The Era of Generative Coding — and Why I Finally Gave In
I’ve never been a big fan of what people now call vibe coding.
To me, coding has always been about clarity, structure, and intent — not just getting something to work because an AI said so.
But here’s the thing: in tech, if you don’t evolve, you get left behind.
That’s just natural selection in motion.
So instead of resisting the wave, I decided to understand it.
I started exploring how AI can be used not just as a helper, but as a collaborator in building better systems.
And that’s how I found myself deep in the world of AI Generative Code — or, as people casually call it today, vibe coding.
A CLI for Machine-Friendly Specs
One of the biggest challenges I’ve noticed when working with AI tools is communication.
Machines don’t “understand” code the way humans do — they interpret patterns, context, and structure.
So, I started building a CLI tool that can generate machine-readable specs, designed to help both developers and AI models speak the same language.
This CLI integrates with multiple AI providers to generate consistent and detailed specification documents.
Think of it as a translator — it turns human intent into structured instructions that AI can process effectively.
The goal isn’t to replace developers.
It’s to make sure that when we code with AI, the results are predictable, explainable, and high-quality.
Output support JSON, YAML & TOON (Token Object Oriented Notation)
Features
- Hybrid Processing: Combines heuristic parsing with AI refinement for optimal accuracy and speed
- Interactive Wizard Mode: Guided interactive refinement when AI is unavailable
- Multiple AI Providers: Supports OpenAI, Anthropic Claude, OpenRouter, and GLM (ZhipuAI)
- Intelligent Caching: LRU cache minimizes redundant API calls
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Flexible Configuration: Environment variables,
.envfiles, and config files - Validation: Built-in spec validation against schema
- Multiple Formats: Output to JSON, YAML, or TOON (Token-Oriented Object Notation)
We’re now entering an era where how we write code matters less than how well we can describe it.
If we can teach the machine to understand our intent — that’s where true collaboration begins.
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