DebunkedNo measured effect on claude-haiku-4-5No measured effect on gpt-5-miniNo measured effect on gemini-3.1-flash-lite
Adding pressure / myth-bust
Emotional stakes framing improves response quality.
You have probably heard that telling the model your job depends on it gets you a better answer. We tested it. Here is what we found.
Adding pressure or high stakes to your prompt did not change answer quality in our tests.
Why it matters
It costs nothing to drop, and it makes prompts easier for your teammates to read.
What to do instead
Describe the task and the standard you want. Concrete requirements do the work that urgency does not.
Rubric mean moved at most 0.11 points on all three models, inside the margin every time.
What the marks mean
- No measured effect
Show the per-model numbers
No measured effect on claude-haiku-4-5, gpt-5-mini and gemini-3.1-flash-lite.
Circulates in practitioner communities. Tested because it circulates, not because it is endorsed.
This tip is OpenAddict's plain-language read of the measured result. The measurement below is the evidence, and it is what the reading has to answer to.
Ledger idC10-emotional-stakes
What was tested
This claim circulates in practitioner communities as advice about how to write prompts. That it circulates is an input to what gets tested here. It is a reason to test the claim, and it is not evidence for or against it. The result below is the evidence, and it is the only thing on this page that carries weight.
The comparison is paired. Two prompts differ in one respect, the manipulated variable, and are otherwise identical by construction. Nothing here supports a causal reading beyond that pairing.
Result
| Measure | claude-haiku-4-5 | gpt-5-mini | gemini-3.1-flash-lite |
|---|---|---|---|
| Control arm | 3.578n 30 | 4.178n 30 | 4.156n 30 |
| Treatment arm | 3.611n 30 | 4.289n 30 | 4.144n 30 |
| Delta | +0.033 | +0.111 | -0.011 |
| Interval, 95 percent | -0.195 to 0.261 | -0.056 to 0.278 | -0.195 to 0.173 |
| Orbit | In free drift60 of 60 records | In free drift60 of 60 records | In free drift60 of 60 records |
Every cell in this table is rubric graded. The score is a grader model reading the answer against a published rubric, not a deterministic check.
Orbit is assigned by the frozen status_v1 rule. On this scale, rubric mean, 1 to 5, the pass threshold is +0.30 and the failure floor is -0.30, each requiring an interval that excludes zero.
Method for this claim
- Task set
- The same 6 domain questions as C09, so the two framing claims are measured on identical material. Only the stakes sentence differs between arms.
- Runs per model per arm
- 5
- Scoring
- Rubric graded, via rubric-quality-v1. A grader model reads each answer against a published rubric.
- Pass criterion as written for the pilot
- Mean graded score for treatment exceeds control by at least 0.5 rubric points on a 5 point scale, with the interval excluding zero.
The published verdict comes from status_v1, not from the pass criterion above. The criterion is recorded because it is what the claim was registered with before the run.
Model versions, as recorded
| Model | Version string returned | Delta on this claim | Interval |
|---|---|---|---|
| claude-haiku-4-5 | claude-haiku-4-5-20251001 | +0.033 | -0.195 to 0.261 |
| gpt-5-mini | gpt-5-mini-2025-08-07 | +0.111 | -0.056 to 0.278 |
| gemini-3.1-flash-lite | gemini-3.1-flash-lite | -0.011 | -0.195 to 0.173 |
Reading across models
Sampling was not held constant across vendors, so comparing one model column against another compares two settings as well as two models.
gpt-5-mini rejected the fixed sampling setting and ran at its own default on all 1040 of its calls. The other models ran at temperature 0.