Plainify: AI-Ready Product Specifications
A product specification tool built to generate AI-ready spec files, transforming fragmented product ideas into structured, machine-readable documentation.
Plainify, 2026
Plainify is a product specification tool built to generate AI-ready spec files. I built it to transform fragmented product ideas into structured, machine-readable documentation, ensuring AI agents have the perfect context to build complete, production-ready applications.
The Problem & The Spark
The idea for Plainify emerged from a real-world necessity. During a "Vibe Coding" workshop I conducted with my design team, we faced a recurring bottleneck: every time we wanted to build a feature with an LLM, we had to manually craft detailed Markdown specification files. This repetitive process was draining our creative momentum. We needed a way to generate these "AI-ready" docs on the fly, without sacrificing depth or technical detail.
As AI coding assistants become increasingly integral to the development workflow, communicating requirements effectively has become a new challenge. Vague or unstructured briefs often lead to suboptimal AI outputs, wasting time and effort. Traditional product requirements documents weren't designed for AI consumption.
The Solution & Methodology
I developed Plainify to automate the creation of the PLAIN (Product Language for AI Notation) format. This project served as a milestone in my Vibe Coding journey, moving beyond simple UI tweaks into complex system architecture.
Tech Deep-Dive
The application integrates LLM connectivity and handles Edge Functions for real-time processing to ensure seamless specification generation. The 14-section framework covers all aspects of product specifications, with real-time markdown preview and direct compatibility with major AI assistants like Claude and GPT.
AI-Native Design Process
One of the most significant aspects of this project was the design workflow. I challenged the traditional "Figma-to-Code" handoff by designing the entire UI "on the fly" through intuitive collaboration with AI assistants. I call this approach "Design in Code." I only utilized Figma for branding essentials (logo, favicon, OG images); every other interface element, layout, and interaction was architected within the terminal using Claude Code CLI.
Real-World Validation
While the concept was proven during the Vibe Coding workshop, the final product is the result of iterative development, focused on creating a robust framework for high-quality AI output. It didn't just save time—it changed how we thought about product definition in the age of AI.
Key Features
- 14-Section Framework — A comprehensive structure covering all aspects of product specifications
- Real-Time Preview — See your markdown output as you build your specification
- AI-Ready Export — Direct compatibility with major AI assistants like Claude and GPT
- Free & Open Source — Available on GitHub for the community to use and contribute