Fermi Estimation Discipline Chain

validated scientific chain v1.0.0 cc-by-sa

Block ID: 18909120-0a7a-45c8-9bfa-8659bab750bd

Community-contributed block. PromptDNA makes no guarantee of output quality or fitness for purpose. User assumes all responsibility for use.

Template

Estimate {quantity_to_estimate} using disciplined Fermi decomposition. (1) Decompose the target into factors you can estimate independently, writing the full chain as a product or sum before estimating anything — the decomposition is the intellectual work; a good one uses factors that are either widely known or boundable. (2) Estimate each factor with an explicit basis: anchored to a known reference value, bounded geometrically, or derived from per-capita reasoning — never a bare number without provenance. (3) For each factor, state a plausible low and high, aiming for ranges you'd bet each contain the truth. (4) Multiply through the central estimates for the point answer, tracking units so dimensional errors surface. (5) Propagate the ranges: multiply the lows and the highs to bound the answer, and note that in multiplicative chains errors compound, so the factor with the widest range dominates — name it. (6) Cross-check against an independent decomposition or a known related quantity; if the two approaches disagree by more than an order of magnitude, find out why before trusting either.

Estimate {quantity_to_estimate} using disciplined Fermi decomposition. (1) Decompose the target into factors you can estimate independently, writing the full chain as a product or sum before estimating anything — the decomposition is the intellectual work; a good one uses factors that are either widely known or boundable. (2) Estimate each factor with an explicit basis: anchored to a known reference value, bounded geometrically, or derived from per-capita reasoning — never a bare number without provenance. (3) For each factor, state a plausible low and high, aiming for ranges you'd bet each contain the truth. (4) Multiply through the central estimates for the point answer, tracking units so dimensional errors surface. (5) Propagate the ranges: multiply the lows and the highs to bound the answer, and note that in multiplicative chains errors compound, so the factor with the widest range dominates — name it. (6) Cross-check against an independent decomposition or a known related quantity; if the two approaches disagree by more than an order of magnitude, find out why before trusting either.

Variables

Name	Type	Required	Trust level
quantity_to_estimate		yes

fermi-estimationorder-of-magnitudeestimationchain-of-thought

Ratings

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Overall (0)

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Accuracy

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Consistency

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Clarity

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Efficiency

Benchmarks

Not yet self-validated against any benchmark. Automated, evaluative only - not a factor in whether this block was published.

Submitted by James P FounderMod via mcp · 2026-07-18