The useful result
Choose answer detail separately from reasoning effort using one repeatable fixture.
- Choose answer detail separately from reasoning effort using one repeatable fixture.
A short answer does not have to mean a shallow task. Reasoning effort and output detail are separate controls in the documented GPT-6 API. Practise changing one at a time, so you can tell whether an improvement came from the setting or a different prompt. This is a tiny evaluation, not a promise that a particular setting always saves money.
Select the named model only if it is available in your interface. API controls and consumer-app controls differ. You can practise the technique on the supplied fictional inputs with an available compatible assistant first. This lesson is documentation-based; examples are expected results, not a claim that we ran the named model.
Before you start
- Access to Astra, or another assistant for the prompt-only exercise.
- API users: permission to change documented request settings and inspect usage.
- Fictional fixture: three tasks with due dates and one blocked dependency.
Review evidence
Documentation-based review · 2026-10-18
Provider documentation checked on 18 October 2026. Examples and checks are original illustrative exercises, not recorded platform tests. Cover artwork is conceptual and does not imply provider sponsorship.
Freeze the small task
Use the same three tasks for every attempt: design due Monday; review blocked until design is approved; publish due Wednesday. Ask for the next action, blocker and one missing fact. Keep the input and output fields unchanged.
Example / expected result
Illustrative example; not a recorded model result.
Expected next action: complete or approve the design; the approval date remains unspecified.
Check your result
Both attempts receive exactly the same facts and requested fields.
Change detail before depth
In an API client, use the documented text.verbosity control for response detail and reasoning.effort for thinking depth. Start with a short output while leaving effort unchanged. In chat, request three concise fields without pretending this changes API settings.
Return only three fields: next action, blocker, missing fact. Facts: design due Monday; review starts after design approval; publish due Wednesday. Do not invent an approval date.Example / expected result
Illustrative example; not a recorded model result.
Next action: finish design. Blocker: review awaits approval. Missing fact: who approves, and when?
Check your result
A formatting request is not reported as an API-setting change.
Evaluate one setting change
If the response misses a dependency, repeat with a different supported effort setting while keeping the detail requirement fixed. Record actual response, usage and time if available. Pick the smallest configuration that meets your own check.
Check your result
The answer preserves the dependency and does not invent a scheduled review or guaranteed saving.
When it goes wrong
A lower verbosity setting does not cap all reasoning tokens. Settings vary by model and API; a sentence in ChatGPT cannot configure a request sent by another application. One successful example is not a general performance benchmark.
Make it your own
Add a second blocker: publication needs a legal approval whose date is unknown. Repeat the same comparison and check that both missing dates remain visible.
Useful next resources
Sources and review
Last checked Oct 18, 2026. Features and account limits can change. Verify important results against your original material.
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