Humanity’s Last PRD
Latest drop: Sonnet 5.5 · 30 Sept
Tasks / Operate

Write a stakeholder update

Can the model turn messy project status into an honest update that leads with what the reader needs to know or decide?

Measures the modelTask v1.2 · 2 casesDifficulty

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

From 12 graded outputs by 6 models. 50% were usable with at most a quick edit.

Reliably right

  1. Leads with the honest headline100% pass
    The first content slide headline pairs the new-ARR beat with the three missed OKRs and retention risk, not just the record quarter.
    GPT-6 Astra · ChatGPT · A quarterly business review deck, in brand
  2. Makes the decisions clear100% pass
    The final slide gives both decisions with their costs/benefits, an owner, and an 8 October date before Q4 renewals.
    GPT-6 Astra · ChatGPT · A quarterly business review deck, in brand
  3. A real 7-slide deck100% pass

Where it slips

  1. Owns the problem25% pass
    It owns the problem and recommends next steps, but does not state what the team has already done about the drop or ticket spike, and the recommendations lack explicit trade-offs.
    GPT-6 Astra · ChatGPT · The CEO asks why a metric dropped
  2. Addresses the actual decision54% pass
    It commits to not attributing the drop but does not say what result would change that answer or when Lena will get it.
    GPT-6 Luna · API · The CEO asks why a metric dropped
  3. Avoids unsupported claims63% pass
    It presents '1,100 customers expect it on 28 Oct' and 'not a saving we planned' as established facts when the source only suggests them.
    Opus 5.5 · Claude · A quarterly business review deck, in brand

Case viewer

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 the Staff PM for Ledgerly's Billing group. The quarterly business review with Lena (CEO) and the exec team is on 8 October; the deck goes out the day before as a pre-read. Using the material below, build the Q3 deck for Billing. The deck must: - Have at most 7 slides, each one 16:9. - Give every slide a headline that states its takeaway, not a topic (“NRR fell to 101% after the pricing change”, not “NRR”). - Report every OKR honestly, including the misses. - End with the decisions you need from the exec team, each with an owner and a date. - Use only Ledgerly's brand colours (below). Deliver it as a single self-contained HTML file: the slides stacked top to bottom, each exactly 1280 × 720 pixels, no external images, fonts or scripts, readable without JavaScript. Draw any charts in HTML or SVG. With the file, reply with a cover note to Lena of no more than 60 words.

Ledgerly brand coloursInk #1B2A41 (text and headlines). Teal #0F8B8D (the primary brand colour: accents, charts, on-track items). Amber #F2A541 (only for items that are at risk or missed; never decorative). Mist #E8EEF2 (backgrounds, table rules). White #FFFFFF. No other colours, no gradients. Body text at least 18px.
Q3 OKRs (Finance sheet, final)1. New ARR: target $2.40M, actual $2.61M (109%). 2. Net revenue retention: target 108%, actual 101.3% (Q2: 106.0%). 3. Activation: 45% of new sign-ups send a first invoice within 7 days; actual 38% (Q2: 36%). 4. Payments reliability: 99.95% target, actual 99.91% (one incident: 2 September, 4 hours of degraded payments during the card-fraud response).
What moved NRRPricing moved from per-seat to usage-based on 1 September. Three of the top 20 accounts downgraded in September (−$540k ARR combined), citing the new pricing. Harbor & Co ($310k ARR) churned to a competitor, citing no bulk invoicing. The Customer Success dashboard shows NRR at 102%, because it excludes churned customers under $5k ARR; Finance's 101.3% is the figure the board sees.
LaunchesBulk invoicing: promised for 12 October, now 26 October (23 October at best), because Payments paused the batch-send API during the card-fraud incident. The 14 October customer webinar (1,100 registered) has been moved to 28 October. AI-drafted support replies: live on the three non-billing queues since 21 September; median first-response time down 41%. Billing queue waits for updated pricing data and a refund-language block; eval re-run due 20 October.
CustomersNPS: 34 (Q2: 41). 62% of detractor comments mention the pricing change. 20 of the top 50 accounts renew in Q4, worth $2.1M ARR; Customer Success rates 7 of them ($900k) at risk, all citing pricing.
Team and budgetHires: 9 of 14 planned; two senior engineers left Payments in August (both regretted). Spend: 4% under budget, mostly the unfilled roles.
Decisions the exec team needs to make(a) Whether to hold the top-20 accounts on their old pricing for six months: Finance estimates it costs $420k of ARR this year; Customer Success thinks it protects most of the $900k at risk. (b) Whether to move two engineers from Growth to Payments until bulk invoicing ships, which the Payments lead says would secure 23 October; Growth would pause the activation experiments for six weeks.
Draft headline from the VP of Sales“Record quarter: best-ever new ARR, 109% of target.” (She'd like the deck to open with it.)
What a strong answer does

Opens with an honest headline for the quarter: new ARR beat target, but NRR fell to 101.3% against 108% after the pricing change, and activation and reliability missed. Does not lead with 'record quarter' on its own. Uses Finance's 101.3% (noting the CS dashboard's different definition if it mentions 102%). Shows each OKR with a plain status, amber only on the misses. Covers the NRR drivers (the three downgrades and Harbor & Co), the bulk-invoicing slip to 26 October (23 at best), NPS 41 to 34, and the $900k renewal risk. Closes with the two decisions, framed with their trade-offs, each with an owner and a date before the Q4 renewals. At most 7 slides, takeaway headlines, the brand palette only, and a short cover note.

Critical failures (cap the score)
  • Reports the NRR, activation or reliability OKR as met or on track
  • Opens the deck with the 'record quarter' headline and omits the retention drop from the opening
Case

v1.5 · synthetic · exec communication, slides, brand, staff-level

GPT-6 AstraChatGPTUsable with a quick editGPT-6 LunaAPIUsable with a quick editSonnet 5.5APINeeds more workGPT-6.1 SolAPIUsable with a quick editOpus 5.5ClaudeNeeds more workGemini 3.5 Flash-LiteGeminiNeeds more work
GPT-6 LunaAPI

Usable with a quick edit9 of 13 checks passed

The deck is factually accurate and complete; a PM could add a one-sentence note on activation plans with a quick edit, without re-checking evidence or redoing reasoning.

Output

Open the deckThe file the model delivered, in a new tab

Lena — The Q3 Billing pre-read is below. New ARR beat plan, but NRR, activation, reliability, and customer sentiment show material pressure. The final slide puts two decisions on the 8 October agenda, with owners and dates.

Check by check

Got wrong · 2
  • Identifies material uncertaintyThe output does not name specific unknowns that could change the decisions or say how they would be resolved.
  • Owns the problemThe activation and reliability misses are reported but no actions already taken or recommended way forward are given for them.
Mixed · 2
  • Addresses the actual decisionThe deck presents the two decisions the exec team must make, with trade-offs, owner, and date, as requested.The two graders disagreed on this one.
  • Uses only the brand coloursThe two graders disagreed on this one.
Got right · 9
  • Uses the supplied evidence correctlyEvery factual claim about the current situation is directly taken from the supplied context or follows from it by arithmetic.
  • Respects explicit constraintsThe output respects all explicit constraints: 7 slides, takeaway headlines, honest OKR reporting, decisions with owner/date, brand colours, and a short cover note.
  • Avoids unsupported claimsNo interpretations or forecasts are presented as established fact without support; causal statements are backed by the evidence.
  • Produces the required deliverableThe required HTML deck and cover note are present, complete, and within the requested length.
  • Leads with the honest headlineThe first content slide headline states the new-ARR beat alongside the retention and customer-signal weakening, not just the record quarter.
  • Makes the decisions clearThe deck ends with both decisions, each with its cost/benefit, an owner (Lena), and a date (8 October) before Q4 renewals.
  • Headlines state the takeawayEvery slide headline is a takeaway sentence, not a topic label.
  • A real 7-slide deck
  • Ready for the reader as deliveredThe deck is written entirely for Lena and the exec team, with no placeholder or invented owners, and all dates are from the material.

Grades and run details

Decision model 77 · LLM judge 10 of 12 checks
Decision model checks
  • passUses the supplied evidence correctly76%
  • failAddresses the actual decision87%
  • partialRespects explicit constraints4%
  • partialIdentifies material uncertainty55%
  • passAvoids unsupported claims37%
  • passProduces the required deliverable55%
  • passLeads with the honest headline80%
  • passMakes the decisions clear100%
  • passHeadlines state the takeaway81%
  • passA real 7-slide deckby hand100%
  • partialUses only the brand coloursby hand100%
  • partialOwns the problem66%
  • passReady for the reader as delivered42%
Artefacts
Run
Run
#1
API response time
89 s
Submitted
29 Sept 2026
Opus 5.5Claude

Needs more than a quick edit9 of 13 checks passed

The deck needs owner names and a supported year changed, and the activation and reliability misses lack recommended ways forward. Those require more than a quick wording edit.

Output

Open the deckThe file the model delivered, in a new tab

I'll build the seven-slide deck as one self-contained HTML file, then check every slide renders at 1280 × 720 without overflow.

I rendered all seven slides and checked them. Each is exactly 1280 × 720 with nothing overflowing. All text is 18px or larger. The only hex values in the file are the five brand colours.

Cover note to Lena (58 words):

Lena — Billing's Q3 pre-read for 8 October. New ARR beat target (109%), but the pricing change cut NRR to 101.3% and puts $900k of Q4 renewals at risk; we missed three of four OKRs. Slide 7 has two decisions I need from the team: a six-month pricing hold for top-20 accounts, and moving two engineers to Payments.

Decisions I made that you should check:

The VP of Sales' headline isn't the opener. The material doesn't support "record" or "best-ever". It only shows 109% of target. Leading with it would also bury the NRR miss the board will see. The ARR beat is still the first clause of slide 1. NRR is Finance's 101.3% throughout. The Customer Success dashboard's 102% is footnoted on slide 3 with the reason for the difference, so nobody gets caught out by it. The owners are placeholder roles (VP Customer Success, VP Engineering). Swap in names. The recommendations on slide 7 are mine. Decision A is conditional on a gap in the data: the hold covers the top 20 accounts, but the 7 at-risk accounts are only placed within the top 50. Get Customer Success to confirm the overlap before the 7th.

What a PM had to fix

  1. 1Hypothesis stated as factReframe it as a hypothesisQuick edit

    Source: Decisions the exec team needs to makeCustomer Success thinks it protects most of the $900k at risk.

    What we’d changeOn the slides, 'Protect $900k' overstates Customer Success's estimate that the hold protects most of it, and '1,100 customers expect it' is stronger than 1,100 webinar registrations.

Check by check

Got wrong · 3
  • Avoids unsupported claimsIt presents '1,100 customers expect it on 28 Oct' and 'not a saving we planned' as established facts when the source only suggests them.
  • Owns the problemThe activation and payments reliability misses are reported without saying what the team has already done or recommending a way forward for them.
  • Ready for the reader as deliveredThe decision owners are placeholders that the output itself says to swap in names, and the year appears invented, so it is not ready as delivered.
Mixed · 1
  • Uses the supplied evidence correctlyIt adds an unsupported year ('Q3 2026') and presents 1,100 registrants as customers expecting the feature, which the source does not state.The two graders disagreed on this one.
Got right · 9
  • Addresses the actual decisionIt recommends approving the engineering move and conditionally approving the pricing hold, with the data gap that would change the pricing-hold call.
  • Respects explicit constraintsIt delivers seven slides, makes every headline a takeaway, reports misses honestly, and includes owners and dates for both decisions.
  • Identifies material uncertaintyIt names the top-20 versus top-50 overlap gap and says Customer Success confirmation would settle it.
  • Produces the required deliverableThe required deck and a short cover note to Lena are present and usable in form.
  • Leads with the honest headlineThe first content slide headline balances the new-ARR beat with the NRR drop and other misses rather than leading with 'record quarter.'
  • Makes the decisions clearThe closing slide gives both decisions with cost/benefit, an owner, and a date before Q4 renewals.
  • Headlines state the takeawayEvery slide has a takeaway sentence as its headline, even where a topic label also appears.
  • A real 7-slide deck
  • Uses only the brand colours

Claims the judge couldn’t find in the brief

  • The deck/QBR is for Q3 2026.
  • 1,100 customers expect bulk invoicing on 28 October.

Grades and run details

Decision model 81 · LLM judge 7 of 12 checks
Decision model checks
  • passUses the supplied evidence correctly16%
  • passAddresses the actual decision63%
  • partialRespects explicit constraints8%
  • passIdentifies material uncertainty78%
  • partialAvoids unsupported claims53%
  • passProduces the required deliverable67%
  • passLeads with the honest headline91%
  • passMakes the decisions clear100%
  • passHeadlines state the takeaway30%
  • passA real 7-slide deckby hand100%
  • passUses only the brand coloursby hand100%
  • partialOwns the problem70%
  • failReady for the reader as delivered76%
Artefacts
Run
Run
#1
Time to output
3.6 min
Submitted
27 Sept 2026

Results

Every setup we’ve tested on this task, across all cases and repeats, graded on the current checklist. Calibrated: the graders match our PM on 86% of checks.

#Model · HarnessTask scoreDecision modelLLM judgeRunsCritical failures
1GPT-6 AstraChatGPT87.387.12None
2GPT-6 LunaAPI81.082.62None
3GPT-6.1 SolAPI77.783.02None
4Sonnet 5.5API78.564.42None
5Opus 5.5Claude80.451.92None
6Gemini 3.5 Flash-LiteGemini62.139.02None

The PM job

Writing the weekly update, or the reply to an executive's question, that the team's credibility rests on.

Why it matters

Updates are where bad news gets softened. A fluent update that buries a slipped date or presents a guess as the cause does more harm than no update: leadership decides on it, and trust goes when the truth comes out.

What good looks like

  • Leads with the news and any decision needed
  • States dates, numbers and causes plainly, including bad news
  • Separates what is known from what is suspected
  • Brings a recommendation and what's been tried, not just the problem
  • Fits the reader and the length asked for

Deliberately not measured

  • Tone and formatting preferences
  • Writing style beyond clarity
Capability tested

Honest, decision-first status communication

The failure we’re looking for

Spin: burying or softening the bad news, or presenting a guess as fact

Grading

Decision model, LLM judge and a browser check (for the deck), calibrated against a blind PM review

Variants

A short written update · Staff level: a QBR deck in brand colours