Reasoning From First Principles
AI reasons by pattern. It tells you what has worked before. First principles reasoning tells you what will work when nothing has been tried before.
The Error Taxonomy from Chapter 2 helps you catch flawed assumptions. The cascade mapping from Chapter 3 helps you see downstream effects of each assumption. Your Prediction Lock habit should now be automatic.
Most advice — from humans and AI alike — is reasoning by analogy: "this worked for Company X, so it will work for you." First principles reasoning strips a problem to its base truths and rebuilds from there. This is the skill that produces original solutions. This chapter trains you to stop asking "what's the best practice?" and start asking "what are the actual constraints, and what do they make possible?"
Exercise 1: Defend the Opposite (No AI)
Layers Used: Layer 1 (Predict Before You Prompt)
What You Do
You receive a widely accepted best practice. Without AI access, write a 500-word argument for why this advice is wrong — identifying the specific conditions under which it fails. This is written entirely by you with no tools. Only after submitting your argument do you use AI.
Choose Your Scenario
- Startup
- Engineering
- Education
Scenario A (Startup): "Startups should build an MVP before investing in scale."
Scenario B (Engineering): "Teams should always write tests before writing code (TDD)."
Scenario C (Education): "Students should master fundamentals before using advanced tools."
Choose the best practice closest to your field and argue against it.
A 500-word contrarian argument (written without AI) identifying at least 3 specific conditions under which the best practice fails, with reasoning for each. A clear statement of the first principles you used to derive these conditions (e.g., "In markets where trust is the primary barrier, an unfinished product destroys credibility permanently").
I wrote a contrarian argument against the common advice that "startups
should build an MVP before investing in scale." I wrote this entirely
without AI assistance.
Please:
(1) Rate my argument's logical rigor from 1-10.
(2) Are my 3+ conditions genuinely situations where the MVP approach
fails, or am I stretching? For each, rate plausibility from 1-10.
(3) Did I reason from first principles (deriving from base constraints)
or from counter-examples (just citing cases where it did not work)?
These are different -- explain the difference using my work.
(4) Identify the strongest point in my argument and explain why it
works.
(5) Identify the weakest point and explain how to strengthen it.
(6) Suggest 2 additional conditions I missed where the MVP approach
genuinely fails.
My argument: [paste your 500-word argument].
Finally, complete the Thinking Score Card for this exercise:
Independent Thinking (1-10), Critical Evaluation (1-10),
Reasoning Depth (1-10), Originality (1-10), Self-Awareness (1-10).
For each score, give a one-sentence justification.
What This Teaches You
You learn the difference between reasoning from principles and reasoning from examples. AI feedback reveals whether your contrarian argument was genuinely derived from constraints or was just a collection of counter-examples — and teaches you why the distinction matters.