Labs

RS AI Learning Lab Library

Labs reference: RS AI Learning Lab Library.

This is the canonical home for hands-on Learning Lab activities. In a migrated package, lab.md owns the learner metadata, materials, relationships, and complete Activity. Its required README.md preserves only the origin story and reverse-chronological change log, with a Return to lab link.

The rendered Labs page gives every migrated package one visible Release mode: Alpha for an idea under development, Beta for a runnable lab whose required documents are ready, or Gold for a complete lab. Detailed review state, pilot evidence, and future freshness remain separate questions; none should be inferred from Release mode.

Every migrated lab declares all seven material slots in lab.md: Required documents, Lab Notebook, and Learner guide under Use during the lab; Related articles, Videos, Gallery, and Facilitator guide under Go deeper. Each slot is explicitly ready with one or more working items or coming_soon with no items. Gallery is the only public home for worked examples. The Activity contains the <!-- lab-materials --> and <!-- learner-map --> rendering markers so these declarations and relationships appear at their approved locations.

During the pilot, release_mode in lab.md identifies a migrated package. Unmigrated labs keep their legacy README metadata and routes as a temporary fallback until the pilot is approved and the library-wide migration begins.

AI Literacy for the Rest of Us

Prompting and Conversation

Context and Constraints

Judgment and Verification

Conversational Privacy

Relationships with Conversational AI

AI Readiness and Risk Assessment Support

Invitation To Be Curious Again

Signature curiosity practice

Shared safety baseline

AI curiosity and verification

Learner-chosen public-speaking practice

Creative AI Makerspace and AI Literacy

Agentic Coding

Migration and Contribution Status

This source index is a curated set of pathways, not the library inventory. The rendered Labs page builds the complete catalog from package metadata, including Release mode and review needs. Material slots name any planned resource that is still coming soon rather than implying completeness.

New labs start with the Lab Contributor Template and the Lab Contribution Workflow. Proposals begin as GitHub Issues; accepted assignments become package changes through a linked pull request.


Source: labs/README.md