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Lamina

Design how it works. Transactional product-knowledge graph for AI coding agents. Invoke /lamina-init, /lamina-design, and /lamina-verify to publish intended behavior, source observations, and isolated Persona Mission evidence.

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# Lamina

> Design how it works. Transactional product-knowledge graph for AI coding agents. Invoke /lamina-init, /lamina-design, and /lamina-verify to publish intended behavior, source observations, and isolated Persona Mission evidence.

Lamina is an Apache-2.0 transactional product graph. Ladybug stores canonical Resources, Statements, versions, sessions, and Runs; CocoIndex incrementally supplies explicit source Observations through graphd.

Positioning: Product-design skill for developers who build with AI — know what to build, iterate faster.

Who it's for: Developers using AI coding agents (Cursor, Claude Code, Codex, Gemini, Pi) — not designers or PMs.

The loop: /lamina-init → /lamina-design → implement → /lamina-verify → fix. Run slash commands explicitly in agent chat — Lamina does not activate passively after install. Slash commands produce `.lamina/` artifacts; your coding agent implements app source; Lamina verifies the live build.

Lamina (lamina.dev) is an open-source product-design skill for AI coding agents — not uselamina.ai (creative API for media generation).

Key facts:

- Not a UI library — never writes app source or picks your component library
- Not an app builder — does not generate stack-locked apps like v0 or Lovable
- Not a pixel skill — Impeccable and frontend-design polish how it looks; Lamina designs how it works
- Open-source Apache-2.0 — https://github.com/aryaniyaps/lamina
- Install: `curl -fsSL https://github.com/aryaniyaps/lamina/releases/latest/download/install.sh | sh && npx skills add aryaniyaps/lamina --skill '*' -a <active-agent> -y`
- Commands: /lamina-init, /lamina-design, /lamina-verify, /lamina (optional router)
- Atomic, versioned product behavior with semantic branch diffs
- Independent Missions for every active Persona
- Epistemically separated intent, observations, simulation, and runtime evidence
- Fits any stack — framework, database, language, UI library, and AI coding tool
- Creator: Aryan Iyappan (https://aryaniyappan.com)
- Contact: https://github.com/aryaniyaps/lamina/issues

## Product

- [Homepage](https://lamina.dev): Product overview, positioning, and install command
- [What is Lamina?](https://lamina.dev/docs/concepts/what-is-lamina): Behavior vs pixels, comparisons, core principles
- [HavenStay demo](https://lamina.dev/docs/guides/demo-havenstay): Side-by-side build with and without Lamina
- [Quickstart](https://lamina.dev/docs/getting-started/quickstart): Run the full init → design → implement → verify loop
- [Installation](https://lamina.dev/docs/getting-started/installation): Install in Cursor, Claude Code, Codex, Gemini, or Pi

## Learn

- [Learn hub](https://lamina.dev/learn): Product behavior, transactional graph lifecycle, independent Persona Missions, FAQs, and guide index
- [What is headless product design?](https://lamina.dev/learn/what-is-headless-product-design): Category definition: behavior contracts for AI coding agents, vs UI skills, headless CMS, and app builders
- [C
…

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