AI Skills6 min
AI Literacy for Adult Learners: Capabilities, Limits, and Mental Models
A practical map of what modern AI can do, where it fails, and the mental models adults need to use it with agency and informed judgment.
ExplainerRead
Work with intelligence
AI Skills
Understand AI, learn with it, verify it, and build useful human–AI workflows without surrendering judgment.
Topic map
What this domain contains
01AI Foundations
02Prompting & Interaction
03AI-Assisted Learning
04Workflows & Agents
05Evaluation & Verification
06Building with AI
07Responsible AI Use
Starting sequence
Read, test, connect.
Start with the first article, then choose by goal—not by whatever is newest.
AI Skills6 min
How to Use AI as a Tutor Without Becoming a Passive Learner
Use AI to question, hint, simulate, and give feedback while preserving the independent retrieval and productive struggle that learning requires.
GuideRead
AI Skills6 min
How to Verify AI Explanations and Sources
A claim-by-claim verification workflow for checking AI explanations, citations, numbers, uncertainty, and missing context before you rely on them.
GuideRead
AI Skills5 min
Prompting for Learning: Questions, Context, Feedback, and Retrieval
Prompt AI for better learning by specifying the capability, prior knowledge, practice rules, evidence standard, feedback rubric, and final retrieval test.
MethodRead
AI Skills8 min
Build Your First Useful AI Workflow: Agents, Automation, and Human Checkpoints
A documented ten-item pilot for turning one bounded task into an AI-assisted workflow with explicit inputs, checks, failure routes, and accountability.
Field LabRead
AI Skills6 min
The State of AI-Assisted Learning in 2026: What Changed and What Matters
A dated, falsifiable interpretation of richer AI learning workflows, persistent outcome gaps, learner rights, assessment, and human responsibility.
WindowRead
AI Skills5 min
What Can Generative AI Actually Do? A Capability Map for Knowledge Work
A task-level map of where generative AI can transform, retrieve, classify, and propose—and where evidence, judgment, or accountable approval must take over.
Research MapRead
AI Skills5 min
AI Search vs Chatbots vs Agents: Which Should You Use for Which Task?
Choose among AI search, conversational models, and tool-using agents by matching evidence needs, action scope, reversibility, and required oversight.
ComparisonRead
AI Skills5 min
How AI Systems Fail: Hallucination, Bias, Drift, and False Confidence
Diagnose four commonly conflated AI failure families, trace their causes across model and workflow layers, and choose controls that can reveal them.
ExplainerRead
AI Skills5 min
How to Evaluate AI Output: A Four-Layer Quality Model for Real Work
Evaluate AI output across factual integrity, task fitness, decision impact, and process accountability instead of relying on polish or one accuracy score.
MethodRead
AI Skills5 min
Automation Bias: Why Capable People Overtrust AI
Understand why skilled users accept automated advice, miss contradictory evidence, and need decision environments—not reminders—to calibrate trust.
ExplainerRead
AI Skills5 min
Why AI Answers Change: Context, Sampling, Model Updates, and Reproducibility
Trace changing AI answers to input context, probabilistic generation, system components, and version changes—and preserve enough state to investigate.
ExplainerRead
AI Skills5 min
The Anatomy of a High-Quality AI Request: Goal, Context, Constraints, Sources, and Success Criteria
Replace prompt folklore with a five-part request specification that makes AI work testable, source-bounded, and easier for humans to review.
MethodRead
AI Skills5 min
Prompt Injection Explained: How Instructions and Data Become Security Risks
Understand prompt injection as a trust-boundary failure, then reduce exposure with content separation, least privilege, validation, and approval gates.
ExplainerRead
AI Skills5 min
What Is an AI Agent? Tools, Memory, Planning, and Human Control
A precise, non-mystical model of AI agents: the loop that joins model decisions to tools, state, observations, permissions, and human checkpoints.
ExplainerRead
AI Skills5 min
AI Workflow Design: Where Human Judgment Must Stay in the Loop
Place human judgment at framing, evidence, exception, value, and release boundaries—then give reviewers the information and authority to intervene.
GuideRead
AI Skills5 min
AI Evals for Knowledge Work: Test Sets, Rubrics, and Failure Thresholds
Build a local AI evaluation from representative cases, anchored rubrics, critical blockers, and versioned results rather than anecdotal demonstrations.
GuideRead
AI Skills5 min
RAG vs Fine-Tuning vs Long Context: Which Knowledge Strategy Fits?
Compare retrieval-augmented generation, fine-tuning, and long context by the problem each solves, its evidence trail, update path, cost, and failure modes.
ComparisonRead
AI Skills5 min
AI Prototyping for Non-Engineers: Where Speed Ends and Engineering Begins
Use AI to test an idea quickly while recognizing the exact boundaries where security, data, reliability, accessibility, and ownership require engineering.
GuideRead
AI Skills5 min
Privacy-Safe AI at Work: What You Should Never Put Into a Model
Decide what data may enter an AI system by mapping purpose, sensitivity, authorization, provider handling, retention, access, and safer substitutes.
GuideRead
AI Skills5 min
AI-Assisted Learning Systems: Tutors, Simulations, Feedback, and Independent Testing
Design an AI learning system that combines explanation, practice, feedback, simulation, and delayed independent tests without outsourcing the target skill.
GuideRead
AI Skills5 min
The Human–AI Collaboration Ladder: From Tool Use to Accountable Delegation
Choose among assistance, recommendation, bounded execution, and delegation by matching AI autonomy to evidence, reversibility, authority, and consequence.
GuideRead
AI Skills5 min
The Scaffolding-Fade Protocol: Use AI Support, Then Remove It
Define the unsupported target, log every aid, fade one support at a time from performance evidence, restore help when needed, and test unaided transfer.
MethodRead
AI Skills5 min
The Alignment Problem: Whose Values Enter the System?
Test Brian Christian’s account of machine-learning alignment against contested objectives, data politics, abstraction, plural values, institutional power, and recourse.
Book AnalysisRead
AI Skills5 min
The Coming Wave: Is Containment a Strategy or a Metaphor?
Test Mustafa Suleyman’s containment proposal against proliferation, concentration, dual use, state capacity, democratic legitimacy, surveillance, and adaptive governance.
Book AnalysisRead
AI Skills5 min
Co-Intelligence: Does Working With AI Make Us More Capable?
Test Ethan Mollick’s practical case for AI collaboration against the jagged frontier, automation bias, skill transfer, homogenization, workflow adoption, and accountability.
Book AnalysisRead
AI Skills6 min
The Worlds I See: What a Human-Centered History of AI Makes Visible
Test Fei-Fei Li’s human-centered history of computer vision against the labor, labels, institutions, exclusions, and power that make machine seeing possible.
Book AnalysisRead
AI Skills5 min
The Technological Republic: Can Public Purpose Guide Technical Power?
Test Alexander Karp and Nicholas Zamiska’s case for public-purpose technology against democratic authorization, procurement, rights, accountability, and conflicts of interest.
Book AnalysisRead
AI Skills5 min
From Model Capability to Workflow Adoption: The Gap That Will Define the Next Phase
A structural map of why rapid AI capability gains do not automatically become reliable organizational performance, and which adoption signposts matter.
WindowRead
AI Skills5 min
AI Agents Are Improving. Are Organizations Ready to Absorb Them?
A readiness test for agentic AI that separates technical progress from identity, authorization, data, observability, evaluation, and incident capacity.
WindowRead
AI Skills5 min
The New AI Divide: Those Who Can Evaluate Systems—and Those Who Can Only Use Them
A structural account of why access and interface fluency may matter less than the ability to test claims, boundaries, failures, incentives, and deployment.
WindowRead
AI Skills5 min
AI Fluency Is Spreading Faster Than AI Governance
Why rapid tool use can outrun authority, evaluation, incident response, and worker participation—and which governance signposts show real institutional learning.
WindowRead
AI Skills5 min
The Rise of Personal AI Workspaces: Memory, Context, and Dependency
A structural analysis of persistent AI workspaces as cognitive infrastructure: their leverage, memory risks, portability boundaries, and dependency tests.
WindowRead
AI Skills5 min
The Physical Infrastructure Behind “Abundant Intelligence”
A structural map of the electricity, grids, data centers, chips, capital, and geography concealed by the metaphor of nearly free digital intelligence.
WindowRead
AI Skills8 min
When Can a Human Checkpoint Actually Stop an Error? A 120-Case Simulation
How does checkpoint performance change when error observability, evidence access, reviewer capacity, and stop authority vary independently? Executed on frozen inputs with inspectab
Field LabRead
AI Skills9 min
When Should an AI Task Escalate to a Human? A 120-Task Cost Curve
How do four human-review thresholds trade review cost against expected error loss across tasks with different consequences and reversibility? Executed on frozen inputs with inspect
Field LabRead