Capable people, unfamiliar machinery
Designed for staff who use AI-supported tools at work but do not need to become machine-learning specialists.
Practice area 01
AI Learning Studio
Practical AI education that replaces hype with usable mental models, responsible judgment, and guided practice.
AI fluency is not memorizing tool features. It is learning when to use a model, how to direct it, how to evaluate its output, and when human judgment must take over.
Foundation series · 7 courses
AI Without the Fog
A practical foundation series that helps non-technical staff understand how generative AI works, recognize its limits, evaluate its output, and use it responsibly at work.
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Course 1 · Live
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Course 2 · Live
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Course 3 · Live
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Course 4 · Live
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Course 5 · Live
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Course 6 · Live
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Course 7 · Live
AI 100: How AI Assistants Work
A narrated, interactive foundation course on next-token prediction, knowledge gaps, confident errors, privacy, and deciding what needs verification.
AI 101: Why It Forgets, Changes Its Mind, and Drifts
A practical course on context windows, uneven attention, output variation, and how to structure source material for more dependable work.
AI 102: What Is Actually in There
A guided course on trained model parameters, retrieval, representation, and the difference between model limitations and product choices.
AI 103: Why It Agrees With You
An interactive course on AI sycophancy, user pressure, independent analysis, and better ways to ask for a challenge.
AI 104: Why Checking Fails
A practical course on automation bias, verification effort, decision ownership, and checks that survive a busy day.
AI 105: What It Does to the Work
A workplace-focused course on redesign, released capacity, skill development, human recourse, and responsible adoption.
AI 106: When It Can Reach Your Files
A connected-tools course on prompt injection, data boundaries, permissions, least privilege, and human review.
Applied learning and tools
Practise the judgment.
Turn the foundation into decisions, feedback, and repeatable checks through games, workshops, and job aids.
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3 games live
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Workshop · Live
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Job aid · Live
11
Reference · Live
BLIP: AI Learning Games
Three browser games that build AI literacy, workplace judgment, and safe autonomy through choices, feedback, and consequences.
Prompting as Instruction
A short workshop that teaches prompts as clear briefs: context, objective, constraints, examples, and evaluation.
The Human Check
A practical job aid for reviewing AI-supported work for accuracy, privacy, bias, usefulness, and appropriate disclosure.
AI 109: Glossary & Reference
A searchable plain-language reference for the terms, distinctions, and recurring failure modes used across AI 100–106.
Portfolio case study
The design behind the course sequence
Seven short modules move non-technical staff from a usable mental model to safer workplace decisions, better work design, and more responsible connected tools. Technical explanation appears only when it changes what the learner should do next.
Replace folklore with judgment
The learning problem is not missing terminology. It is knowing when an answer is safe to use, what needs checking, and where responsibility remains human.
Mechanism → failure → action
Each concept predicts a recognizable failure, then immediately becomes a practical behaviour: verify, trim, reposition, inspect the source, or ask the system owner.
Transfer, not trivia
Learners audit AI-supported work, rebuild failing requests, design checks, allocate released capacity, and assess connected-tool risks using workplace scenarios.
AI 100–102 · UnderstandExplain the mechanism and diagnose the failure.
AI 103–104 · JudgeResist agreement pressure and build checks that survive.
AI 105–106 · DesignProtect the work, the learner, the data, and the decision.
Inclusive by design: narrated pages, matching transcripts, keyboard-operable interactions, visible progress, reduced-motion support, and no learner data leaving the page.
Evidence practice: technically sensitive claims are qualified, source-linked, and paired with an explicit limitations note. AI supported research and production; final instructional decisions and review were human-led.