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.
Key facts
- Source basis
- Author-supplied book manuscript; editorial synthesis
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 2026-10-28. About our recommendations.