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.
Starting from how AI coding agents execute work, this article explains why agent-native documentation has evolved from reference material into infrastructure, defines the responsibilities and organization of AGENTS.md, PRD, Architecture, Spec, and Plan documents, and shows how Context Engineering and Spec-Driven Development can produce a context-efficient system that reliably directs agent behavior.
This article systematically reviews frontline experience from OpenAI, Anthropic, HumanLayer, and other teams documenting AI coding-agent projects. It explains why entry-point files, layered knowledge bases, state-tracking files, and local documentation directly affect Agent performance, and provides an actionable path from a minimum viable documentation system to continuous maintenance.