gaoweiblue-source/tob-llm-paradigm-collection

★ 22TypeScriptAudience · pm founderComplexity · 2/5Setup · easy

Mindmap

mindmap
  root((tob-llm-paradigm-collection))
    What it does
      Catalogs AI patterns
      Interactive demos
      Copyable agent prompts
    Audience
      Enterprise businesses
      B2B teams
    Tech Stack
      TypeScript
      Next.js App Router
      React
    Structure
      Paradigms registry
      Demos directory
      App and components dirs
    Use Cases
      Browse AI patterns
      Try demos before adopting
      Build internal pattern library

mindmap root((tob-llm-paradigm-collection)) What it does Catalogs AI patterns Interactive demos Copyable agent prompts Audience Enterprise businesses B2B teams Tech Stack TypeScript Next.js App Router React Structure Paradigms registry Demos directory App and components dirs Use Cases Browse AI patterns Try demos before adopting Build internal pattern library

Click or tap to explore — scroll the page freely

Things people build with this

USE CASE 1

Browse a catalog of named enterprise AI patterns and try each one with a live interactive demo before adopting it in a real workflow.

USE CASE 2

Copy a ready-made AI agent prompt for a specific business process and paste it directly into ChatGPT or Claude.

USE CASE 3

Fork the project and extend it with new patterns by adding a registry entry and a demo component, with no extra configuration needed.

USE CASE 4

Use it as a starting template for building an internal AI pattern library tailored to your own company's workflows.

Tech stack

TypeScriptNext.jsReact

Getting it running

Difficulty · easy Time to first run · 5min

No license information is mentioned in this explanation.

In plain English

This is a TypeScript web application that serves as a catalog of AI transformation patterns for enterprise businesses. The site lists named patterns on its home page, clicking any pattern opens a detail page with two panels: a live interactive demo on the left and a copyable AI agent prompt on the right. The target audience is Chinese enterprise companies (the "toB" label refers to the business-to-business market) that are exploring how to apply large language models in their workflows. The project uses Next.js with the App Router. Source code is organized into four areas: the app directory for the home page and per-pattern detail pages, a components directory for layout and card components, a demos directory for each interactive pattern demo, and a paradigms registry where each pattern's title, description, prompt, and live-or-draft status are stored. Adding a new pattern involves three steps: updating the registry file with the pattern's details and changing its status to live, creating a new demo component in the demos directory, and registering that component in a separate registry file. The home page then automatically displays the new pattern with an indicator that it can be tried interactively. The README is brief and focused almost entirely on setup and deployment steps, with minimal description of what any specific pattern or demo actually does. The project appears to be a personal or small-team tool for collecting and presenting enterprise AI prompts alongside proof-of-concept demos, rather than a finished product. Local development runs with a standard npm install and npm run dev.

Copy-paste prompts

Prompt 1

I'm building a Next.js App Router site similar to this project. Show me how to create a registry file that stores pattern metadata and dynamically generates a detail page for each pattern.

Prompt 2

How do I add a new AI pattern to this catalog? Walk me through updating the paradigms registry, creating a demo component, and registering it so it appears automatically on the home page.

Prompt 3

I want to fork tob-llm-paradigm-collection and translate all the pattern names and descriptions from Chinese into English. Which files do I need to edit?

Prompt 4

Show me how to deploy this Next.js app to Vercel and configure it so each pattern detail page is statically generated at build time.

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