Track Map

RS AI Learning Lab Track Map

A working map of Learning Lab tracks, relationships, reusable submodules, and holes to fill.

Status: Working map, not finished curriculum.

This document turns the first AI Learning Lab brainstorm into a usable planning map. It names the tracks we can see, links to detailed track notes, captures cross-track relationships, and identifies the holes we need to fill before any track becomes pilot-ready.

The map is intentionally broader than V0 build scope. V0 still focuses on the current spine, the first module sketches, a small number of lab activities, and contributor workflow. Expansion tracks are captured here so ideas have a place to land without becoming simultaneous commitments.

Track Catalog

Current V0

These are the active V0 organizing tracks.

Expansion

These tracks should be outlined now and built only when enough modules, labs, and learner demand make them viable.

Advanced

This track builds from the published AI engineering framing and should stay concept-led rather than vendor-led.

Potential Split / Needs Definition

This area is visible, but not yet a track.

  • Intro to the Various Tools

Tool-specific instruction may need to split by learner job-to-be-done or mode, such as writing, research, coding, image creation, automation, local hosting, publishing, or collaboration. We should avoid a vendor tour as the organizing frame unless a specific pilot proves it is useful.

Current Track Organization

AI Literacy for the Rest of Us, Invitation To Be Curious Again, Creative AI Makerspace, Agentic Coding, AI Readiness and Risk Assessment Support, Study Time, Fun for the Family, Building Knowledge Bases / Second Brains, Systems Thinking and AI Engineering, Contributor and Mentor Development, Podcaster / Influencer, Zero-to-Hero Agentic Literacy, and Local Hosting have had a Track composition pass. Their shared organizing rule is:

Track → Module → Related Labs

The track guides organize existing sources. They do not rewrite modules or labs, change availability, create prerequisites, or turn a missing item into an implementation commitment.

AI Literacy for the Rest of Us

Promise: 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.

Core — recommended sequence:

  1. AI Without the Hype → A Safe First Try. This is the signature module and lab entry.
  2. Safety: Share Less, Notice More → What Else Came Along?.
  3. Prompting Is the Door, Not the Destination → One Task, Three Conversations.
  4. Conversation Engineering → Stay, Steer, or Start Over.
  5. Reality Check for AI → Reality Check for AI: Six Experiments.

All five featured labs are Beta and have standalone Notebooks. The orientation, Safety, and Reality Check modules remain Draft / Drafting; Prompting and Conversation Engineering remain Sketch / Planned. Core is a composition role, not a readiness label. Live use and supplied-example routes are both complete participation routes. No separate Shared Support module is assigned within AI Literacy; Safety and Reality Check are core here and shared with Curiosity.

Optional Branch — depth routes:

  • Understand and steer: What AI Is and Is Not; Context Engineering.
  • Privacy and relationships: Before You Paste; Conversational Privacy; Relationships with Conversational AI.
  • Verification: When the Bot Sounds Right but Is Not; Trust, But Check the Wires.
  • Technology choices: Pause Before You Pay; How Technology Changes the Ecology of Communication.
  • Learning and making: Creative Latitude.
  • Communication: Public Speaking and its module-owned practice choices.

Developing Route — candidates and deferred directions:

  • Becoming an Informed Technology Consumer is a Sketch / Planned candidate from AI Readiness; no AI Literacy relationship is added by featuring it.
  • AI for Learning: Tutor, Quizmaker, Simulator remains a Seed / Planned input. Dedicated AI-as-instructor curriculum has not been created.
  • Sounds Right—Check It is a proposed lab for When the Bot Sounds Right but Is Not. What’s Possible Beyond Text is a proposed module including provenance and disclosure. Neither has a canonical source page.
  • Current Events Need Current Context, History Beyond the First Answer, Thinking in Constraints, and The Constraint Landscape remain Ideation / Deferred. Escaping the Conversation Gravity Well and Separate the Builder from the Reviewer remain Seed / Deferred.
  • Chatbot Roles and Modes, Problem Definition, and Human-AI Collaboration remain unplaced planning ideas.

AI Literacy gaps and follow-up decisions

  • Brain Dump to Memo remains primary to When the Bot Sounds Right but Is Not. Its fit as applied writing practice, and the proposed Sounds Right—Check It verification lab, need the next artifact review. This composition pass does not reassign either relationship.
  • What AI Is and Is Not is depth rather than a second required orientation. Opportunity Finder remains its assigned lab; the Track does not make it a ready alternate entry.
  • Prompting teaches the first request and repair; Conversation Engineering extends into multi-turn steering and stopping. Reality Check tests a working mental model through experiments. Their core roles do not remove the need to test those handoffs with learners.
  • Track composition, beginner-language, accessibility, package-specific reviews, and pilot evidence remain outstanding. No status is promoted by this organization.

The AI Literacy Track Guide is the current learner route. The historical Track audit preserves the earlier inventories, gap and overlap tables, superseded wording, and checkpoint hashes as evidence rather than a second current inventory.

Invitation To Be Curious Again

Curiosity gaps and overlaps

  • Signature lab assets: the self-contained Lab Notebook, printable Question Path, and Gallery. The Gallery contains two constructed teaching walkthroughs: Which Mountain Is Tallest? and Refrigeration Before Refrigerators. These illustrate the signature question journey; each continuation has its own worked examples.
  • Learner instructions and route choices belong in the Track Guide; preparation, participation adjustments, pilot flow, and learning evidence belong in the signature lab facilitator guide. This map owns contributor inventory, relationships, gaps, and review needs.
  • The Track, signature module, and lab need learning-design, mixed-age, accessibility, privacy/security, applicable-rights, and learner-pilot review before status changes. Linked resources keep their own lifecycle and release labels; appearing in the Track does not promote them or establish pilot readiness.
  • One Small Idea, Two Versions supplies the introductory creative-play Activity, Notebook, optional planning card, Gallery, and facilitator guide. All three continuation packages remain Alpha pending human review and pilot evidence.
  • Each continuation has two prepared written walkthroughs. Simulation examples cover a moving mountain reference line and an invented ice store. These hand-run models use invented numbers and explicit rules; they are not validated physical models or captured learner evidence.
  • Simulation and instructional support share one Seed module. The two Alpha labs provide introductory practice without completing the module or its broader quizmaking and simulation directions.
  • Creative candidates keep their existing primary relationships and lifecycle or Release mode. Inclusion here gathers feedback; it does not reassign or promote them.
  • Shared Safety and Reality Check resources remain primary to AI Literacy. Curiosity embeds only the minimum habits needed for its signature experience.
  • Public Speaking remains primary to Curiosity but is demoted from the core path to an optional branch.

The Curiosity track guide now organizes the learner-facing question journey. This contributor map holds the detailed inventory, gaps, and overlaps.

Two-Track Gaps and Overlaps

  • AI Literacy has an explicit five-module core. Missing verification and beyond-text artifacts, some depth-module lab assignments, and remaining handoff questions are recorded above for the next artifact pass.
  • Safety: Share Less, Notice More and Reality Check for AI remain primary to AI Literacy and related to Curiosity.
  • Public Speaking remains primary to Curiosity and related to AI Literacy; Forty-Five Seconds to Make It Clear remains primary to Conversation Engineering.
  • Module and track statuses remain unchanged; A Safe First Try uses the Beta lab release mode. Human review and pilot evidence are still required before either track is described as pilot-ready.

Creative AI Makerspace

Promise: Use generative AI to make something that interests you, explore different possibilities, and improve it through your own creative choices.

Creative play is the center. The making loop is Imagine → Make → Notice → Change → Decide. The intended signature experience includes purposeful live AI use, directly or through a learner-directed partner or facilitator. A personal account, polished artifact, and public sharing are not required.

  • Core → Make Something Weird: Creative AI Lab, the signature module, remains Sketch / Planned. Its first prepared practice is One Small Idea, Two Versions, Alpha, with a self-contained Notebook and two written examples.
  • Optional Branch — Follow a creative spark → Creative Latitude, Draft / Drafting, and its primary lab From Inspiration to Invention, Beta. The lab is also related to Make Something Weird, but ownership is unchanged.
  • Optional Branch — Build a place to explore → Make Something Weird and its primary lab Build a Tiny Virtual Museum, Alpha. Blender and local project setup belong to this optional branch, not the signature entry.
  • Shared Support → Prompting Is the Door, Not the Destination; Before You Paste; Reality Check for AI; Becoming an Informed Technology Consumer; Conversational Privacy; Relationships with Conversational AI. The guide labels current module statuses and candidate relationships. Prompting remains the signature module’s stated dependency; this pass adds no prerequisites or reciprocal metadata assignments.
  • Developing Route — Make something for learning or family → AI for Learning: Tutor, Quizmaker, Simulator and Family Learning Lab, both Seed / Planned. The former’s related Module to Interactive Single-Page Application is a Beta static context-practice prototype and planning input, not evidence of an AI-as-instructor or simulation curriculum.

Makerspace gaps and relationships

  • One Small Idea, Two Versions supplies the first creative-play Activity and synchronized Notebook. Learners choose one bounded AI contribution and make a deliberate revision; notes, sharing, and image generation are optional. Human and learner-pilot review remain open.
  • The two optional making labs have valid no-AI routes. They support this Track but do not, by themselves, satisfy its intended AI-making encounter. Their instructions and primary-module relationships are preserved.
  • Before You Paste, Reality Check, and Relationships with Conversational AI remain support candidates without a reciprocal Makerspace assignment. Prompting is an explicit module dependency but also has no reciprocal Makerspace Track assignment. Review these handoffs in the subsequent artifact pass rather than silently changing metadata.
  • The Track remains Draft / Drafting, owner Unassigned. The introductory lab has two prepared written demonstrations; demonstrations for the other making branches remain Coming Soon. Source presence is not evidence of pilot readiness; activity design, rights, privacy, accessibility, and pilot evidence remain open.
  • Publishing, family projects, and new creative formats require selection and appropriate boundaries before new packages are commissioned. The Curiosity simulation continuation has its own package; these additions do not complete a family-specific curriculum.

The Makerspace Track Guide is the current learner route. The historical Track audit preserves the old module and lab ideas, dependencies, MVP questions, and checkpoint references as evidence, not another current inventory.

Agentic Coding

Promise: Turn an idea into a small working tool with a coding agent, while keeping control of the plan, changes, tests, and what happens next.

  • Core → Build a Safe Text-to-Speech Skill, the signature module, Draft / Drafting · Builder, and its primary Build a Safe Text-to-Speech Skill lab, Alpha, with a standalone Notebook. Both retain Mike as owner. The transferable practice is Describe → Plan → Build → Check → Decide, not a tour of speech providers.
  • Shared Support → Prompting Is the Door, Not the Destination and Context Engineering, both Sketch / Planned, are the signature module’s stated preparation (Context Engineering or equivalent safe-file practice). Safety: Share Less, Notice More, Draft / Drafting, is a support candidate from AI Literacy. Ownership, dependencies, and reciprocal Track metadata are unchanged.
  • Developing Route — Build a small game → Building a Tiny Game and a small browser-game lab idea. No dedicated module or lab source pages exist for these ideas.
  • Developing Route — Try a bounded automation → Building a Small Automation and a low-risk personal-workflow lab idea. The first project needs synthetic inputs, limited authority, preview-only behavior, and recovery rules; it is not production automation.
  • Developing Route — Share and maintain a project → Publishing Your Work, Git and GitHub for Learners, Deploying Version 2, and a static-project-page lab idea. These are proposed packages without source links. Sharing is optional; the derived map keeps these unbuilt selections in Developing Route, not an available Optional Branch.

Agentic Coding gaps and relationships

  • Runnable safe repository setup and the referenced Voice Auditions project inputs remain missing core inputs for the signature lab. Its existing source and Notebook do not make it pilot-ready. Provider-currentness, secrets-practice, accessibility, and learner-pilot review remain open.
  • Planning, paired review, and mock testing are valid participation. The current Activity and Notebook require a personal provider account and live audio for full completion, while the facilitator guide accepts documented mock evidence. This mismatch is recorded for the subsequent artifact pass, not repaired or hidden here.
  • Provisional timing is kept in the facilitator guide for refinement after pilot evidence.
  • Prompting and Context Engineering remain primary to AI Literacy without reciprocal Agentic Coding assignments. Safety remains primary to AI Literacy and related to Curiosity; its Agentic Coding support role is a candidate relationship. The TTS lab’s existing related modules and Tracks are preserved.
  • A lower-friction beginner environment and the game/automation/sharing packages remain missing. Earlier orientation, planning, changed-file explanation, and acceptance-testing ideas are historical inputs; the Track loop does not claim separate artifacts for them.
  • The Track remains Draft / Drafting, owner Unassigned. Source presence in its review map means a file exists, not that curriculum is ready. Demonstrations are Coming Soon. Local completion, publication, deployment, and production use are distinct decisions; voice cloning remains idea-only.

The Agentic Coding Track Guide is the current learner route. The historical Track audit preserves the old inventory, dependencies, MVP questions, and checkpoint references as evidence, not another current curriculum inventory.

AI Readiness and Risk Assessment Support

Promise: Understand how work actually happens, preserve what works, and decide where AI can help, what needs better controls, and what should remain human-led.

  • Core → Friction Mapping — Understanding Work Before Recommending Solutions, the signature module, remains Sketch / Planned, owner Unassigned. Its in-page practice is the current short entry. No canonical signature Lab is assigned yet.
  • Shared Support → AI Is a Tool, Not the Organizing Frame, Seed / Planned, is Friction Mapping’s stated preparation. Conversational Privacy and Relationships with Conversational AI remain Sketch / Planned and related to AI Readiness. Safety and Reality Check are Draft / Drafting support candidates from AI Literacy. The guide features Conversational Privacy’s Beta What Does the Tool Need? and its Notebook as privacy support, not a replacement signature Lab.
  • Developing Route — Understand the work → Friction vs Pain, Working but Person-Dependent, and Preserve What Already Works, all Seed / Planned. Information-Flow Discovery Before Automation is a proposed module without a source page. Their guided Lab packages remain missing.
  • Developing Route — Decide what to delegate → Decision Ownership Before Delegation, Seed / Planned. Its Decision Ownership Map and Delegation Ladder and Control Plan remain candidate artifacts; they do not authorize automation or expansion of authority.
  • Developing Route — Prepare for dependence → Becoming an Informed Technology Consumer, Sketch / Planned, and its Consumer Reports for Emerging Technology lab, Alpha; Resilience and Outage Planning remains Seed / Planned. The consumer lab’s Notebook is Coming Soon, and a guided outage/recovery Lab is missing.
  • Optional Branch — Communication and images → Customer Communication Before AI Drafting, Seed / Planned; How Technology Changes the Ecology of Communication and Brand Images in the Age of Generative Editing, Sketch / Planned. The latter’s Generative Image Modification Lab remains Alpha, with its Notebook Coming Soon.
  • Developing Route — Other applications and deferred depth → Secure Photo-Based Triage and What Happens After Intake, Seed / Planned; When AI Starts Arguing Instead of Thinking and Designing Systems That Can Admit They Are Wrong, Seed / Deferred. AI Story Reality Check remains an exercise idea, not a published Lab or second signature entry.

AI Readiness gaps and relationships

  • Identifying the Squeaky Wheel is a proposed signature Lab with an internal planning concept, not a canonical Lab source. The shared package and standalone Notebook are missing. The derived review map records a proposed Lab, while the concept link remains visible for feedback.
  • The concept’s Mermaid maps and toolkit-ready outputs need reconciliation with the module’s paper/discussion practice and lack of a formal-record requirement. No diagramming software or AI tool becomes a Track requirement. The readiness loop is Scope → Map → Notice → Investigate → Decide; “Decide” may mean investigate more, improve without AI, explore bounded assistance, preserve a practice, or keep work human-led.
  • What Does the Tool Need? remains primary to Conversational Privacy and related only to AI Literacy in its lab metadata. Safety and Reality Check retain their AI Literacy/Curiosity relationships. Their featured AI Readiness use is a candidate handoff; no reciprocal metadata, ownership, or dependencies change.
  • The Track remains Draft / Drafting, owner Unassigned. Source presence in its review map means a file exists, not that a package is ready. Facilitator demonstrations remain Coming Soon; timing, accessibility, privacy, alignment, and learner-pilot evidence remain open.
  • Keep the sibling AI Readiness Kit’s proprietary assessment sources separate. This learner Track is not a finished client assessment, qualification, or authorization to change business systems. Reserved decisions on vocabulary, delegation-ladder stages, tacit-context examples, and proprietary artifacts remain open.

The AI Readiness Track Guide is the current learner route. The historical Track audit preserves the previous seven-module candidate path, July ideation, inventories, MVP questions, and reserved decisions as evidence, not another current curriculum inventory.

Study Time

Promise: Use AI to explore an explanation, practice what you are learning, and check your understanding—while keeping the thinking your own.

  • Core → AI for Learning: Tutor, Quizmaker, Simulator, the signature module, remains Seed / Planned, owner Unassigned. It is a planning source, not a finished tutoring lesson. The intended loop is Choose a learning goal → Try → Get help → Check → Try again.
  • Shared Support → Trust, But Check the Wires, Seed / Planned, remains the signature module’s stated preparation. Prompting, Conversation Engineering, and Conversational Privacy remain Sketch / Planned; Safety and Reality Check remain Draft / Drafting. The guide features Prompting’s Beta One Task, Three Conversations and Conversational Privacy’s Beta What Does the Tool Need?, each with its existing Notebook, as support rather than study-specific Labs. Relationships with Conversational AI remains Sketch / Planned and is an adult support candidate, with a separate youth evidence and safeguarding review required.
  • Developing Route — Understand something → Explaining at Different Levels and Study Prompt Patterns are proposed module directions without source pages. Try, Check, Explain supplies the first prepared explanation practice; broader examples and learner-pilot evidence remain needed. These ideas may belong inside the signature rather than in separate modules.
  • Developing Route — Practice what you know → Building a Quiz and Creating a Simulation are proposed module directions without source pages. Change One Thing, Alpha, supplies initial simulation practice and a debrief with explicit hand-run rules. Try, Check, Explain includes an attempt after a hint; full quizmaking and validated question banks remain missing.
  • Optional Branch — Make a learning tool → The signature module’s Module to Interactive Single-Page Application, Beta, includes a deterministic context-practice prototype, Notebook, learner guide, and facilitator guide. Using and critiquing the prototype is a non-coding path in those guides; building or adapting it is optional. It is not a live AI tutor and serves a different purpose from Try, Check, Explain.
  • Developing Route — Deferred depth → Current Events Need Current Context → Current Event Retrieval Check; History Beyond the First Answer → History Surfacing Lab. Both modules remain Ideation / Deferred and both Labs Alpha · idea packages, with missing example packets, protocols, Notebooks, and learner/facilitator materials.

Study Time gaps and relationships

  • Try, Check, Explain, Alpha, now supplies the guided study Activity, reference packet, Notebook, and two prepared examples. Human and learner-pilot review remain open. The live activity requires chatbot access with partner/facilitator operation valid; viewing an example alone is preparation. Learner accounts, recording, and coding are not required.
  • The signature module stays primary to Creative AI Makerspace and now names AI Literacy and Study Time as related Tracks. Its Beta Lab retains Makerspace/AI Literacy and its Context Engineering relationship. Conversational Privacy, Current Events, and History already name Study Time; most other support modules and both featured support Labs do not. Those additional handoffs remain candidates for editorial review.
  • The Beta app Activity and standalone Notebook now carry the learner/facilitator guides’ existing complete route: use and critique the supplied prototype. Builder design records are optional extensions.
  • Youth/school participation needs age, tool-access, consent/safeguarding, school-policy, and example review. Relationships with Conversational AI is adult-focused, not a ready youth lesson. Checking allowed help and source evidence belongs throughout the learner route; Checking the Answer and Learning Without Cheating remain historical module ideas rather than new artifacts.
  • The Track remains Draft / Drafting, owner Unassigned. Source presence in its review map does not establish curriculum readiness. The guided study and simulation continuations each have two prepared written demonstrations; quizmaking and tool-building route demonstrations remain Coming Soon. Existing module and Lab statuses are unchanged.

The Study Time Track Guide is the current learner route. Its historical Track audit preserves the original inventory, dependencies, MVP questions, and artifact-alignment evidence outside the Track catalog.

Fun for the Family

Promise: Use AI to play, create, and learn together, with room for every generation to contribute.

  • Core → Family Learning Lab, the signature module, remains Seed / Planned, owner Unassigned. Despite its name, it is a module seed without an assigned canonical Lab. The intended loop is Choose together → Give AI a job → Make or play → Notice → Decide together.
  • Shared Support → Prompting Is the Door, Not the Destination, Sketch / Planned, remains the signature’s stated dependency. AI Without the Hype and Safety remain Draft / Drafting; Before You Paste and Conversational Privacy remain Sketch / Planned. Relationships with Conversational AI is a Sketch / Planned adult/caregiver reference, not a family prerequisite or a child-ready lesson; separate youth evidence and safeguarding review is required.
  • Developing Route — Make a story or game → Bespoke Stories and Family Quiz Games are proposed module directions without source pages. Guided activities, reviewed fictional examples and answer keys, and mixed-age roles are missing. These choices may belong inside the signature instead of becoming separate modules.
  • Developing Route — Explore a shared interest → Connections to the Curiosity and Study Time guides, both Draft / Drafting. These are Track connections, not another inventory of their modules and Labs. A family-specific inquiry path and reviewed sources remain missing.
  • Developing Route — Remember with care → Recreating a Special Moment and Remembering the Past Safely remain proposed module directions without sources. Consent, emotionally sensitive facilitation, source/permission records, and distinctions among memory, checked history, uncertainty, and generated invention need development before personal-memory workshops.
  • Optional Branch — Existing creative practice → Creative Latitude, Draft / Drafting, owns From Inspiration to Invention, Beta, with its existing Notebook and paper/nonvisual route. Make Something Weird: Creative AI Lab, Sketch / Planned, owns Build a Tiny Virtual Museum, Alpha, with a Notebook, Blender requirement, and source/rights/credit planning. Both remain supporting options, not substitutes for the family starter or evidence of mixed-age readiness.
  • Optional Branch — Adult/caregiver safety → Pause Before You Pay: Scam Awareness Basics, Sketch / Planned, is a candidate from AI Literacy with safety review still open. It does not complete the proposed Scam Awareness for Families package and is not the playful starter.

Family gaps and relationships

  • Shared family play is a descriptive starter-Lab candidate, not a settled title or source package. Its Activity, fictional prompt/example packet, self-contained Notebook, and mixed-age facilitator guide are missing. Shared-AI and supplied-example versions both need design; no child account, personal photo, paid subscription, or public sharing should be required.
  • Family Learning Lab remains primary to Makerspace, with Prompting as its dependency, and now names Fun for the Family as a related Track. Creative Latitude, From Inspiration to Invention, and Conversational Privacy already name this Family Track. The museum, other support modules, adult relationship reference, and scam-awareness branch remain candidate handoffs; their metadata, ownership, and dependencies are unchanged.
  • Conversational Privacy’s dedicated family-use scenario README is a placeholder. The family AI-use agreement and Creative Show-and-Tell remain original ideas, not new packages. Optional sharing in the guide does not create a Show-and-Tell module or make one person’s permission cover everyone’s information.
  • Existing creative Lab estimates are not family-pilot evidence. Preserve the Beta and Alpha labels alongside their open learning-design, accessibility, rights, and pilot reviews, including From Inspiration to Invention’s counsel/legal review boundary before external or commercial use. Neither package requires live AI; their no-AI completion routes stay valid.
  • The Track remains Draft / Drafting, owner Unassigned. Age ranges, operator roles, tool suitability, consent/safeguarding, accessibility, meaningful participation, and support/stopping options remain open. Demonstrations are Coming Soon. Source presence does not establish family-workshop readiness.

The Family Track Guide is the current learner route. Its historical Track audit preserves the old inventory, dependencies, MVP questions, and artifact gaps outside the Track catalog.

Building Knowledge Bases / Second Brains

Promise: 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.

  • Core → Context Engineering, Sketch / Planned, owner Renaissance Solutions, is the signature module. Its module-owned Context Cleanup, Beta, is the short entry; Build the Brief Before the Work, Beta, is the longer practice. Both have standalone Notebooks and learner/facilitator materials. They prepare task-specific context, not a maintained knowledge base.
  • Shared Support → Conversation Engineering and Before You Paste: Privacy and Data Boundaries, both Sketch / Planned, and Reality Check for AI, Draft / Drafting. These support conversation, privacy, and verification without adding a second mandatory core.
  • Developing Route — Build a small collection → What Is a Knowledge Base?, Building a Second Brain, and Source Quality and Provenance are proposed module directions without sources. The starter-folder Lab idea needs a reviewed source set, purpose, naming, source records, index, guided Activity, standalone Notebook, and facilitator guide.
  • Developing Route — Connect and find → Knowledge Maps and Relationships and Retrieval and Verification are proposed module directions without sources. The five-document relationship-map Lab idea needs supported connections, answer-to-source checks, and examples where the collection cannot answer. Start with manual lookup, not assumed automatic retrieval.
  • Developing Route — Keep it trustworthy → Memory Types and Maintaining Stored Memories are proposed module directions without sources. The stored-chatbot-memory review Lab idea needs fictional examples, update/conflict scenarios, permissions, retention decisions, and a maintenance record. Product memory, files, notes, and conversational context are not interchangeable.
  • Optional Branch — Context experiments → How Context Constrains the Continuation and Contradictions in Context, both Beta, remain owned by Context Engineering. Both have Notebooks and learner/facilitator materials; their required-document collections remain Coming Soon. They deepen context judgment, not collection-building readiness. Tool-specific setup and automated retrieval remain later developing directions without invented source links.

Knowledge Bases gaps and relationships

  • The intended loop is Choose → Gather → Organize → Use → Check → Maintain. The missing bridge is from one context packet to a collection that can be revisited, searched, checked, and updated. No new module, Lab, Notebook, tool tutorial, or demonstration is created in this pass.
  • Context Engineering retains AI Literacy as primary and now names Knowledge Bases as a related Track, reflecting the approved signature role. All four Labs retain their AI Literacy relationships; additional cross-Track memberships remain candidates. The old Context Engineering Basics idea points to the existing module; the old pile-versus-curated-packet idea is served in part by the entry practice, not duplicated as a new Lab.
  • Context Engineering keeps Conversation Engineering in its dependency metadata and now names it in Recommended Preparation.
  • Context Cleanup supports paper-first completion. The longer Lab and optional experiments include output-comparison steps; use an appropriate live operator or a facilitator-prepared comparison set. The module’s supplied-example option does not mean every Lab includes a reviewed no-tool packet. Keep live, observed, and supplied evidence distinct.
  • Use public or fictional starter material and a familiar folder, paper index, or note tool. Obsidian is an option, not a requirement. No paid account, personal archive, upload, or public presentation is required. Tool access, permissions, memory, and retention behavior need checking at actual use.
  • The Track remains Draft / Drafting, owner Unassigned. All four Labs retain learning-design, accessibility, and pilot review, with safety review also open for Contradictions in Context. Demonstrations remain Coming Soon. Source presence and Beta labels do not establish workshop readiness.

The Knowledge Bases Track Guide is the current learner route. Its historical Track audit preserves the old inventory, dependencies, MVP questions, and artifact-alignment evidence outside the Track catalog.

Systems Thinking and AI Engineering

Promise: 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.

  • Core → How Technology Changes the Ecology of Communication, Sketch / Planned, owner Unassigned, is the signature module. Its embedded Communication Ecology Map introduces the systems view; it is not a canonical Lab package. The standalone Activity, Notebook, reviewed example packet, and facilitator package remain missing.
  • Shared Support → Conversation Engineering with Stay, Steer, or Start Over, and Context Engineering with Build the Brief Before the Work. Both modules remain Sketch / Planned; both Labs remain Beta, with standalone Notebooks and learner/facilitator materials. These are bounded practice choices, not another AI Literacy core or substitutes for the signature package.
  • Developing Route — Follow the information → Memory and Retrieval is a proposed module without a source. The system-decomposition Lab idea needs a reviewed information-flow example, source and handoff labels, an Activity, and a Notebook. Conversation and context practice supports parts of this route, not the whole system.
  • Developing Route — Understand action and authority → Decision Ownership Before Delegation, Seed / Planned, is a candidate from AI Readiness. Its ownership map and control plan remain candidate artifacts. The permissions, memory, observability, and oversight Lab idea remains proposed without a source; review overlap before building another package.
  • Developing Route — Evaluate and improve → Designing Systems That Can Admit They Are Wrong, Seed / Deferred, is a candidate from AI Readiness, not a ready design framework. Observability is a proposed module without a source. A beginner-friendly failure-and-recovery example and guided evidence comparison are still missing.
  • Optional Branch — Technical and evaluation depth → AI Runtimes, Tools and Agents, Designing AI Systems, and Deploying Version 2 remain proposed module ideas without sources. The vendor-pattern comparison Lab is also proposed. When the Average Lies: Simpson’s Paradox in AI Evaluation remains Sketch / Deferred: an imported synthetic-data packet awaiting statistical-methods, accessibility, learning-design, and pilot review, not validated curriculum.

Systems Thinking gaps and relationships

  • The intended loop is Map → Trace → Set boundaries → Test → Observe → Revise. Begin with people, information, trust, and decisions around AI. Technical architecture remains optional; no coding, deployment, learner account, or live-system access is required.
  • The signature retains AI Literacy as its primary Track and AI Readiness as related, and now adds Systems as a related Track. Shared modules and Labs retain their primary homes; additional Systems support memberships remain candidates. The two governance candidates retain AI Readiness placement; When the Average Lies retains Systems placement. Dependencies, statuses, and ownership are unchanged.
  • First build priority is the Communication Ecology Map package, followed by one short reviewed mapping pilot. Paper, discussion, supplied examples, and observing a facilitator are valid routes. The missing signature examples are not already supplied merely because the module lists them. Demonstrations remain Coming Soon.
  • Shared Labs retain learning-design, accessibility, and pilot review needs. Recommended Preparation exposes Context Engineering’s preserved Conversation Engineering dependency. Prepare a live operator or suitable comparison set for output steps; a single supplied scenario or sorted brief is not a complete comparison.
  • Preserve evidence boundaries: observations, assumptions, AI suggestions, and outside verification differ. Output changes or model self-report do not prove that all context was used. Use public or fictional examples, not private records or live permissions changes.
  • Keep the deferred evaluation packet’s instructor materials separate from learner materials. Source presence does not establish curriculum readiness. The Track remains Draft / Drafting, owner Unassigned; no new module, Lab, Notebook, example packet, or demonstration is created.

The Systems Thinking Track Guide is the current learner route. Its historical Track audit preserves the old inventory, dependencies, MVP questions, and artifact-alignment evidence outside the Track catalog.

Contributor and Mentor Development

Promise: 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.

  • Core → How to Turn a Lesson Into a Lab, Seed / Planned, is the signature. Its stated preparation is completion of several beginner modules. The intended first result is a bounded activity draft with a learner outcome, steps, safety boundary, and observable result—not a finished or approved Lab.
  • Shared Support — Reference documents, not additional curriculum → the Contributor Policy, Lab Contribution Workflow, Lab contributor template, module template, and facilitator notes template. These existing references support the work; they do not fill the derived map with extra modules or Labs or establish workshop readiness.
  • Developing Route — Signature package → the proposed “turn a concept into a lab outline” activity needs a complete Activity, standalone Notebook, reviewed examples, and facilitator guide. It has no canonical Lab source and is not a settled package title.
  • Developing Route — Write for learners → How to Write for Beginners Without Talking Down, Seed / Planned, with no stated dependencies. The dense-explanation rewrite Lab idea needs permitted examples and meaning-preservation checks; it has no source package.
  • Developing Route — Observe and improve → How to Capture Learner Friction, Seed / Planned, depends on the signature. Field Notes to Revision remains a proposed module without a source. The practice-session field-note Lab idea needs observation/interpretation examples, a minimal record, and revision practice.
  • Developing Route — Facilitate and review → Facilitation Basics and Review for Safety, Tone, and Clarity remain proposed modules without sources. The beginner-clarity/privacy-review Lab idea is also unbuilt. Guided practice, example feedback, escalation boundaries, and mentor-practice guidance remain missing.
  • Optional Branch → Consultant Readiness: Judgment, Scope, and Trust, Seed / Planned, remains later-stage exploration with its AI Readiness module sequence dependency unchanged. It is not certification, client-advisory authorization, a qualification threshold, or a promise of employment.

Contributor gaps and relationships

  • The intended loop is Notice a need → Agree scope → Make → Try → Review → Revise. Useful, ethical contribution is the center; not everyone needs to become an activity designer, facilitator, or consultant.
  • All four linked modules remain Seed / Planned, owner Unassigned, review status Not reviewed, and primary to this Track. None has a canonical Lab package or Notebook. No dependency or reciprocal relationship changes occur in this pass.
  • First build priority is the signature package, followed by one reviewed short pilot: shape an activity, have someone follow it, and revise one point of friction. Templates and a polished draft are not pilot evidence. Demonstrations remain Coming Soon.
  • The existing policy already distinguishes personal practice, assigned work, credit/payment terms, permission to use work, and RS review before external or commercial use. Assigned work needs terms before it begins; commercial/product use should be paid unless a separate written agreement says otherwise. This Track creates no new policy or assignment.
  • Contributor levels, mentor preparation, and review responsibilities remain open design work. Encouragement, formative feedback, artifact approval, independent final QC, and publication permission must stay distinct. Consultant readiness’s broad sequence dependency needs clarification during its artifact pass.
  • AI assistance is optional and bounded. Generated learner reactions are not observed learner evidence, and AI review is not independent human approval. Practice may use paper, speaking, observation, or a partner without a personal AI or GitHub account. Actual submissions retain the GitHub Issues, Project board, and linked pull-request workflow.
  • Use permitted material and collect minimal, non-identifying learner-friction notes with agreement before observing or recording. Keep self-walkthroughs, simulated examples, and real learner observations distinguishable. Do not create a learner-record collection system.
  • The Track remains Draft / Drafting, owner Unassigned. Additional Reading is preserved. Source links gather feedback without promoting curriculum. No module, Lab, Notebook, example packet, demonstration, assignment, policy, or operational workflow is created or rewritten.

The Contributor Track Guide is the current learner route. Its historical Track audit preserves the old inventory, dependencies, MVP questions, and artifact-alignment evidence outside the Track catalog.

Podcaster / Influencer

Promise: Use AI to support your public voice without losing authorship or audience trust.

  • Core — proposed signature → Voice and Persona Consistency. No module source exists. The intended result is a voice guide and an annotated AI-assisted draft with a human choice to keep, change, or decline. Core is an intended composition role, not evidence that the module exists or is ready.
  • Developing Route — Signature package → “Build a voice guide before asking AI to draft” is a proposed activity direction, not a settled Lab title. Comparison against a human voice standard belongs within that practice. The module, complete Activity, standalone Notebook, reviewed examples, and facilitator guide are missing.
  • Developing Route — Transform one idea → Transforming Content, Show Notes and Summaries, and Social Post Variations remain proposed modules without sources. The long-idea-to-multiple-formats Lab concept needs a permitted source and meaning-preservation checks; no Lab package exists.
  • Developing Route — Publish with care → Publishing Your Work remains proposed without a source. Customer Communication Before AI Drafting, Seed / Planned, is an existing business-focused candidate from AI Readiness with its Decision Ownership Before Delegation dependency unchanged. The publishing/review/attribution Lab idea is unbuilt.
  • Developing Route — Reach people without chasing every trend → Getting Attention and Being Noticed and Google Zero and Changing Discovery remain proposed modules without sources. How Technology Changes the Ecology of Communication, Sketch / Planned, provides a concept-led source; its Communication Ecology Map has no canonical Lab package or Notebook. Platform-specific guidance and the Google Zero working title need current evidence review, not implied growth promises.
  • Shared Support → Safety: Share Less, Notice More → What Else Came Along?, and Reality Check for AI → Reality Check for AI: Six Experiments. Both modules remain Draft / Drafting; both Labs remain Beta with standalone Notebooks. These support privacy and evidence questions without becoming new prerequisites.
  • Optional Branch — Speaking and technical voiceover → Public Speaking, Draft / Drafting, through its module-owned practice choices; Build a Safe Text-to-Speech Skill, Draft / Drafting, Builder level → Build a Safe Text-to-Speech Skill, Alpha Lab, and existing standalone Notebook. Tool-building is not the signature. Its Prompting and Context Engineering or equivalent safe-file preparation, credential boundaries, budget checks, and human listening remain in force.

Podcaster gaps and relationships

  • The intended loop is Intend → Set the voice → Ask → Compare → Check → Decide. “Voice” means language, perspective, and choices, not synthetic audio. A voice guide can evolve; it does not require a fixed persona or imitation of another person.
  • Personal and work-related creators share the entry; the customer-communication candidate is business depth, not a requirement for hobby creators. Speaking, recording, public posting, and audience-growth targets remain optional or outside the first practice.
  • First build the signature package, including a Notebook that works without the module page and a reviewed supplied-AI-draft route. Then pilot one short comparison and decision, gathering actual timing and friction. Live, partner/facilitator, text-first, and supplied-example access are intended routes; the missing signature packet does not yet implement them. Demonstrations remain Coming Soon.
  • Preserve meaning, facts, quotation context, source permissions, attribution, and disclosure decisions. Generated audience reactions are not audience research. Publication and any use of another person’s voice need separate human authority; the TTS source keeps cloning at idea status.
  • The existing customer-communication Seed has only a channel/template/escalation/approval inventory concept, not a Lab package. The ecology module has an embedded activity description, not a canonical Lab. Do not manufacture Lab links for either. These artifact gaps remain visible for the subsequent pass.
  • Track roles do not change reciprocal metadata: Customer Communication remains primary to AI Readiness; Ecology, Safety, and Reality Check remain primary to AI Literacy; Public Speaking remains primary to Curiosity; TTS remains primary to Agentic Coding. Additional Podcaster support links are composition selections, with reciprocal relationship review deferred to the artifact pass. The TTS Lab already lists Podcaster as a related Track.
  • The Track remains Draft / Drafting, owner Unassigned. No source status is promoted. No module, Lab, Notebook, example packet, demonstration, or publishing system is built in this pass; Additional Reading is preserved.

The Podcaster Track Guide is the current learner route. Its historical Track audit preserves the original ideas and artifact-alignment evidence outside the Track catalog.

Zero-to-Hero Agentic Literacy

Promise: Understand what changes when AI can act—choose what to delegate, set limits, and verify what happened.

  • Core — proposed signature → From Chatbot to Agent. No module source exists. The intended entry compares a chatbot answer with a tool-using plan for one small task, identifying permissions, approval points, verification, and a stop condition. Core is a composition role, not source availability or readiness.
  • Developing Route — Signature package → “Compare a chatbot answer to a tool-using assistant workflow” is a proposed activity direction, not a settled Lab title. The historical simple delegation checklist belongs within this first practice. The module, complete Activity, standalone Notebook, reviewed examples, and facilitator guide are missing. A live practice environment has not been selected or reviewed.
  • Developing Route — Choose tools and permissions → Permissions and Sandboxes; Tools, Actions, and Connectors; and the permission-identification Lab concept are proposed without sources. Missing: low-risk permission examples, a reviewed environment, denied-action examples, and a self-contained Activity/Notebook. Prompt instructions do not replace enforced access limits.
  • Developing Route — Bound context and memory → Memory in Agentic Systems remains proposed without a source. Missing: practice distinguishing conversation, saved memory, files, and retrieved material, including stale/untrusted content and access/persistence boundaries. No completed agent-memory Lab is implied by existing context practice.
  • Developing Route — Review and recover → Planning and Review Loops; Deploying Version 2; and the pre-action plan-review Lab concept are proposed without sources. Missing: plan/action/result comparisons, failure and partial-completion examples, and stop/recovery practice. Updating and deployment are later depth, not entry requirements.
  • Shared Support → Conversation Engineering → Stay, Steer, or Start Over; Context Engineering → Build the Brief Before the Work; Safety: Share Less, Notice More → What Else Came Along?; Reality Check for AI → Reality Check for AI: Six Experiments. Conversation and Context remain Sketch / Planned; Safety and Reality Check remain Draft / Drafting. All four featured Labs are Beta, with standalone Notebooks. They support judgment, not proof of live-agent competence.
  • Optional Branch — Organizational delegation → Decision Ownership Before Delegation, Seed / Planned, Business level, owned by Mike, remains later depth from AI Readiness, with its Friction Mapping dependency unchanged. Its Decision Ownership Map and Delegation Ladder and Control Plan are concepts without a canonical Lab or Notebook. Why High-Value Automation Can Still Be a Bad First Move remains a proposed module without a source.
  • Optional connections, not additional curriculum assignments → Agentic Coding for building tools, and Systems Thinking and AI Engineering for whole-system ownership, evaluation, and recovery. Neither is a required graduation destination.

Agentic Literacy gaps and relationships

  • The intended loop is Choose → Bound → Review → Authorize → Observe → Verify and decide. Answer, plan, permission, attempted action, completed action, and verified result must remain distinguishable. More autonomy is not assumed progress; stopping, narrowing, or using a simpler tool are valid outcomes.
  • Basic AI Literacy remains preparation. Conversation Engineering’s metadata depends on Prompting; Context Engineering’s metadata depends on Conversation Engineering. Both learner pages now name those existing dependencies as Recommended Preparation. This clarification adds no new prerequisite and leaves dependency metadata intact.
  • First build and review the signature’s plan-comparison package, including a Notebook that works without the module page and supplied examples that support account-free, paper, partner, observer, and facilitator participation. Pilot the comparison and delegation decision before claiming live operation. The packet is missing; these participation routes are design commitments.
  • A live extension needs disposable fixtures, least-necessary enforced access, visible action records, tested stop/reset behavior, denied-action examples, and a checkable result. A written plan is not execution approval or evidence that the environment is contained. Do not connect personal accounts, send real messages, make purchases, or require irreversible public actions in the entry pilot. Demonstrations remain Coming Soon.
  • Verification must use observed outputs or state beyond the assistant’s success claim. Retrying can duplicate completed actions; revoking access does not undo past actions. Recovery and reset need evidence, not reassurance. Saved context and instructions inside retrieved material are not new human authority.
  • All four support modules remain primary to AI Literacy; all featured Lab primary-module relationships remain unchanged. Decision Ownership remains primary to AI Readiness. Additional Agentic Literacy support links are composition selections; reciprocal metadata review is deferred to the artifact pass.
  • The Track remains Draft / Drafting, owner Unassigned. Additional Reading is preserved. No module, Lab, Notebook, example packet, demonstration, practice environment, status promotion, or permission system is created.

The Agentic Literacy Track Guide is the current learner route. Its historical Track audit preserves the original outline, dependencies, MVP questions, and artifact-alignment evidence outside the Track catalog.

Local Hosting

Promise: Choose when local or self-hosted tools fit, and understand who will secure, maintain, and recover them.

  • Core — proposed signature → What Local Hosting Means. No module source exists. The intended entry compares hosted, local, and hybrid options for one small use case, then records data flow, access, upkeep ownership, costs, failure/recovery, evidence, and a learner decision. Core describes the proposed role, not availability or readiness.
  • Developing Route — Signature package → “Compare hosted, local, and hybrid options for a simple use case” is an activity direction, not a settled Lab title. The module, complete Activity, standalone Notebook, reviewed comparison packet, and facilitator guide are missing. The hosting decision record belongs within this first practice. No installation environment has been selected.
  • Developing Route — Choose where it runs → Local Models vs Hosted Models; When Not to Self-Host. Both are proposed without sources. Missing: reviewed placement and data-flow examples, capability/access/cost/support comparisons, and a case where staying hosted fits better. A local interface is not evidence that every service or data copy is local.
  • Developing Route — Protect access and commitments → Accounts, Keys, and Secrets; Spend Limits and Vendor Changes; and the account/secret/update/support ownership Lab idea are proposed without sources. Missing: fictional examples, reviewed access and spending boundaries, lost-access scenarios, and a complete Activity and Notebook.
  • Developing Route — Maintain and recover → Backups and Restores; Service Availability; Updating Safely; and the backup-checklist and outage-role-play Lab ideas are proposed without sources. Missing: worked failure/fallback cases, ownership decisions, a complete Activity and Notebook, and a reviewed environment for later update and restore tests. A checklist or role-play is not a tested restore.
  • Developing direction — Later installation → No additional module or Lab is declared. Environment selection, prerequisites, disposable materials, reviewed install/update/uninstall and reset/restore steps, account/secret/network safeguards, accessible alternatives, and support remain gaps. Installation is not required for the comparison entry.
  • Shared Support → Becoming an Informed Technology Consumer → Consumer Reports for Emerging Technology; Conversational Privacy → What Does the Tool Need?. Both modules remain Sketch / Planned. Consumer Reports is Alpha, with fictional product cards and decision materials; its Notebook is Coming Soon. What Does the Tool Need? is Beta, with a standalone Notebook. These support decision and disclosure practice, not operational readiness.
  • Optional Branch — Organizational resilience → Resilience and Outage Planning, Seed / Planned, Business level, owner Unassigned, remains AI Readiness depth. Its outage-plan Lab is a concept without a canonical package or Notebook. The Safe AI Use for Small Business or equivalent dependency remains unresolved in the source’s own status notes.
  • Optional Branch — Hosted-provider tool-building → Build a Safe Text-to-Speech Skill, Draft / Drafting, Builder level → Build a Safe Text-to-Speech Skill, Alpha, with a standalone Notebook. This existing Agentic Coding package demonstrates local secret-handling boundaries, budget guardrails, and revocation response for a hosted provider; it is not a self-hosting Lab. Its technical prerequisites remain unchanged and outside the entry.
  • Optional connections, not additional curriculum assignments → AI Readiness and Risk Assessment Support for organizational decisions and Agentic Coding for building tools.

Local Hosting gaps and relationships

  • The intended loop is Choose a need → Map the data → Name the owners → Compare → Decide → Review. Staying hosted, hybrid use, postponement, or adding no tool can be valid outcomes. Self-hosting describes operating responsibility; locality alone does not prove privacy, security, offline operation, or low total cost.
  • Build and review the signature comparison package first, including a Notebook that works without the module page. Account-free supplied examples, paper, discussion, partner direction, and observation are intended participation routes; the packet does not yet exist. No live AI use, coding, purchase, or installation is required for this decision practice.
  • Basic AI literacy, privacy/data boundaries, continuity concepts, and comfort with accounts/files/devices remain preparation topics. Technical prerequisites need definition before later installation work. Do not connect real accounts, expose a service publicly, or use sensitive files and credentials as comparison fixtures.
  • Pilot a short comparison after package review and record actual timing, terminology and access friction, and the learner’s decision. Keep supplied evidence, assumptions, proposed tests, and observed results distinct. Demonstrations remain Coming Soon. A completed decision record does not prove installation, security, or recovery competence.
  • Shared Support selections preserve canonical module/Lab parent relationships and existing reciprocal Track metadata. Conversational Privacy now names its existing dependencies as Recommended Preparation, and its Practice section links directly to its primary Lab, What Does the Tool Need? Additional Local Hosting memberships remain candidates for editorial review.
  • Resilience’s unresolved prerequisite and concept-only practice remain visible. The text-to-speech Lab already lists Local Hosting as a related Track; its module remains primary to Agentic Coding. No hosted-provider capability is reclassified as self-hosting.
  • The Track remains Draft / Drafting, owner Unassigned. Additional Reading is preserved. No module, Lab, Notebook, example packet, demonstration, installation environment, dependency, primary relationship, or curriculum status is created or rewritten.

The Local Hosting Track Guide is the current learner route. Its historical Track audit preserves the original outline, dependencies, MVP questions, and artifact-alignment evidence outside the Track catalog.

Relationship Map

These topics should be treated as shared components. Some may become full modules plus short reusable explainers that can be embedded elsewhere.

Topic Used By Relationship
Prompting Is The Door AI Literacy, Makerspace, Study Time, Systems Engineering, Agentic Coding Core practice for making useful requests, adding context and boundaries, inspecting assumptions, and revising outputs without treating prompts as magic.
Conversation Engineering AI Literacy, Contributor Development, Makerspace, Study Time, Systems Engineering Keeps human intent present across multiple turns through steering, comparison, constructive friction, checkpoints, and stopping rules.
Becoming Curious Again Curiosity Uses It Starts With a Question as its signature lab: notice, shape one question, choose a bounded live generative AI job and tool, explain where a useful result came from and what supports it or still needs checking, and make a learner-owned next-step decision.
Safety: Share Less, Notice More AI Literacy, Curiosity Teaches private and third-party information boundaries, hidden file content, metadata, indirect prompt injection, limited tool authority, and share / sanitize / substitute / stop.
Public Speaking Curiosity, AI Literacy Uses learner-first reflection, evidence-bounded observations, one chosen change, and a second attempt without grades, personality claims, accent grading, or required recording.
Reality Check for AI AI Literacy, Curiosity Uses one six-experiment scientific-method sequence to test self-description, framing, context, confirmation bias, source checking, and a revised mental model without turning the work into prompt engineering.
Context Engineering AI Literacy, Knowledge Bases, Agentic Literacy, Systems Engineering, Agentic Coding Helps learners select, inspect, maintain, bound, and verify the informational environment surrounding a task.
Current Events Need Current Context AI Literacy, Study Time Distinguishes current information that must be retrieved or supplied from information already available in the conversation, then requires validation of what the search actually found.
History Beyond the First Answer AI Literacy, Study Time Shows that a first historical response may favor prominent, strongly connected events and teaches learners to widen the frame, compare coverage, and consult reviewed sources.
Constraint Thinking AI Literacy, AI Readiness, Agentic Literacy, Systems Engineering Extends context work by helping learners identify the goals, boundaries, sources of truth, decisions, and conflicts that define the problem before seeking an AI-supported solution.
The Constraint Landscape AI Literacy, Agentic Literacy, Systems Engineering Explains how conversational constraints accumulate, drift, disappear, and conflict over time; supports deliberate clarification, summarization, restarting, and later collaboration patterns.
Chatbot Modes AI Literacy, Study Time, Makerspace, Agentic Literacy Helps learners understand when they are planning, brainstorming, world building, tutoring, or tool building.
Before You Paste AI Literacy, Makerspace, Family, Study Time, Agentic Literacy, Local Hosting Safety prerequisite for personal, family, client, and business examples.
Conversational Privacy AI Literacy, AI Readiness, Makerspace, Family, Study Time, Privacy and Information Handling Helps learners decide what information belongs in a chatbot conversation, reduce unnecessary precision, protect other people’s information, and understand shared account/device exposure.
Relationships with Conversational AI AI Literacy, AI Readiness, Makerspace, Family, Study Time, Privacy and Information Handling Helps learners distinguish real human experience from evidence about a conversational system, evaluate task-specific reliance, notice role expansion, and preserve human judgment around emotionally fluent systems.
Memory Types Knowledge Bases, Agentic Literacy, Systems Engineering, Family, AI Readiness Explains stored memories, project context, organizational knowledge, and personal memory boundaries.
Friction vs Pain AI Readiness, Contributor Development, Agentic Literacy Teaches nonjudgmental opportunity discovery and prioritization.
Friction Map AI Readiness, Contributor Development, Business Continuity, Agentic Literacy Likely needs a full deep dive and a short reusable explainer. Its AI Readiness use includes mapping roles into decision loops and context gaps before recommendations.
Information-Flow Discovery AI Readiness, Systems Engineering, Agentic Literacy, Knowledge Bases Prerequisite before automation, delegation, or context design.
Content Transformation Makerspace, Study Time, Podcaster / Influencer, Contributor Development Converts content across audience, age level, format, and mode.
Decision Ownership AI Readiness, Agentic Literacy, Systems Engineering, Local Hosting Should appear before delegation, automation, or tool action. Its AI Readiness use includes staged bounded delegation, deterministic controls, and rollback conditions.
Customer Communication Standards AI Readiness, Podcaster / Influencer, Business Communication Standardizes voice before AI drafting to reduce drift.
Brand Images And Generative Editing AI Readiness, Makerspace, Podcaster / Influencer, Privacy and Information Handling Helps organizations make intentional choices about public brand images, image editing, practical exposure, verification, and response.
Becoming An Informed Technology Consumer AI Readiness, Makerspace, Family, Small Business, Privacy and Information Handling Helps learners choose, test, renew, downgrade, replace, or leave subscriptions, services, connected devices, and AI-enabled tools without making AI the organizing frame.
Rights And Provenance AI Readiness, Makerspace, Podcaster / Influencer, Family, Privacy and Information Handling Reusable follow-on lab for source records, metadata, permissions, markings, and provenance evidence.
Business Continuity AI Readiness, Local Hosting, Systems Engineering Connects outages, accounts, vendors, backups, and operational resilience.
Publishing Your Work Makerspace, Agentic Coding, Podcaster / Influencer, Contributor Development Teaches sharing and review without turning every class into a web project.
Deploying Version 2 Agentic Coding, Local Hosting, Systems Engineering, AI Readiness Teaches upgrade, patch, vendor, model, and operating-system change planning.

Candidate Reusable Submodules

These should not be published as standalone products yet. Treat them as embedded explainers, glossary terms, cheatsheets, or short labs until repeated use proves they need their own source files.

Short definitions, disclaimers, safety language, and standard warnings belong in learning-library/ so modules can link to them or embed them without copy/paste drift. Use docs/embed-policy.md as the source rule for when [[...]] links or ![[...]] embeds are appropriate.

  • What is a friction map?
  • Safe paste rules.
  • Stored memory review.
  • Memory types.
  • Deterministic vs probabilistic processes: models may interpret, predict, classify, or propose; records, limits, authorization, and transactions need controls outside the model.
  • Functional decomposition: split a role or goal into tasks, decisions, actors, states, and feedback loops before selecting technology.
  • Tacit context and weak signals: capture the limits of informal, physical, social, historical, and relational context without treating people as data sources to harvest.
  • The grace gap and error budgets: assess failure by consequence, detectability, reversibility, recovery, and trust cost rather than average accuracy alone.
  • Delegation ladder: move from shadowing to bounded action only through evidence and controls; expanded autonomy is not the default destination.
  • What is a token?
  • What is attention?
  • What is drift?
  • What is refactoring?
  • What is a use case?
  • Accounts, keys, and secrets.
  • Backup and restore basics.
  • Source quality and provenance.
  • Human review checkpoint.
  • Four-question prompt model.
  • Repair loop.
  • Two safety gates.
  • Conversation cycle.
  • Thread-reconstruction checks.
  • Constructive-friction prompts.
  • Conversation checkpoint.
  • Continue, steer, summarize, restart, or stop.
  • Five context questions.
  • Five context failure modes.
  • Context hierarchy.
  • Add, correct, remove, or isolate.
  • Source-of-truth reminder.
  • Active-context checkpoint.
  • Brand-control spectrum.
  • Image exposure checklist.
  • Official verification channel.
  • Renewal review.
  • Experiment graduation.
  • Exit path.
  • Conversational privacy pause.
  • Reduce the precision.
  • Shared account warning.
  • Mine, theirs, or ours.
  • Four digital relationship questions.
  • Trust by task.
  • Digital maintenance check.
  • Weight test.

Holes To Fill

  • Two-track readiness: Use the AI Literacy and Curiosity gap reports to identify missing content, facilitator assets, and human evidence. Do not fill those gaps until the specific curriculum work is approved.
  • Audience boundaries: Decide which tracks are for public community classes, small-business clients, internal contributors, future consultants, families, students, or advanced builders.
  • MVP threshold per track: Define what counts as “track MVP.” A likely rule is an intro, 3 to 5 mapped modules, 1 hands-on lab, a take-home artifact pattern, and clear dependencies.
  • Tool-specific split strategy: Decide whether tool intros split by mode, job-to-be-done, learner role, or vendor. Default to mode or job-to-be-done.
  • Family and privacy guardrails: Define consent, age, photo, family-history, and emotionally sensitive memory boundaries.
  • Local-hosting prerequisites: Decide the minimum technical level before learners touch installs, secrets, ports, backups, or network exposure.
  • Reusable submodule criteria: Decide when a repeated concept becomes a source file instead of staying as an embedded explainer.
  • Publishing boundary: Decide when learners publish work publicly, privately, locally, or not at all.
  • AI Readiness overlap: Keep the Learning Lab supportive of the AI Readiness Kit without absorbing its source artifacts.
  • Contributor workflow: Define how track-map ideas become GitHub Issues, module sketches, contributor briefs, and review tasks.
  • Vocabulary scope: Decide which terms need beginner analogies, advanced definitions, or both.

Next Planning Pass

  1. Choose which expansion track should be nearest to MVP after the current V0 tracks.
  2. Identify 3 to 5 module candidates per selected track that already overlap with existing modules.
  3. Create contributor issues only for the next small batch of track/module work.
  4. Keep the brainstorm visible, but do not turn every idea into a module folder until it has a clear owner, audience, and next use.

Source: docs/track-map.md