meta-loop-methodology

What problem does it solve?

The Meta-Loop methodology provides a repeatable, AI-assisted software development workflow that emphasizes external documentation as the durable artifact, enabling single-shot delivery and transferability across platforms.

Core Features & Use Cases

• Three-loop model combining Wireframe → Spec → Implementation with Plan, Ask, and Agent modes to guide AI actions.
• Delete and Regenerate discipline that discards faulty artifacts and rebuilds from clarified source docs.
• Documentation-centric learning that persists across sessions and platforms, including wireframes, specs, and AGENTS.md.
• Use cases include teams seeking reproducible AI-assisted development and cross-platform prototyping.

Quick Start

Draw a simple wireframe, verify understanding with /ml-wireframe, generate the spec with /ml-spec, implement with /ml-impl, and capture learnings with /ml-retain.