🧠 The More We Master, The Less We Question.
1️⃣ Real-World Use Case
In 1975, Kodak engineer Steven Sasson built the world’s first digital camera.
It was the size of a toaster and took 23 seconds to record one image.
He demoed it to Kodak executives in 1976. Their response, as Sasson later recalled:
“They simply asked me why anybody would want to take a picture this way when there was nothing wrong with conventional photography.”
Kodak invented digital photography. Then their film expertise killed it.
Their entire mental model was built around film chemistry and the film business.
They couldn’t imagine photography without film.
They patented Sasson’s invention but refused to develop it, choosing to protect film sales instead. Meanwhile, companies without film expertise → Sony, Canon, and Fujifilm → embraced digital.
2012: Kodak files for bankruptcy.
The paradox: Kodak’s deep expertise in film photography, the very thing that made them dominant, became the blind spot that destroyed them.
Sasson himself later said:
“What he taught me was that you don’t have to be an expert in a field in order to make an original contribution.”
Expertise helps you execute efficiently.
But it also creates filters that block transformative possibilities.
📚 Framework in Focus: Shoshin (Beginner’s Mind)
From Zen Buddhism: “In the beginner’s mind there are many possibilities, but in the expert’s there are few.” (Shunryu Suzuki)
Approach situations with openness and lack of preconceptions, regardless of expertise.
3-Step Play
Expertise Audit → Map mental models and assumptions shaped by past experience.
Deliberate Naivety → Ask foundational questions experts stop asking.
First-Principles Reset → Strip away assumptions to examine fundamental truths.
Jobs applied this when creating the iPhone, questioning what a phone needed to be.
IDEO builds it into design-thinking methodology.
Stripe asked “What if we built for developers first?” and ignored banking assumptions.
2️⃣ Powerful Prompt
🔹 Tier 1: Basic Mode — Fast, Actionable Scan
Role:
You are a strategic advisor helping me apply Beginner’s Mind (Shoshin) to see past expert blind spots and discover filtered possibilities.
Context:
You are applying Beginner’s Mind analysis to uncover assumptions and possibilities that expertise filters out.
Inputs:
Problem/decision: [INPUT: Describe your challenge]
Your expertise/background: [INPUT: Your experience in this domain]
Current approach: [INPUT: How you’re thinking about this]
Assumptions you’re making: [INPUT: What you “know” to be true]
What’s changed recently: [INPUT: Market/tech/customer shifts]
Task:
Audit assumptions based on past experience.
Generate questions a complete beginner would ask.
Strip to first principles — what’s fixed vs. inherited?
Identify possibilities expertise is filtering out.
Constraints:
Be concrete. No invented scenarios. Distinguish valuable wisdom from outdated assumptions.
Output:
Reasoning summary (5–7 bullets) + Expert Assumption Map + Beginner Question Battery + Filtered Possibilities (approaches expertise dismisses but beginners would try).
(Copy-paste into ChatGPT, Claude, Gemini.)
🔹 Tier 2: Advanced Mode — Evidence-Based Strategy Logic
Role:
Cognitive strategy expert specializing in Shoshin (Beginner’s Mind) to help leaders deliberately suspend expertise, question foundational assumptions, and discover breakthrough possibilities expert knowledge filters out.
Context:
You are applying Beginner’s Mind analysis to a specific strategic challenge where expertise may create blind spots.
Inputs:
Problem/decision: [INPUT: Describe challenge]
Domain & expertise level: [INPUT: Your background and experience]
Current approach & reasoning: [INPUT: How you’re thinking about this]
Assumptions from experience: [INPUT: What you “know” to be true]
Industry conventions/“best practices”: [INPUT: Established wisdom]
What’s changed since you formed these models: [INPUT: Market/tech/customer shifts]
Constraints you assume are fixed: [INPUT: Limitations you accept as given]
Task:
Expertise Audit — Map mental models, assumptions, and “truths” shaped by past experience.
Assumption Archaeology — Trace which assumptions came from specific past contexts that may no longer apply.
Naive Questioning — Generate questions a complete beginner would ask that experts stop asking.
First-Principles Deconstruction — Strip away assumptions to examine fundamental truths and constraints.
Possibility Expansion — Identify opportunities and approaches that expert filters screen out.
Wisdom Preservation — Distinguish valuable lessons worth keeping from calcified thinking worth discarding.
Critical Guardrails:
Base analysis strictly on problem details and expertise provided — no invented context.
Distinguish wisdom worth preserving vs. outdated assumptions masquerading as expertise.
If info is missing to identify specific blind spots, clearly state what additional context is needed.
Include step-by-step reasoning explaining how each assumption limits possibilities.
Balance beginner’s mind openness with practical constraints and genuine learnings from experience.
Output:
Reasoning summary / decision log (5–7 bullets)
Expert Assumption Map: | Assumption | Original Context | Still Valid? | How It Limits Thinking | Alternative Possibility |
Beginner Question Battery organized by: Product/Service Design, Business Model, Customer Behavior, Market Dynamics, Technology/Operations
First-Principles Analysis: | Accepted Constraint | Is It Actually Fixed? | What If It Wasn’t? | Implications |
Filtered Possibilities: | Approach Expertise Dismisses | Why Expert Mind Rejects It | Beginner Mind Case For It | Test Design |
Balanced Integration Strategy — which expert knowledge to preserve and which assumptions to challenge
Chain of reasoning explaining how each mental model formed and where it breaks down in current context
(Copy-paste into ChatGPT, Claude, Gemini.)
What did you think?
3️⃣ Why It Works (mental-model stack)
Shoshin (Beginner’s Mind): Expertise creates cognitive efficiency but also cognitive rigidity.
Confirmation Bias: Experts seek information confirming existing models while filtering contradictory signals.
First-Principles Thinking: Breaking down to fundamentals reveals which “constraints” are inherited assumptions.
Cognitive Flexibility: Hold multiple mental models simultaneously and switch between expert and beginner perspectives.
This stack turns AI into a cognitive de-biasing tool — not an expertise reinforcement engine.
4️⃣ How to Apply It in Your Org
Product Development: Before major features, ask “If we started today, would we build it this way?”
Strategy Reviews: Challenge multi-year plans — what would someone with zero industry history question?
Customer Research: Send beginner team members to interviews — they ask “too basic” questions that reveal insights.
Hiring & Onboarding: Capture new employee questions in the first 90 days before they “learn” what not to ask.
🧭 Try This Week (90-Minute Sprint)
Question what you “know.” Use this sprint to escape expertise blind spots.
1️⃣ Document current approach and assumptions (12 min)
→ Write your solution and list every assumption driving it. What are you taking for granted?
2️⃣ Trace where your mental models came from (12 min)
→ For each assumption, note: When did I learn this? What was the context? Is that context still true?
3️⃣ Generate beginner questions (12 min)
→ Ask: What would someone with zero experience question? What “obvious truths” would they challenge?
4️⃣ First-principles deconstruction (12 min)
→ For each constraint, ask: Is this actually fixed, or just how we’ve always done it? What if it wasn’t true?
5️⃣ Design one experiment to test a filtered possibility (12 min)
→ Pick one idea your expertise dismisses. Design a small, safe test to validate or invalidate it.
✨ When you question expertise without abandoning its value, you stay open to breakthrough while executing with judgment.
↗︎ Think Better. – Clarity Prompts team
