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Try NowWhat is Hermae?
Hermae is an AI assistant designed for enterprise design systems, built by Mike Carbone. It aimed to solve the problem of providing LLMs with the context of a design system to help teams ship products faster. The core capability was converting Storybook documentation to Markdown and creating vector embeddings for RAG, enabling AI to generate production frontend code. However, Hermae has been shut down as an experiment. The tool was intended for design and development teams working with design systems. It fit workflows where teams needed to bridge design and code generation. Despite its shutdown, the insights from Hermae have influenced current best practices, such as using local context in IDEs, public examples, and design tool MCPs. Users looking for similar functionality today are directed to tools like Vercel v0, shadcn/ui, Cursor, and Figma MCP.
AI Tool Review Summary
3.5/5
Experimental, not production-ready
Not specified
LLMRAG
To generate production frontend code by providing LLMs with design system context.
Integrated with Storybook and Markdown workflows.
Discontinued
Features with the highest value for users are highlighted here.
Storybook to Markdown conversion
Vector embeddings for RAG
Design system context for LLMs
Code generation from design tokens
Integration with enterprise design systems
How It Works
1
Convert Storybook docs
Hermae converts Storybook documentation to Markdown format.
2
Create vector embeddings
The Markdown is used to create vector embeddings for RAG.
3
Provide context to LLM
The embeddings give the LLM context about the design system.
4
Generate frontend code
The LLM generates production-ready frontend code based on the design system.
Design system engineers
Frontend developers
Product teams
Enterprise organizations
Startups
UI/UX designers
Technical writers
Open source contributors
Agency teams
Freelance developers
Free
$0/free
No longer available
Pro
N/A/monthly
Discontinued
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Pros & Cons
Validated the concept of AI-assisted design system code generation. Provided a novel approach to context injection for LLMs.
Product has been shut down, no longer available. Approach was less effective than integrated IDE or public context solutions.
FAQs
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Rating
5.0
Pros
Cons
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