This article presents a core design framework for excellent AI agent systems, covering Spec-Driven Development, a three-layer architecture, resolvers, the boundary between latent and deterministic work, diarization, and a self-improving learning loop, helping engineers move from autocomplete-tool thinking to AI-augmented software engineering.
Drawing on 2025–2026 practices in AI coding agents and Spec-Driven Development, this article systematically explains the definition, value, essential components, workflow, and common pitfalls of a Software Spec, and provides a practical template for tools such as Claude Code, Codex CLI, and Cursor.
This article systematically explains the core concepts and four-stage workflow of Spec-Driven Development, as well as its fundamental difference from vibe coding. Drawing on today’s tools and maturity levels, it explains why writing a specification before implementation substantially reduces ambiguity and rework in the age of AI coding agents.