Project Ops

AI Literacy — Historical Track Audit

Project operations source: AI Literacy — Historical Track Audit.

This is historical evidence, preserved from the Track Guide at source checkpoint 11887d2. The matching Astro checkpoint is 8ed5c94. Those commits preserve the Curiosity work and shared Track contract before the AI Literacy composition pass.

The original wording below includes superseded route choices, old status labels, conflicting ownership statements, and unavailable-feedback claims. It records what informed the decisions; it does not describe current curriculum readiness. The current Track Guide and shared Track Map carry the current composition.

Follow-up relationship question: Brain Dump to Memo is still assigned primarily to When the Bot Sounds Right but Is Not. The Track pass does not change that relationship. Review its fit as applied writing practice when designing Sounds Right—Check It as a verification lab. Becoming an Informed Technology Consumer remains primary to AI Readiness and has no declared AI Literacy relationship; its Track link is a candidate for discussion.

Original Track Guide Snapshot

Track Identity

An open, practical guide to understanding, using, evaluating, and continuing to learn about generative AI.

This is the active internal Track Guide.

Participation model: Guided or learner-directed. Learners may follow a recommended sequence, begin from a suggested starting point, choose a goal-based path, or explore the track map directly.

Purpose and Learner Promise

AI Literacy for the Rest of Us is an open invitation to understand and use generative AI in practical, grounded ways. Learners begin with ordinary needs, learn how to match tasks with appropriate tools and safeguards, work with AI intentionally, check the results, and remain accountable for the work they produce.

The track also supports people who may not use AI directly but need to understand the language, options, tradeoffs, and responsibilities involved when AI is introduced into a process, workplace, service, or community.

You will be able to do something useful with generative AI, understand what makes a task and tool suited to one another, apply the safeguards the work requires, and evaluate the result with accountable confidence. You will also have a repeatable way to continue learning as AI tools, uses, and claims change.

Who This Is For

Primary audience: Beginners, community learners, staff, older adults, students, clients, and anyone who wants a grounded first experience with generative AI.

Secondary audience: Facilitators, contributors, reviewers, caregivers, and mentors who support those learners or help improve the Lab.

This includes people evaluating whether or how AI should be integrated into an existing process, service, workplace, or community activity, even when they are not direct users.

No technical background is required.

Learners may type, work with a partner, observe a facilitator demonstration, use printed scenarios, or take a break. Curiosity and skepticism are both valid starting points.

Track Goals and Learner Outcomes

Learners may be able to:

  1. Use generative AI to complete a small, useful task.
  2. Describe generative AI as a class of tools built for particular kinds of work.
  3. Understand enough common AI language to evaluate tools, uses, and claims.
  4. Determine whether a task and tool are suited to one another.
  5. Identify the level of safety, privacy, and verification a task requires.
  6. Decide what information is appropriate to share.
  7. Frame and steer a multi-turn conversation intentionally.
  8. Ask for clarification, feedback, critique, uncertainty, and reflection.
  9. Check outputs against appropriate sources, standards, constraints, evidence, and human judgment.
  10. Decide whether there is enough evidence to stand behind the result.
  11. Participate more confidently in decisions about whether and how AI should be integrated into an existing process.
  12. Identify a useful next question, experiment, module, or learning path as the technology changes.

Learner Snapshot

Before beginning and after completing a module, path, or broader track experience, learners may take a private snapshot of how they would approach a practical AI-related situation. The Lab does not need to collect the snapshot. Its purpose is to help learners notice changes in how they choose tasks, establish safeguards, steer conversations, check work, make accountable decisions, and identify what they want to learn next.

Core Capability Domains

1. Understand

Describe generative AI as a class of tools built for particular kinds of work, recognize what it is and is not, and understand enough of the language to evaluate new tools, uses, and claims.

2. Choose for Fit and Safety

Determine whether a task is suited to generative AI, what level of safety and verification the task requires, what information is appropriate to share, and what tool or process boundaries should be used.

3. Steer

Frame, continue, clarify, compare, constrain, summarize, ask for feedback, request critique, restart, or stop a conversation intentionally.

4. Check and Learn

Evaluate outputs against appropriate sources, standards, constraints, evidence, and human judgment. Examine both the result and the process to understand what worked, what changed, and what should be carried into the next attempt.

5. Decide with Accountable Confidence

Review the process and result until there is enough evidence to stand behind the work with the same responsibility carried for work produced personally or by a human team. When that confidence is not justified, revise the work, seek additional expertise, change the process, or decline to use the result.

Ways to Navigate This Track

This track offers several ways to begin. Learners who want clear direction can follow the recommended route without choosing among modules. Learners may also use a snapshot to find a starting point, begin with a particular goal, or explore the full track map. These routes use the same underlying modules and capabilities, and learners may move between them as their needs change.

When a learner is unsure where to begin, the recommended route is the starting point.

Show Me the Way

Show Me the Way begins with the Start Here grouping in the organized track below. It is intended for learners who want to begin without first comparing modules or designing a learning path.

The current starting point connects AI Without the Hype to its A Safe First Try activity. The module remains Draft / Drafting for internal review; the lab is Beta, with feedback welcome. This starting point is not a completed public course or required gateway.

The other groupings organize what already exists without turning Planned or Deferred material into a recommended sequence.

Help Me Find My Starting Point

Help Me Find My Starting Point will use the optional learner snapshot to suggest one starting point and a likely next step.

This route will serve learners who are uncertain about what they need, have some prior AI experience, or are entering the track with a mixture of confidence and concern. The snapshot will be completed privately and will not need to be submitted to the Lab.

I Have Something I Need to Do

I Have Something I Need to Do will organize modules around recognizable learner goals rather than curriculum terminology.

A learner might begin here because they want to:

  • understand what generative AI is and try something useful;
  • protect information and evaluate results;
  • improve how they work with chatbots;
  • participate in a decision about introducing AI into an existing process;
  • understand AI-enabled tools, media, subscriptions, or technology choices; or
  • use AI for learning, creativity, or another practical purpose.

The organized track below maps these goals to existing modules and related labs. The groupings help learners and facilitators find material; they do not create prerequisites that the module sources do not already name.

Let Me Explore

Let Me Explore will provide access to the complete track map, module descriptions, concept relationships, statuses, and suggested connections.

This route will support learners who prefer to browse, compare, or assemble their own path. Required prerequisites will still apply when a module genuinely depends on earlier work.

Changing Routes

Learners may change routes, revisit a module, follow a related path, or stop after gaining the capability they came for. A route may recommend preparation without making it mandatory. When a genuine prerequisite exists, the module should name it explicitly and provide catch-up guidance where practical.

flowchart TD
    Start["Where should I begin?"] --> Recommended["Show Me the Way<br/>Recommended route"]
    Start -.-> Snapshot["Help Me Find My Starting Point<br/>Optional snapshot"]
    Start -.-> Goal["I Have Something I Need to Do<br/>Goal-based choices"]
    Start -.-> Explore["Let Me Explore<br/>Full track map"]
    Recommended --> Change["Change routes as needs change"]
    Snapshot --> Change
    Goal --> Change
    Explore --> Change

Track Shape

Track Map

Emerging Conceptual Progression

The following progression names a durable shift in how learners can approach AI work. It is a conceptual guide, not a required path or a claim that every step is a learner-available module.

  1. Prompt Engineering — introduced through Prompting Is the Door, Not the Destination
  2. Conversation Engineering
  3. Context Engineering
  4. Constraint Thinking
  5. Problem Definition — future direction
  6. Human-AI Collaboration — future direction

Constraint Thinking is the bridge between Context Engineering and the later work. It emphasizes that context is valuable because it helps define the problem an AI system is being asked to address.

Track → Module → Related Labs

This organization maps existing curriculum without changing any module or lab. A module’s lifecycle and learner availability remain separate from its place in the track. A related lab remains in the canonical Lab Library; it is linked here rather than copied into the module or track.

Status labels below come from the current module and lab sources:

  • Beta: a lab release mode for an activity learners can try, with feedback welcome.
  • Draft / Drafting: existing material available for internal review or controlled practice, with named review work still open.
  • Sketch or Seed / Planned: an existing source record that is not yet a learner-ready offering.
  • Ideation or Seed / Deferred: an existing source record intentionally outside the current learner path.
  • Proposed only: named in planning material, but no canonical module page exists.

Start Here

Foundations

Safer Use

Working with AI

Checking and Verification

Optional and Deferred Directions

Gap Report

  • The Start Here module remains Draft / Drafting and still needs its named human reviews and pilot evidence. A Safe First Try is a Beta lab, with learner feedback welcome.
  • Chatbot Roles and Modes and What’s Possible Beyond Text have no canonical module pages.
  • Several existing modules have no assigned central Lab Library package, including Before You Paste, Pause Before You Pay, and the planned media-and-technology modules.
  • Planned and Deferred sources remain visible for organization but are not promoted into learner availability by this map.
  • Reviewer assignments, approved support routes, and pilot evidence remain incomplete.

Overlap Report

  • AI Without the Hype and What AI Is and Is Not still require a later decision about orientation versus deeper foundation.
  • Reality Check for AI intentionally samples prompting, context, and verification through an experimental method without replacing those modules.
  • Prompting, Conversation Engineering, and Context Engineering form related layers, but only source-declared dependencies are mandatory.
  • When the Bot Sounds Right but Is Not and Trust, But Check the Wires still require a later decision about failure recognition versus source-checking practice.
  • The shared Curiosity modules and labs keep one primary home and appear here only as related resources.

Detailed Inventory and Curriculum Decisions

Current Track Inventory

This audit preserves the earlier evidence comparison behind the organized track. Inventory statuses are derived from module sources when one exists. Its earlier grouping labels are retained as historical audit evidence rather than the current learner organization.

Title Canonical reference Item kind Current grouping Lifecycle status Learner availability Current track relationship Open questions
AI Without the Hype ai-without-the-hype module Get the big picture Draft Drafting listed Track says “Drafting”; that matches source availability, not source lifecycle.
What AI Is and Is Not what-ai-is-and-is-not module Get the big picture Sketch Planned listed Track says “Drafting”; source says Sketch / Planned.
Reality Check for AI reality-check-for-ai module Get the big picture Draft Drafting primary One six-experiment lab builds a mental model through hypothesis, controlled comparison, observation, source checking, and revision; human reviews and pilot evidence remain outstanding.
Prompting Is the Door, Not the Destination prompting-is-the-door-not-the-destination module Work with chatbots more intentionally Sketch Planned listed Track says “Drafting”; source says Sketch / Planned.
Conversation Engineering conversation-engineering module Work with chatbots more intentionally Sketch Planned listed Track says “Drafting”; source says Sketch / Planned.
Chatbot Roles and Modes — proposed-module Work with chatbots more intentionally unknown unknown listed No module page exists. Track labels it Idea, but production and availability cannot be confirmed from a module source.
Context Engineering context-engineering module Work with chatbots more intentionally Sketch Planned listed Track says “Drafting”; source says Sketch / Planned.
Thinking in Constraints thinking-in-constraints module Work with chatbots more intentionally Ideation Deferred listed Track says “Ideation,” matching source lifecycle; learner availability is not shown in the track list.
The Constraint Landscape the-constraint-landscape module Work with chatbots more intentionally Ideation Deferred listed Track says “Ideation,” matching source lifecycle; learner availability is not shown in the track list.
Escaping the Conversation Gravity Well escaping-the-conversation-gravity-well module Deferred Conversation and Prompting Directions Seed Deferred listed Track says “Idea”; source says Seed / Deferred.
Separate the Builder from the Reviewer separate-the-builder-from-the-reviewer module Deferred Conversation and Prompting Directions Seed Deferred listed Track says “Idea”; source says Seed / Deferred.
Before You Paste: Privacy and Data Boundaries before-you-paste-privacy-and-data-boundaries module Protect your judgment and information Sketch Planned listed Track says “Idea”; source says Sketch / Planned.
Safety: Share Less, Notice More safety-share-less-notice-more module Protect your judgment and information Draft Drafting primary Shared safety baseline for private and third-party information, hidden file content, metadata, indirect prompt injection, and limited tool authority.
When the Bot Sounds Right but Is Not when-the-bot-sounds-right-but-is-not module Protect your judgment and information Sketch Planned listed Track says “Drafting”; source says Sketch / Planned.
Trust, But Check the Wires trust-but-check-the-wires module Protect your judgment and information Seed Planned listed Track says “Idea”; source says Seed / Planned.
Current Events Need Current Context current-events-need-current-context module Protect your judgment and information Ideation Deferred listed Freshness and retrieval concept; current examples must be selected and reviewed near the lab date.
History Beyond the First Answer history-beyond-the-first-answer module Protect your judgment and information Ideation Deferred listed Historical coverage and surfacing concept; needs an inclusive, expert-reviewed case set.
Pause Before You Pay: Scam Awareness Basics pause-before-you-pay-scam-awareness-basics module Protect your judgment and information Sketch Planned listed Track says “Idea”; source says Sketch / Planned.
What’s Possible Beyond Text — proposed-module Understand media and technology choices unknown unknown listed No module page exists. Track labels it Idea, but production and availability cannot be confirmed from a module source.
How Technology Changes the Ecology of Communication how-technology-changes-the-ecology-of-communication module Understand media and technology choices Sketch Planned listed Track says “Drafting”; source says Sketch / Planned. Source track metadata is “Multiple,” so this track relationship remains unstructured.
Becoming an Informed Technology Consumer becoming-an-informed-technology-consumer module Understand media and technology choices Sketch Planned listed Track says “Drafting”; source says Sketch / Planned. Source track metadata does not name this track.
Conversational Privacy conversational-privacy module Optional related modules Sketch Planned optional-related The current track list supplies no status; source metadata includes this track among multiple relationships.
Public Speaking public-speaking module Optional related modules Draft Drafting related Curiosity-primary practice for learner reflection, evidence-bounded coaching, and repeated attempts.
Relationships with Conversational AI digital-relationships module Optional related modules Sketch Planned optional-related The current track list supplies no status; source metadata includes this track among multiple relationships.
AI for Learning: Tutor, Quizmaker, and Simulator ai-for-learning-tutor-quizmaker-simulator module Optional related modules Seed Planned optional-related The current track list supplies no status; source metadata names this track alongside Creative Makerspace.
Prompt Engineering — conceptual-direction Track Shape → Track Map unknown unknown listed The progression says it is introduced through Prompting Is the Door, Not the Destination; no separately titled module page or structured relationship exists.
Constraint Thinking — conceptual-direction Track Shape → Track Map unknown unknown listed The progression names this as a bridge and the page links related constraint modules, but the relationship is not yet structured.
Problem Definition — conceptual-direction Track Shape → Track Map unknown unknown future-direction Named as a future direction; no module page or status source exists.
Human-AI Collaboration — conceptual-direction Track Shape → Track Map unknown unknown future-direction Named as a future direction; no module page or status source exists.

Core Route Candidate Comparison

This comparison records source evidence for nine possible contributors to Show Me the Way. It does not select core membership, decide a route, or establish an order.

Module Primary learner need Understand Choose for Fit and Safety Steer Check and Learn Decide with Accountable Confidence Likely contribution Overlap and distinction Open curriculum questions
AI Without the Hype A calm, low-pressure first understanding and safe first use of generative AI. Primary Primary Not evidenced Supporting Supporting Orientation and safe first practice Shares an opening explanation of AI and human responsibility with What AI Is and Is Not; distinct evidence is the A Safe First Try practice and personal ground rules. Source is Draft / Drafting and needs multiple reviews and pilot evidence. Whether this is sufficient orientation without the deeper foundations module remains open.
What AI Is and Is Not A plain-language mental model of AI as a capability layer with human responsibility. Primary Supporting Not evidenced Supporting Supporting Orientation and fit Shares beginner framing, risk, and human ownership with AI Without the Hype; extends into opportunity, systems, adaptation, and responsible participation. Source is Sketch / Planned. Opportunity Finder is a placeholder; the boundary between a deeper foundations module and an orientation asset is unresolved.
Reality Check for AI An experimentally tested mental model of language-model behavior, framing, context, confirmation bias, and verification. Primary Supporting Supporting Primary Supporting Experimental foundation and checking practice Unlike the orientation modules, it asks learners to make hypotheses, hold conditions steady, observe outputs, inspect sources, and revise their model. It touches prompting, context, and factuality but uses them as variables in one scientific-method sequence. Source is Draft / Drafting with a complete text-and-Notebook package. Factuality, learning-design, mixed-age, accessibility, and learner-pilot review remain open; core-route placement is not selected.
Before You Paste: Privacy and Data Boundaries A practical habit for sorting, sanitizing, and withholding information before using an AI tool. Supporting Primary Supporting Not evidenced Supporting Safety Distinct depth is the safe / sanitize / stop sorting practice and safer-prompt rewrite. Other candidates mention safety but do not teach these information boundaries in depth. Source is Sketch / Planned and needs privacy review, sorting cards, and a final handout. The cross-cutting safety rail is not yet defined.
Prompting Is the Door, Not the Destination A usable first request with relevant context, boundaries, inspection, and a repair loop. Supporting Primary Primary Supporting Supporting Practice and first-turn task framing Establishes intent, context, desired output, and boundaries for the first request. It overlaps Conversation Engineering at follow-up and revision but does not develop multi-turn strategy, drift, or stopping in the same depth. Source is Sketch / Planned. The precise handoff to Conversation Engineering and the depth of safety and verification in this module remain open.
Conversation Engineering Intentional multi-turn work: clarify, compare, steer, test, checkpoint, restart, or stop. Supporting Supporting Primary Supporting Primary Steering and decision Extends Prompting from first-turn framing and repair into multi-turn direction, constructive challenge, comparison standards, drift management, and stopping decisions. Source is Sketch / Planned and names Prompting as a dependency; that is module evidence, not yet a track prerequisite decision. The limit between conversation practice and later Context Engineering remains open.
When the Bot Sounds Right but Is Not Recognizing polished but unsupported, stale, invented, or overgeneralized output and choosing a check. Supporting Supporting Not evidenced Primary Supporting Checking and verification practice Distinct current evidence is failure-mode recognition and deciding what kind of verification is needed. It overlaps Trust, But Check the Wires at verification but is more fully specified. Source is Sketch / Planned and needs factuality review plus teachable flawed-output examples. Specific verification methods are not yet developed in depth.
Trust, But Check the Wires A focused habit of checking AI-generated output against a trusted public source. Not evidenced Supporting Not evidenced Primary Not evidenced Checking Appears intended to follow the failure-modes module and focus on source checking. Its present source is much thinner than When the Bot Sounds Right but Is Not, so meaningful distinction versus duplication remains unresolved. Source is Seed / Planned. It lacks stated audience, learning outcomes, and a defined verification method beyond a simple source-checking checklist.
Becoming an Informed Technology Consumer Making right-sized decisions about evolving products, subscriptions, commitments, renewals, and exit paths. Supporting Primary Not evidenced Primary Primary Accountable decision and continued learning Applies checking and decision-making to technology choices rather than chatbot output. It reinforces evidence, trials, and review without duplicating output-failure instruction. Source is Sketch / Planned. Its source metadata does not name this track, and its broad consumer scope may fit an optional path rather than the core.

Explicit overlap findings

  • AI Without the Hype and What AI Is and Is Not: Current evidence supports an orientation-plus-deeper-foundations distinction: the first centers safe first practice and personal ground rules, while the second centers AI as a capability layer, adaptation, opportunity, and responsible participation. Both teach introductory framing and human ownership. The sources do not yet settle whether both need to be discrete core modules.
  • Reality Check for AI and the existing foundation, prompting, context, and verification modules: Reality Check supplies a distinct experimental method: predict, control a variable, observe, verify, and revise. It samples concepts developed elsewhere without replacing deeper instruction. The sources do not yet settle whether it belongs immediately after orientation, later as integration practice, or as an optional Curiosity route.
  • Prompting Is the Door, Not the Destination and Conversation Engineering: Prompting establishes a first request, boundaries, inspection, and repair. Conversation Engineering develops multi-turn direction, constructive challenge, comparison, drift, checkpoints, and a stopping decision. Follow-up and revision overlap; the exact handoff remains a curriculum-design question.
  • When the Bot Sounds Right but Is Not and Trust, But Check the Wires: The first teaches learners to recognize unreliable output and choose a verification need. The second appears intended to practice source checking, but its current source does not yet establish enough outcomes or method detail to show whether it is a distinct layer of checking or a reinforcement activity.
  • Before You Paste and the cross-cutting safety rail: Before You Paste is the only candidate with a dedicated sorting, sanitizing, and safer-rewrite practice. Other modules reinforce low-risk examples, input safety, and human responsibility. The source evidence supports a dedicated privacy depth, while the shared safety rail still needs a later design decision.

Earlier Need-Based Grouping

This earlier grouping is retained as working evidence. The Track → Module → Related Labs organization above is the current track view.

Get the big picture

Work with chatbots more intentionally

Deferred Conversation and Prompting Directions

Advanced prompting is not merely writing better prompts. It is designing conversations that produce trustworthy outcomes. This includes deliberately separating idea generation, critique, verification, and decision making.

Future conversation work may address context accumulation, framing effects, conversational inertia, anchoring, persuasion loops, and healthy reset strategies. These are post-beginner directions, not new requirements for the current path.

Protect your judgment and information

Understand media and technology choices

Terms and Concepts

Available AI literacy glossary terms now include:

Additional Reading

These optional readings are hosted outside the Learning Lab. Medium access may vary.

  1. AI Is Only Magic When We Close Our Eyes — Grounds the reader by removing the mystique around AI, establishing it as a tool rather than magic.
  2. The First Tool That Can Speak Before It Knows Why — Explains the fundamental nature of Large Language Models and how they generate text.
  3. How LLMs Answer Questions They Were Never Taught — Breaks down inference, helping readers understand how models extrapolate information.
  4. Why Giving AI More Context Works — A practical look at the underlying mechanics of effective prompting.
  5. From Zero to Hero in Prompting — A straightforward, accessible guide to communicating with AI.
  6. Choosing the Right AI Assistant — Provides actionable advice on selecting the appropriate tool for specific needs.

Access, Status, and Current Limitations

This is the active AI literacy track guide. It is a map for learners and contributors, not Module 0 and not a promise that every listed module is ready today.

Current access: Some modules are available as source sketches for internal review. Others are drafting or are ideas only. No public class, video, Discord, office-hours, learner gallery, or capstone destination is implied until it is separately approved and available.

No paid account is required by this guide. Individual modules may use an approved general-purpose chatbot, printed scenarios, a shared screen, or a facilitator demonstration. Formats, schedules, videos, office hours, and community spaces remain status text until a real approved destination exists.

An optional capstone is not currently offered and is not a completion requirement.

Safety, Support, and Feedback

Use fictional, public, sanitized, or everyday low-risk examples. Do not paste private, sensitive, medical, legal, financial, employment, client, credential, or safety information into a practice tool. AI output is not proof, professional advice, or a replacement for human responsibility.

No response channel, safety page, or facilitator service is currently claimed as live.

Current limitations: modules are still being developed and reviewed; access formats are not yet broadly available; additional glossary definitions, facilitator materials, feedback routes, and a capstone remain follow-up work.

Stewardship and Review

Current owner and track steward: Mike

Individual modules and learning formats are at different stages of production and learner availability. Status language remains provisional until the planned governance review.

The intended operating model remains shared stewardship across contributors, facilitators, reviewers, producers, accessibility partners, subject reviewers, community stewards, and learner testers. Those roles are being recruited and should be named as they are assigned.

Reviewer assignments are not yet complete.

This guide can lead into Invitation To Be Curious Again, Zero-to-Hero Agentic Literacy, Systems Thinking and AI Engineering, Creative AI Makerspace, Study Time, and AI Readiness. Those next steps are optional and depend on the learner’s goals.

Working Notes and Unplaced Content

Candidate Starting Points and Path Material

Superseded Foundation Wording

Track Identity

Safe curiosity and practical skills for ordinary people using generative AI.

Participation model: Learner-directed. Tracks are maps; modules are selectable learning units. Only prerequisites stated on an individual module are mandatory.

Purpose and Learner Promise

AI Literacy for the Rest of Us is for people who are curious, skeptical, anxious, practical, or simply new to generative AI. It starts with ordinary tasks and plain language: what these systems can and cannot do, how to use them without treating them as magic, what not to paste, and how to keep human judgment in the loop.

The goal is not to make everyone an expert, engineer, or consultant. It is to help people make better decisions around AI, experiment safely, and choose the next useful question or module for themselves.

Track Goals and Learner Outcomes

Depending on the modules they choose, learners may be able to:

  1. Describe AI as a tool with useful limits.
  2. Try a small, low-risk chatbot task.
  3. Ask for help without believing there is a magic prompt.
  4. Continue, steer, compare, summarize, restart, or stop a conversation intentionally.
  5. Decide what information is relevant, safe, and appropriate to share.
  6. Notice when fluent output is not evidence.
  7. Check an answer against a source, standard, or human judgment.
  8. Recognize privacy, scam, and relationship risks.
  9. Make more informed choices about AI-enabled technology and subscriptions.
  10. Choose a next learning path without treating one path as universal.

Core Capability Domains

This track covers practical skills and durable concepts: safe experimentation, prompting, multi-turn conversation, context, privacy and data boundaries, verification, scams and persuasive systems, technology choices, and the limits of AI output.

Deferred vocabulary additions

Future module vocabulary passes will add terms such as conversation, context, model, hallucination, privacy, data boundary, scam, agent, memory, and multimodal when the modules that teach those concepts are developed.

Future capstone detail

An optional capstone may later invite learners to document one small, low-risk use case, what they checked, and what they chose not to share.

Future support, feedback, and escalation detail

Support, feedback, and escalation routes will be linked when they are approved and available.

Consolidated stewardship wording

Mike is the current owner and initial track steward.

Reviewer timing for review

Reviewer assignments are not yet complete. Independent review work is planned for the week of July 20, subject to reviewer availability.

Source: ops/track-audits/ai-literacy-for-the-rest-of-us.md