Pick the right AI tool
Code, spreadsheets, and calculators
Deterministic tools should perform exact calculations and repeatable transformations; AI can help formulate and explain them.
1Learn the idea
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The working principle
Deterministic tools should perform exact calculations and repeatable transformations; AI can help formulate and explain them. This principle matters because an AI system produces likely output from the context and instructions it receives; it does not automatically know the organization’s current facts, private policy, unstated intent, or acceptable risk.
Use the following sequence for this page: use a spreadsheet or code for arithmetic; make formulas and assumptions visible; test edge cases and reconcile totals; ask AI for explanation without replacing the calculation. The sequence is a guide, not a ritual. Skip a step only when its question truly has no effect on the outcome, and strengthen it when mistakes would be costly.
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A practical method
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1. Use a spreadsheet or code for arithmetic
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2. Make formulas and assumptions visible
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3. Test edge cases and reconcile totals
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4. Ask AI for explanation without replacing the calculation
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Work through the scenario
Return to the opening case: A finance assistant must compute totals, identify duplicate rows, and explain variance from a budget. Begin by rewriting the request as a small contract. Name the intended reader or user, the authoritative material, the operation to perform, the required output, and the review owner. If current information is required, identify where it will come from. If exact calculation or action is required, assign that step to a deterministic tool or an approved system rather than relying on prose generation.
A useful instruction could follow this shape:
Goal: help [reader] accomplish [outcome]. Use only [named sources or supplied material] for factual claims. Perform [specific operation] and return [format]. Mark missing information as TBD or ask a focused question; do not guess. Before the result is used, [named person or role] will check [criteria].
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Failure modes to catch
- Copying numbers from prose instead of source data. This hides an important assumption or removes a review point. Replace it with an explicit rule, a source check, or a human decision.
- Running generated code without reviewing effects. This hides an important assumption or removes a review point. Replace it with an explicit rule, a source check, or a human decision.
- Assuming a plausible answer is numerically exact. This hides an important assumption or removes a review point. Replace it with an explicit rule, a source check, or a human decision.
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Make it reusable
Turn Code, spreadsheets, and calculators into a template you can reuse this week: job statement, required evidence, failure mode to catch, and reviewer. Store it next to your other pick the right ai tool notes. When the job changes, rewrite only the job statement and re-run the same failure-mode list — do not invent a new workflow from scratch. Role of this page: Precision and verification.
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Why this matters
A finance assistant must compute totals, identify duplicate rows, and explain variance from a budget. The temptation is to begin by typing a broad request and judging whatever appears. That approach makes a good result hard to repeat and a bad result hard to diagnose.
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