# Docusaurus Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/docusaurus
> Markdown URL: https://aitinkerers.org/technologies/docusaurus.md
> Technology record last updated: 2026-02-24T08:56:27Z
> Generated: 2026-09-22T03:43:42Z

Docusaurus is an open-source static-site generator (SSG) from Meta (formerly Facebook) for building and deploying high-performance documentation websites with React.

Docusaurus is a powerful SSG that streamlines documentation creation: you focus on content in Markdown/MDX, and it handles the architecture. It builds a fast single-page application (SPA), leveraging React for interactive elements and client-side navigation. Key features are built-in: versioning for API docs, internationalization (i18n), and search integration (e.g., Algolia). The framework is highly extensible via a robust plugin system, allowing developers to customize themes and add functionality without building a doc site from scratch.

- Official technology site: https://docusaurus.io
- Public AI Tinkerers demos and talks: 2
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Survey of Software: Mapping Python's Library Landscape with AI-Powered Research](https://seattle.aitinkerers.org/talks/rsvp_OA9n1DYQS8M)

A live research repository demonstrating systematic library discovery using Claude Code. Visit my station to explore 40+ completed categories (sorting algorithms, graph libraries, ML frameworks, crypto tools, etc.) organized in a Dewey Decimal-style taxonomy. I'll walk visitors through: The research output - Browse the Docusaurus site (https://research.modelcitizendeveloper.com/survey/) showing completed surveys The Four-Pass Survey methodology - How each category gets researched: Rapid Discovery → Comprehensive Analysis → Need-Driven Discovery → Strategic Selection Live demonstration - Run a new category research session with Claude Code if there's interest The metaprompt - Show the actual prompts that drive the research Visitors can: Request categories they need researched (128 still pending!) See how to adapt the methodology for their own domains Grab the metaprompt to run their own surveys Discuss the broader question: "What does development look like when AI can generate code instantly?" (Answer: Systematic library selection becomes the bottleneck) This is a working research project, messy and evolving. Perfect for science fair show-and-tell.

- Event context: AI Tinkerers Seattle: January Meetup — 2026-01-31 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_OA9n1DYQS8M

### [Shifting Out: Using AI to Translate Across the Organization](https://atlanta.aitinkerers.org/talks/rsvp_ws8aA88TM4Y)

I will explores how AI can act as a translation layer across the organization. Not replacing people, but helping teams shift perspective without losing meaning. How to: Translate executive intent into actionable product and engineering scopes Normalize language between product, design, engineering, and marketing Preserve context while shifting between abstraction levels (strategy ↔ tactics ↔ implementation) Reduce “telephone game” loss across async, distributed teams Rather than focusing on prompt tricks or specific models, this talk centers on organizational leverage: where AI creates clarity, where it introduces risk, and how to design workflows that make translation reliable instead of fragile.

- Event context: Co-Co-Code & Cocoa: The AI Tinkerers Atlanta Holiday Meetup — 2025-12-16 — Atlanta
- Public talk page: https://atlanta.aitinkerers.org/talks/rsvp_ws8aA88TM4Y

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