This article details a specification-driven AI collaboration system combining OpenSpec for structured requirements and AI Workflows with skills, hooks, and templates for execution, demonstrated through a Vue/TypeScript retail project where AI accuracy improved from 60% to 90%.
Starting in May 2025, the Tmall/Taobao overseas team standardized AI coding through a five‑stage Specification‑Driven Development (SDD) SOP, evolving from manual Vibe Coding rules to the unified All‑in‑One skill, which raised AI coding usage from under 5% to over 90% across multiple business domains.
The article critiques the five fatal flaws of the emerging Vibe Coding paradigm, explains the Specification‑Driven Development (SDD) methodology—including its principles, three‑phase workflow, tool ecosystem, and integration with AI agents—and promotes the first Chinese book that details this approach.
The article explains a specification‑driven development workflow that anchors AI‑generated code to a living requirements document through six closed‑loop stages—requirement authoring, clarification, code generation, cross‑compilation, download verification, and issue fixing—highlighting three iterative cycles and six human decision points that keep the process traceable and safe for industrial control projects.
OpenSpec adds a specification layer to existing codebases, offering a pure, brownfield‑friendly, tool‑agnostic approach where specs act as contracts, changes become first‑class citizens, and incremental Delta Specs replace full‑spec rewrites, with detailed workflows, design insights, limitations, and a side‑by‑side comparison to Spec‑Kit.
Spec Kit is an open‑source specification‑driven development (SDD) toolkit that turns formal specs into executable assets, integrates AI agents, and provides a step‑by‑step workflow—from environment setup and project initialization to automated task breakdown and AI‑driven implementation—enabling predictable, traceable, and governable software delivery.
The article explains how combining OpenSpec’s structured specification and traceability with gstack’s 23 role‑based AI skills transforms AI‑generated code into a fully deliverable, testable, and auditable engineering workflow, providing architecture diagrams, step‑by‑step commands, best‑practice guidelines, FAQs, and real‑world case studies.
The article examines why AI agents need a unified workflow, introduces three popular tools—Spec‑Kit, OpenSpec and Superpowers—details their architectures, data‑flow and core features, shows practical installation and usage examples, and offers scenario‑based recommendations and limitations to help developers pick the right solution.
The article examines why developers mistakenly think AI tools require no learning, outlines the evolution from traditional coding to Vibe Coding, identifies its pitfalls, and presents a four‑stage Specification‑Driven Development (SDD) workflow that transforms personal AI‑assisted coding into a reliable, team‑wide engineering practice.
The article argues that traditional documentation quickly becomes obsolete and proposes a self‑updating specification workflow where both developers and AI agents read and write the spec, eliminating hidden maintenance work and keeping the plan aligned with reality.
VoidLink, an AI‑crafted advanced malware, was produced by a single hacker in under a week, generating over 88,000 lines of code through a specification‑driven workflow that turned AI into both developer and architect, raising alarming concerns about the democratization of high‑level cyber attacks.
This article analyzes the challenges of AI‑assisted coding, explains specification‑driven development, and provides a detailed technical comparison of three tools—OpenSpec, Spec‑Kit, and BMAD—along with scenario‑based recommendations for choosing the most suitable solution.
Spec Kit is an AI‑native specification‑driven development toolkit that treats structured natural‑language specs as the single source of truth, providing end‑to‑end traceability, AI‑native collaboration, and automated code generation to accelerate project setup, planning, and implementation.
The article contrasts the chaotic, prompt‑driven "Vibe coding" approach with Kiro's Spec‑driven development, explaining how a two‑session model—Vibe for creative exploration and Spec for deterministic engineering—structures AI projects from project‑level documentation to runtime execution, improving reliability and traceability.
