Usable with a quick edit4 of 9 checks passed
The note provides clear direction; a PM could quickly add a condition for reverting and verify SRM, but the core reasoning is sound and evidence is accurate.
Output
Hi Team,
Before we write off the shorter onboarding checklist as a failure, let's look at the full picture.
While the headline result was statistically non-significant, the numbers and qualitative feedback tell a more nuanced story:
Positive Directional Lift: Group B (5 steps) saw a 32.9% activation rate compared to 31.2% for Group A (9 steps)—a 1.7 percentage point increase.
Underpowered Test: Our pre-registered minimum detectable effect (MDE) was 3pp, meaning the test wasn't powered to reliably catch a 1.7pp or 2pp shift.
Reduced Support Friction: Support tickets tagged "onboarding confusion" dropped significantly from 44 to 29 during the test.
What we should conclude: The test wasn't a failure; it was inconclusive. We likely have a small positive gain accompanied by a meaningful reduction in user confusion.1
What we should do next: Given that shipping this to everyone only takes about a day of engineering, we should ship it. Continuing to run the test for another four weeks just to chase statistical significance on a small effect isn't a wise use of time2 when the engineering cost to launch is so low and support friction has already improved. Let's roll out the 5-step checklist and monitor downstream retention.
What a PM had to fix
1Hypothesis stated as factReframe it as a hypothesisStart again
Source: Readout
Activation: A 31.2%, B 32.9% (+1.7pp, 95% CI −1.4 to +4.8).
What we’d changeGive the interval: anywhere from a 1.4pp loss to a 4.8pp gain, so a gain isn't established. And the ticket drop wasn't split by arm, so it can't be credited to the new checklist.
2OtherFix itTargeted repair
Source: Options on the table
Running the test for another four weeks at current traffic would detect an effect of about 2pp.
What we’d changeWeigh the risk of a small activation loss, not only the one day of engineering, and say what result would justify the extra four weeks.
Check by check
Got wrong · 3
- Addresses the actual decisionOutput commits to shipping but does not state what result or condition would change that decision.
- Identifies material uncertaintyOutput does not name the specific unknowns that could change the decision (e.g., true effect could be zero or negative) and does not bound the uncertainty; it presents the effect as likely positive without acknowledging the CI includes negative values.
- Trusts the data before reading itNo trust signal (e.g., sample ratio, SRM check) is examined before interpreting the results.
Mixed · 2
- Uses the supplied evidence correctlyAll facts are drawn directly from the supplied context without invention.The two graders disagreed on this one.
- Avoids unsupported claimsInterpretations are labelled as 'likely' and 'meaningful reduction' is supported by ticket data; no claims presented as established fact that aren't.The two graders disagreed on this one.
Got right · 4
- Respects explicit constraintsThe note is under 300 words and respects the requested short note format.
- Produces the required deliverableThe output is a complete note to the onboarding team, within word limit, and could be acted on with light edits.
- Interprets power correctlyCorrectly explains that the test was not powered to detect a 1.7pp or 2pp shift given the 3pp MDE.
- Gets the base of every number rightPercentage differences and ticket counts are presented accurately with clear bases.
Grades and run details
Decision model 56 · LLM judge 7 of 10 checks
Decision model checks
- failUses the supplied evidence correctly7%
- partialAddresses the actual decision39%
- passRespects explicit constraints87%
- partialIdentifies material uncertainty73%
- failAvoids unsupported claims40%
- passProduces the required deliverable89%
- passInterprets power correctly74%
- failTrusts the data before reading it97%
- passGets the base of every number right55%
Run
- Run
- #1
- Time to output
- 6 s
- Submitted
- 25 Sept 2026