexity grows too quickly. Kiro solves this by introducing structure before code exists
Final Thoughts:
AI development is evolving from fast code generation to structured system design.Copilot helps you write faster, Cursor helps you work with code, but Kiro helps you define systems before they are built. And that’s the key difference.
Vibe coding fails in production not because AI is weak, but because structure is missing from the process.
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