How to evaluate AI reasoning for your own task
Evaluate reasoning against a task-specific acceptance test rather than fluent prose alone. The Reasoning Machine offers linguistic, mathematical and spatiotemporal lenses for framing questions. Those lenses are an author’s conceptual framework; deciding whether a particular model is reliable still requires actual inputs, independent checks and records of failure.
Define an observable result
“Good reasoning” is too broad to serve as an acceptance criterion. Specify the input, required output and an independent way to check it. For a calculation, retain the intermediate quantities and recompute them. For a document answer, identify the supporting passage. For a physical task, text plausibility cannot replace observation in the relevant environment.
Use three lenses without turning them into a leaderboard
| Lens from the book | A question to ask | A possible check |
|---|---|---|
| Linguistic | Does the response address the requested meaning? | Compare it with explicit requirements |
| Mathematical | Do quantities and constraints agree? | Recompute or use a suitable verifier |
| Spatiotemporal | Does the proposed action fit the setting? | Check against observations of that setting |
Use these lenses to choose appropriate checks for your task. A system may work well in one area and still need close review in another.
Keep a failure record
Save the task, relevant model or application version, date, expected result and actual result. Include failures rather than retaining only the best demonstration. If a prompt is revised after seeing the result, record that revision. Otherwise a successful final example can obscure how much supervision was required.
Where the book fits
Choose The Reasoning Machine for a conceptual discussion of these categories. Choose a reproducible evaluation suite when making a model procurement decision. The book’s scenes and dialogue should not be treated as records of experiments.
Read a sample before choosing
The Reasoning Machine
A three-lens framework for asking better questions about AI reasoning.
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Sample, chapter outline and limitations →Prepared with AI assistance. Updated 2026-10-24. About our recommendations.