Recreation of MU/TH/UR 6000 UI from Alien using Fable and Claude
A fan recreation of the fictional MU/TH/UR 6000 interface from the Alien franchise, built using Fable (a generative UI tool) and Claude. The creator, a React developer, used natural language prompts to generate the UI with minimal coding, demonstrating how LLMs can assist in rapid prototyping of complex animated interfaces.
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MCP server feeding live design tokens from real products to LLM agents
An MCP server that provides structured design tokens (colors, typography, spacing, etc.) extracted from live DOM of real products like Linear and Supabase. LLM code agents use these tokens via MCP to generate UI that matches a specific product's design system, avoiding generic outputs. Solves the problem of agents producing bland, average UI by giving them concrete design references.
User recreates old Claude Code 'Agent View' mode as parody video
A Reddit user posted a parody video titled 'New mode tomorrow from Anthropic(parody)' that recreates the old Claude Code 'Agent View' mode. The user notes the irony of using the current model to recreate a previous interface, and that the video required more prompts than earlier recreations.
Co-wrote a 100k-word literary fantasy novel with Claude and built a website
The author spent 400+ hours co-writing a 100k-word literary fantasy novel using Claude, an LLM, and built a website (worldfall.ink) to showcase the work. This demonstrates a use case for LLMs in long-form creative writing, solving the problem of generating coherent, lengthy narratives with human guidance.
3D library of personal book quotes
A desktop-only 3D library where users can walk around and pick up books, each containing a quote saved from a book read since 2017. LLMs were used to port the plain-text quote collection into the 3D environment, enabling a novel, immersive way to revisit personal reading highlights.
LLM-based intelligent chatbot with session history
A full-stack chatbot project that uses an LLM (Anthropic Claude by default) to answer user messages while maintaining per-session conversation history. It provides a simple, self-contained setup with a Node.js backend and a plain HTML/CSS/JS frontend, suitable for developers who want to quickly deploy an LLM-powered chat interface.