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First Principles

Rebuild a problem from fundamental truths (physics, economics, unit costs, what's actually true regardless of convention) rather than by analogy to how things are normally done — the reasoning style associated with Elon Musk's approach to manufacturing cost problems and Richard Feynman's approach to physics problems.

Use when: the user is reasoning by analogy or precedent ("that's just how it's done," "industry standard is..."), is stuck because "everyone knows X isn't possible," or is pricing/costing something and the number seems anchored to convention rather than to actual inputs. Not a fit for problems that are genuinely about social convention or law, where precedent is the actual substance of the answer.

Install this skill

  1. Create a folder named `first-principles`.
  2. Save the skill content below as `SKILL.md` inside that folder.
  3. Place the folder in `~/.codex/skills/` for Codex, `.cursor/skills/` for Cursor or `.claude/skills/` for Claude Code.
  4. Describe the task normally. Your agent loads the skill when its description matches.
first-principles/SKILL.md
---
name: first-principles
description: Rebuild a problem from fundamental truths (physics, economics, unit costs, what's actually true regardless of convention) rather than by analogy to how things are normally done — the reasoning style associated with Elon Musk's approach to manufacturing cost problems and Richard Feynman's approach to physics problems. Use this whenever the user is reasoning by analogy or precedent ("that's just how it's done," "industry standard is..."), is stuck because "everyone knows X isn't possible," or is pricing/costing something and the number seems anchored to convention rather than to actual inputs. Not a fit for problems that are genuinely about social convention or law, where precedent is the actual substance of the answer.
---

# First Principles

Reasoning by analogy is usually fine and fast — most of the time, doing
what's normally done is a reasonable shortcut built on real accumulated
knowledge. First-principles reasoning is for the specific moments when
the analogy is the thing holding a wrong answer in place.

## The technique

1. **State the claim being taken for granted.** Usually something like
   "X costs/takes/requires Y" where Y is treated as fixed. Say it plainly:
   "the assumption here is that ___."

2. **Ask why that's true, one layer down.** Not "is it expensive" but
   "what specifically makes it expensive — which inputs, at what
   quantities, at what price?" Keep asking "why is *that* true" until you
   hit something that's actually fundamental (raw material cost, a
   physical constraint, a real regulatory requirement) rather than
   another layer of "because that's how it's usually done."

3. **Rebuild the estimate from the fundamental layer up.** If you costed
   out the raw inputs at their actual prices, what would this cost? This
   number is often wildly different from the conventional number —
   that gap is the interesting part, and it's exactly the gap Musk
   pointed at with rocket manufacturing costs and battery costs.

4. **Explain the gap.** If the first-principles number is much lower than
   the conventional one, the gap is usually markup, inefficiency,
   regulatory capture, or a coordination problem — name which one, because
   that's what tells you whether the gap is closeable.

5. **Check you haven't thrown away something real.** Precedent sometimes
   encodes hard-won knowledge, not just inertia (this is why circle of
   competence matters — see `mental-models`). Before concluding "this
   should be way cheaper/faster/different," ask what the incumbent
   approach might know that the rebuild is missing.

## Output

Show the layer-by-layer "why is that true" chain explicitly, not just the
final rebuilt number — the chain is what makes the conclusion trustworthy
rather than just a different unsupported guess.

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