Daily Updates
Added Reality Check for AI as one six-experiment scientific-method module and lab across AI Literacy and Curiosity, with step-based Notebook and source-backed verification materials.
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A working home for tracks, modules, lab ideas, contributor materials, and the V0 roadmap. This site is designed for team access before everyone is comfortable living in GitHub or Obsidian.
Daily updates
Added Reality Check for AI as one six-experiment scientific-method module and lab across AI Literacy and Curiosity, with step-based Notebook and source-backed verification materials.
Added Reality Check for AI as one six-experiment scientific-method module and lab across AI Literacy and Curiosity, with step-based Notebook and source-backed verification materials.
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Tracks
Revisit a question you set aside and use generative AI to see where it leads.
Turn an idea into a small working tool with a coding agent, while keeping control of the plan, changes, tests, and what happens next.
Understand what generative AI can do, choose where it fits, use it with care, and check the results so you can decide what to trust, change, or decline.
Understand how work actually happens, preserve what works, and decide where AI can help, what needs better controls, and what should remain human-led.
Organize information that matters to you so you can find it again, give AI useful context, trace answers to sources, and keep your knowledge current.
Help make learning clearer, more useful, and more welcoming by creating, testing, and improving activities—with clear scope, human review, and fair treatment of contributors.
Use generative AI to make something that interests you, explore different possibilities, and improve it through your own creative choices.
Use AI to play, create, and learn together, with room for every generation to contribute.
Choose when local or self-hosted tools fit, and understand who will secure, maintain, and recover them.
Use AI to support your public voice without losing authorship or audience trust.
Use AI to explore an explanation, practice what you are learning, and check your understanding—while keeping the thinking your own.
See how people, information, tools, and decisions work together, and use that understanding to improve AI-supported systems while keeping responsibility, evidence, and consequences visible.
Understand what changes when AI can act—choose what to delegate, set limits, and verify what happened.
Modules
Help participants use generative AI to follow a worthwhile question farther while keeping curiosity, judgment, and the decision to continue or stop in human hands.
Give learners repeatable ways to think, listen, speak, recover, and revise without turning delivery into a personality judgment or a single score.
Build a more accurate mental model of today's AI by experimenting with it yourself.
Help learners make practical, non-fearful choices before text, files, images, links, or tool access enter an AI-supported activity.
Show students, parents, and lifelong learners how to use AI to learn without outsourcing thinking.
Help businesses avoid treating AI as the starting point instead of the work itself.
A calm, practical first look at generative AI: useful enough to explore, never a reason to hand over human judgment.
A no-account learning sequence for a calm and safe first look at generative AI.
Help people make right-sized technology decisions by comparing current needs with current evidence, testing before depending, reviewing recurring commitments, and planning how to leave.
Beginners, staff, clients, families, students, and community learners who need practical habits for deciding what can and cannot go into AI tools.
Help organizations make intentional choices about public-facing brand images when generative editing makes alteration and recontextualization faster and easier.
Use a coding agent as a planning and implementation partner to make one small, reviewable text-to-speech skill. The learner defines the tool's boundary before code exists, protects a personal provider credential, tests failure paths before a live request, and keeps a human responsible for the audio that is used.
Reusable references
Project Ops
The V0 roadmap, phases, and definition of done.
The active two-week plan for agreeing the content contract and proving it with complete examples.
Transparent contribution, credit, review, and payment expectations.
Issue templates, labels, project-board guidance, and contributor workflow.
Durable project decisions for the Learning Lab.
The source-home overview, V0 boundary, artifact map, and working agreements.
How durable contributor briefs relate to the GitHub work queue.
Project operations source: Curriculum Alignment Disposition — 2026-09-09.
Project operations source: Learning Lab icon dictionary.
Project operations source: Learning Package Architecture Review.
Project operations source: Status Governance Evidence: AI Without the Hype.
Project operations source: Draft Lab Closeout QA — 2026-08-07.
Project operations source: Agentic Coding — Historical Track Audit.
Project operations source: AI Literacy — Historical Track Audit.
Project operations source: AI Readiness and Risk Assessment Support — Historical Track Audit.
Project operations source: Building Knowledge Bases / Second Brains — Historical Track Audit.
Project operations source: Contributor and Mentor Development — Historical Track Audit.
Project operations source: Creative AI Makerspace — Historical Track Audit.
Project operations source: Fun for the Family — Historical Track Audit.
Project operations source: Local Hosting — Historical Track Audit.
Project operations source: Podcaster / Influencer — Historical Track Audit.
Project operations source: Study Time — Historical Track Audit.
Project operations source: Systems Thinking and AI Engineering — Historical Track Audit.
Project operations source: Zero-to-Hero Agentic Literacy — Historical Track Audit.
Project operations source: Contributor Brief: [Module or Activity Title].
Project operations source: RS AI Learning Lab facilitator notes — working v1.
Project operations source: RS AI Learning Lab gallery entry template — working v1.
Project operations source: RS AI Learning Lab contributor template — working v1.
Project operations source: [Title].
Project operations source: RS AI Learning Lab external drafting workbench.
Project operations source: Lab brief — complete before drafting.
Project operations source: RS AI Learning Lab — Claude Code drafting workbench.
Project operations source: [title].
Project operations source: [title].
Project operations source: Facilitator guide: [Title].
Project operations source: Gallery entry: [Title].
Project operations source: Lab: [Title].
Project operations source: External Draft Submission Manifest.
Project operations source: Writing Review: Becoming an Informed Technology Consumer.
Project operations source: Worked example: [Title].
Project operations source: Writing Review - Brand Images in the Age of Generative Editing.
Project operations source: Writing Review - Context Engineering.
Project operations source: Writing Review - Conversation Engineering.
Project operations source: Writing Review: Conversational Privacy.
Project operations source: Writing Review: Digital Relationships.
Project operations source: Writing Review - Prompting Is the Door, Not the Destination.