New direction

Critical Thinking in the Age of AI.

Critical thinking is purposeful, reflective judgement: using and evaluating evidence, and reasoning precisely. It is not scepticism — it is disciplined reasoning. And it is becoming scarcer and more valuable at once.

Why now.

Complexity and data abundance are rising while time and the quality of reflection are shrinking. AI amplifies both: confident output comes at no cost, but it removes all the proof of the thinking behind it. AI can make capable people faster and better — it can also produce flawed reasoning that reads very persuasively.

The market has drawn the same conclusion: critical thinking now ranks as the number-one hireability factor. For us this is nothing new — it has always been the core of the Masterclass. We are now making that core explicit, and extending it.

Hand-drawn sketch: two people examining a large question mark with magnifying glasses

The nine modules.

Every module is optional and can be added before, during or after the Masterclass — same framework, no basics re-taught. Each runs as a keynote (1–1.5 h), a workshop (2 h to half a day), or a deep dive on your own documents, and modules combine into a tailored track.

Critical thinking in the age of AI

Why critical thinking is hard to see and measure, and a usage protocol for AI: where to trust it for speed, where to demand human review, and where not to rely on it at all.

Using AI to build a narrative

Where AI helps across the four TLSM steps — and where it quietly damages the result. What stays human-owned: purpose, meaning, coherence, credibility, original thinking.

Evidence & source evaluation

Judging what you are handed: sample and method, correlation versus causation, charts that mislead without lying — and, with AI, invented sources and fabricated quotes.

Data & information quality

Where a number comes from and whether it can carry the weight put on it — and the minimal governance that fixes recurring confusion: owned definitions, a single source of truth.

Asking the right question

The least-practised skill, made urgent by AI — a prompt is only a question you ask a machine. Writing the question down, then questioning it: hidden assumptions, framing, substitution.

Arguments & logic

Testing an argument, not only building one: valid versus true, deduction versus induction, the fallacies that survive in business reasoning.

Confidence, bias & accuracy

Confidence reflects how coherent a story feels, not whether it is true. Confirmation bias, anchoring, miscalibration — and how to judge how sure you should be. Think like a fox, act like a hedgehog.

Decision processes & collective thinking

The machinery around the decision: matching process to decision type, challenge mechanisms, recorded assumptions — and designing forums so good thinking doesn't depend on one person.

Turning data into decisions

Numbers inform, stories convince — most reporting fails by attempting both at once. Separating the reference report from the short dynamic narrative, and the process connecting them.

Build your track.

Tell us which of these questions your organisation is wrestling with — we'll suggest a combination of modules that fits.