Tasks / Leadership

Write a performance review

Can the model write a review that is clear, fair and specific enough to change what the person does next?

Measures the modelTask type v1.1 · 2 tasksDifficulty

What AI gets right here, and what you’ll still have to catch

From 14 graded outputs by 7 models. 64% were usable with at most a quick edit.

Reliably right

  1. Produces the required deliverable100% pass
    The review summary, PIP recommendation, and note to Ines are complete, in the right form, and usable with light edits.
    GPT-6 Astra · ChatGPT · A PIP, or a bad month?
  2. Judges outcomes, not activity100% pass
    The rating is based on outcomes against goals (two exceeded, one failed launch) rather than activity or output volume.
    GPT-6 Astra · ChatGPT · A PIP, or a bad month?
  3. Weighs the whole period100% pass
    The review weighs the full year's results, explicitly balancing the two above-target outcomes against the one bounded failure, and guards against letting the Dispatch incident dominate.
    GPT-6 Astra · ChatGPT · A PIP, or a bad month?

Where it slips

  1. Identifies material uncertainty38% pass
    Does not explicitly name the specific unknowns that could change the decision (e.g., whether Lukas improves launch readiness); only says to reassess after the relaunch.
    GPT-6 Luna · API · A PIP, or a bad month?
  2. Avoids unsupported claims71% pass
    Presents 'not through negligence on his part' as an established fact without labelling it as a hypothesis, when the evidence only shows he was on leave and his deputy ran checks.
    Sonnet 5.5 · API · A PIP, or a bad month?
  3. Sets next goals as outcomes, with support75% pass
    Goals are partly process-oriented (implement a mandatory process, create a framework) and lack specific support from Ana beyond a general offer.
    Gemini 3.5 Flash-Lite · Gemini · Shipped a lot, moved nothing

How it’s graded

The checks come from what the best product leaders have said about doing this job well on Lenny’s Podcast. Each one names the guest it comes from: follow a name to the idea on the Lenny’s Podcast wiki.

  1. Clear and direct, with care

    Does the review say plainly what needs to change, in words the person couldn't misread, while showing it is written to help them succeed?

    Passes when Every main point is stated directly, with the specific change expected and the support on offer.

  2. Judges outcomes, not activity

    Does the review judge the person on the outcomes they achieved against their goals, rather than on how much they shipped or how busy they were?

    Passes when Rates against the goals' outcomes, with the evidence, and treats output as context, not the result.

  3. Names gaps you could see

    Is each area to improve described as specific, observable behaviour with what good would look like, rather than labels like 'be more strategic'?

    Passes when Every gap names what the person did or didn't do, in a specific situation, and what doing it well would look like.

  4. Weighs the whole period

    Does the review weigh the whole review period, rather than letting one recent event or one strong impression decide the verdict?

    Passes when Covers the whole period in proportion, and explicitly guards against a recent event or one impression dominating.

Plus our standard checks

Uses the supplied evidence correctly · Addresses the actual decision · Respects explicit constraints · Identifies material uncertainty · Avoids unsupported claims · Produces the required deliverable · and 2 written for each task, which you’ll see in the tasks below.

The tasks

Read the brief, then put up to three outputs side by side, each with the LLM judge’s verdict on every check. Highlights mark what a PM had to fix.

The brief

You're Director of Product at Railyard, and calibration is in five days. Ines Okoro, our VP Product, has drafted the calibration pre-read and suggested putting Lukas Brenner, one of your Senior PMs, on a performance improvement plan. Write, in no more than 1,100 words: (1) Lukas's review summary and the rating you propose, with the evidence; (2) your recommendation on the PIP, and if you recommend one, its key terms; (3) a short note to Ines on the evidence. The record is below.

What the model was given7 items: Lukas's goals and results this year, What happened with Dispatch v2, Ines's draft for the pre-read, Peer feedback, Feedback on record, HR policy on PIPs, A precedent
Lukas's goals and results this year1. Cut carrier onboarding time from 21 days to 10: done, now 9 days. 2. Launch Dispatch v2 by October: launched in October, then rolled back after six days. 3. Grow carriers using live tracking from 40% to 55%: reached 57%.
What happened with Dispatch v2It launched without support being briefed, and 340 support tickets came in the first week. It was rolled back after six days. Lukas was on approved leave the week before launch; his deputy ran the final launch checks. It's due to relaunch next quarter.
Ines's draft for the pre-read'Lukas: Below expectations. Not strategic enough, lacks product sense, and Dispatch was a disaster. Suggest a PIP.'
Peer feedbackThree of four peers are positive, citing the onboarding work and his collaboration. The Head of Operations is negative about how Dispatch was communicated.
Feedback on recordNo written feedback to Lukas this year about strategy or product sense. One conversation, in November, about launch readiness, after Dispatch.
HR policy on PIPsA PIP needs earlier documented feedback on the specific gap and a chance to improve. A PIP lasts 60 days and needs measurable success criteria.
A precedentLast year Priya, another Senior PM, had a launch rolled back after a similar support failure. She was rated Meets expectations, with no PIP.
What a strong answer doesThe answer key the graders mark against

Recommends against a PIP now: policy requires earlier documented feedback on the specific gap, and there is none on strategy or product sense, and only one conversation about launch readiness, after the fact. Rates Lukas Meets expectations (arguably higher on two of three goals met or beaten), weighing the whole year rather than October: onboarding time 21 to 9 days and live tracking 40% to 57% against one failed launch, which happened while he was on approved leave. Turns 'not strategic enough' and 'lacks product sense' into the observable gap the evidence does support: launch readiness, including briefing support and having a cover plan for his absence. Proposes documented feedback on that gap now, with clear expectations for the relaunch and a check-in after it. Notes the precedent: Priya was rated Meets with no PIP for a similar failure, so a PIP would be inconsistent. Pushes back on Ines firmly and respectfully, with the evidence.

Critical failures (cap the score at 40)
  • Recommends starting a PIP now, without the documented earlier feedback the policy requires
Task

Staff-level · v1.0 · synthetic · B2B SaaS, logistics, management, staff-level

The outputs

7 setups answered this brief. Pick up to three to read side by side.

Usable with a quick edit11 of 12 checks passed

The output is clear, evidence-based, and requires only minor wording tweaks; no re-checking of evidence or redoing of reasoning is needed.

Output

1. Lukas’s review summary and proposed rating

Proposed rating: Meets Expectations, with a significant development area in launch readiness and communication.

Lukas delivered strong results against two of his three goals. He reduced carrier onboarding time from 21 days to 9, beating the 10-day target, and increased carrier adoption of live tracking from 40% to 57%, above the 55% target.

Dispatch v2 launched in October as planned, but the launch was not successful: support had not been briefed, 340 tickets came in during the first week, and the product was rolled back after six days. Lukas was on approved leave the week before launch, and his deputy ran the final checks. That context matters when assessing individual responsibility for the checks, but it does not erase the product team’s launch outcome or the need to clarify Lukas’s ownership of readiness and communication. The relaunch next quarter will be an important opportunity to demonstrate improvement.

Peer feedback is largely positive: three of four peers cited his onboarding work and collaboration. The Head of Operations raised a concern about how Dispatch was communicated. Overall, the evidence supports recognizing Lukas’s substantial delivery while clearly addressing the failed launch. A Meets Expectations rating is also consistent with the precedent of a Senior PM rated Meets Expectations after a similar support-related rollback.

2. Recommendation on a PIP

Do not recommend a PIP at this time. HR policy requires earlier documented feedback on the specific gap and a chance to improve. The record contains no written feedback this year on strategy or product sense, and the only recorded conversation about launch readiness took place in November, after the Dispatch launch. That does not meet the stated prerequisite for a PIP. The current record also does not substantiate the draft’s broader claims that Lukas “lacks product sense” or is “not strategic enough.”

Instead, give Lukas direct, documented feedback now on the Dispatch readiness and communication failures, clarify his responsibilities for the relaunch, and set measurable launch-readiness expectations for that work. Reassess his performance with that evidence. This addresses the issue without bypassing the required feedback process.

3. Note to Ines on the evidence

Ines, I recommend revising the pre-read to distinguish the documented launch failure from the broader judgments about strategy and product sense, for which we have no recorded feedback. We should include the onboarding and tracking results, the rollback and support impact, the Operations feedback, and the approved-leave/deputy context. The November readiness conversation came after the launch, so it does not establish earlier feedback or an opportunity to improve for PIP purposes. Applying the same Meets Expectations rating used in Priya’s similar case would also support consistency.

Grades and run details

Decision model 96 · LLM judge 12 of 13 checks
Decision model checks
  • passUses the supplied evidence correctly87%
  • passAddresses the actual decision88%
  • passRespects explicit constraints79%
  • partialIdentifies material uncertainty28%
  • passAvoids unsupported claims63%
  • passProduces the required deliverable71%
  • passHolds the PIP to the policy and the record100%
  • passTreats Lukas like Priya96%
  • passClear and direct, with care47%
  • passJudges outcomes, not activity99%
  • passNames gaps you could see45%
  • passWeighs the whole period96%
Run
Run
#1
API response time
14 s
Submitted
5 Oct 2026

Check by check

Open a check to read the judge’s reasons. “Mixed” means the two graders disagreed.

Got wrong 1

Identifies material uncertaintyWrong

Does not explicitly name the specific unknowns that could change the decision (e.g., whether Lukas improves launch readiness); only says to reassess after the relaunch.

Got right 11

Uses the supplied evidence correctlyRight

All factual claims are taken directly from the supplied context with no inventions.

Addresses the actual decisionRight

Commits unambiguously to Meets Expectations and no PIP now, with conditions for reassessment after documented feedback and relaunch.

Respects explicit constraintsRight

Provides all three requested parts (review summary, PIP recommendation, note to Ines) and is well within the 1,100-word limit.

Avoids unsupported claimsRight

Interpretations are presented as recommendations or judgments, not as established facts.

Produces the required deliverableRight

The output is complete, in the right form for the VP Product, and usable with at most light edits.

Holds the PIP to the policy and the recordRight

Clearly shows that the policy requires earlier documented feedback, which is absent, and proposes documented feedback first instead of a PIP now.

Treats Lukas like PriyaRight

Raises Priya's similar rollback case and argues for consistency in rating and no PIP.

Clear and direct, with careRight

States the development area directly (launch readiness and communication) and specifies the feedback and measurable expectations to be set.

Judges outcomes, not activityRight

Rates against the three goal outcomes, not activity, and uses the evidence of results.

Names gaps you could seeRight

Gap is described as specific, observable behavior (Dispatch readiness and communication failures) with what good looks like (measurable launch-readiness expectations).

Weighs the whole periodRight

Weighs the whole year, explicitly balancing the two strong outcomes against the one failed launch, and does not let the recent event dominate.

Results

Every setup we’ve tested on this task type, across all its tasks and repeats, graded on the current checklist. Calibrated.

#Model · HarnessTask scoreDecision modelLLM judgeRunsCritical failures
1Opus 5.5withClaude91.792.32None
2GPT-6 AstrawithChatGPT93.892.32None
3Sonnet 5.5withAPI95.884.62None
4GPT-6.1 SolwithAPI97.984.62None
5GPT-6 LunawithAPI95.884.62None
6Gemini 3.5 Flash-LitewithGemini77.180.82None
7Gemini 3.8 FlashwithAPI83.357.72None

About the task

The PM job

Reviewing the performance of a PM you manage.

Why it matters

Reviews fail by being kind and vague, or by judging a whole year on its worst month. Either way, the person doesn't know what to change.

What good looks like

  • Clear and direct, with care
  • Judges outcomes, not activity
  • Names gaps in observable terms
  • Weighs the whole period, not the last month

Deliberately not measured

  • HR policy compliance beyond what the brief supplies
Capability tested

Feedback and judgement

The failure we’re looking for

Vague, diplomatic feedback, or a verdict driven by one recent event

Grading

Decision model and LLM judge, calibrated against a blind PM review