Tasks / Strategy

Challenge an idea

Can the model find the strongest reason an idea may fail, backed by evidence?

Task type v1.2 · 2 tasksLast changed 6 Oct 2026 · ChangelogDifficulty

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

From 16 graded outputs by 8 models. 44% were usable with at most a quick edit.

Reliably right

  1. Finds the load-bearing assumption100% pass
    The critique targets the assumption that agencies' growth is limited by a shortage of new leads, using referral, abandoned-outbound, and capacity evidence.
    GPT-6.1 Sol · API · An AI SDR for small agencies
  2. Uses the interviews faithfully100% pass
    All quotes are accurately taken from the transcripts and correctly attributed to A05, A04, and A08.
    GPT-6.1 Sol · API · An AI SDR for small agencies
  3. Finds the timeline that sinks it100% pass
    Cites 9-month build and concludes Q1 launch is unsupported.
    GPT-6 Astra · ChatGPT · Five billion dollars, on paper

Where it slips

  1. Avoids unsupported claims55% pass
    Presents the existence of local taxes and multi-state complexity as fact without support from the context.
    GPT-6 Astra · ChatGPT · Five billion dollars, on paper
  2. Uses the supplied evidence correctly55% pass
    Claims that local taxes and multi-state operations affect eligibility are not supported by the supplied context, which only mentions state-by-state tax rules.
    GPT-6 Astra · ChatGPT · Five billion dollars, on paper
  3. Rebuilds the market size81% pass
    It uses the $150 price for 10+ staff businesses instead of the higher UK revenue per customer for those segments, so the market size is understated and not correctly rebuilt.
    GPT-6 Luna · API · Five billion dollars, on paper

How it’s graded

Each check is built on how world-class product and growth leaders do this work, as they’ve described it on Lenny’s Podcast, and names the leader it comes from.

  1. Finds the need behind the idea

    Does the critique identify the underlying need the idea is meant to serve, and offer at least one other way to meet that need, at a different cost, saying what would have to be dropped for it?

    Passes when States the need behind the proposal, and gives an alternative way to meet it with its cost and what it displaces.

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 · Tigers, not paper tigers · and 2 written for each task, which you’ll see in the tasks below.

The tasks

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

The brief

You're the VP Product at Halyard. Our CEO is taking the US launch plan below to the board next week and has asked you to challenge it hard first. Write a memo of no more than 1,000 words: what the plan gets wrong, what would sink it, what's less scary than it looks, and what you'd propose instead. The deck excerpt and our data are attached.

What the model was given4 items: about_halyard.md, ceo_board_deck_excerpt.md, uk_customers_by_size.csv, us_small_business_stats.md
about_halyard.md3 lines · Download
# About Halyard in the UK

Payroll and HR for small businesses. 14,800 customers, $3.9M ARR, five years old. UK payroll rules are built in; US payroll would need state-by-state tax rules (the team estimates 9 months of work for the first 10 states).
ceo_board_deck_excerpt.md5 lines · Download
# US launch (CEO's board deck, excerpt)

- Market: 33 million US small businesses x our UK price of £120 ($150) a year = about $5B. "Even 1% is $50M."
- Plan: launch in the US in Q1, $2.5M budget, hire a US sales team of 6, target $5M ARR in year one.
- Why now: a competitor raised in the US; we need to get there first.
uk_customers_by_size.csv4 rows · Download
company_size,uk_customers,share_of_uk_customers_pct,retained_at_12_months_pct,avg_revenue_usd_per_year
Sole trader,6100,41,18,150
2-9 staff,5300,36,33,150
10-49 staff,2900,20,71,620
50-249 staff,480,3,78,2400
us_small_business_stats.md5 lines · Download
# US small businesses (government statistics)

- 33.2 million small businesses in total.
- About 27.1 million have no employees (sole proprietors).
- About 6.1 million have employees; of those, about 1.1 million have 10 to 249 employees.
What a strong answer doesThe answer key the graders mark against

Shows the $5B market is the wrong number. It multiplies every US small business by the UK price, but in the UK only businesses with 10+ staff stay (71% and 78% at 12 months) and pay more ($620 to $2,400 a year); sole traders and 2-9 businesses mostly leave (18% and 33%). Most US small businesses (27.1M of 33.2M) have no employees and don't need payroll at all; the comparable US market is about 1.1M businesses with 10 to 249 staff, worth roughly $0.7B to $1B at UK revenue per customer, not $5B. The tiger: US payroll needs state-by-state tax rules, about 9 months for the first 10 states, so a Q1 launch with payroll isn't possible and $5M ARR in year one would need thousands of 10+ staff customers from a standing start. Dismisses the 'first mover' worry as less scary: a competitor's raise doesn't make a market winner-takes-all. Proposes instead: target 10+ staff businesses, start with HR in the US while payroll is built for a few high-density states, test demand with a small budget and a clear threshold before hiring a sales team, and fix the UK mix towards 10+ staff companies meanwhile.

Critical failures (cap the score at 40)
  • Endorses the $5B market size
Task

Staff-level · v1.0

The outputs

8 setups answered this brief.

Usable with a quick edit8 of 10 checks passed

Minor unsupported claim about crowded market can be edited out; core reasoning and evidence use are solid.

Output

MEMO

To: CEO From: VP Product Re: Challenge to the US launch plan before the board

Bottom line: The market story is wrong, the timeline is not achievable, and the budget can't carry the target. The opportunity is real but much smaller and more specific than $5B. I'd take the board a staged plan with gates, not a Q1 launch.

---

What the plan gets wrong

1. The TAM is built on the wrong customers. 33M × $150 assumes every US small business buys our product at our UK sole-trader price. But 27.1M of those firms have no employees. Payroll is not their problem. Our own data shows sole traders retain at 18% at twelve months and bring in $150 a year. Our customers who retain are the ones with staff.

2. The right pool is about 1.1M firms, and the "1%" math shrinks accordingly. The government figure is 1.1M businesses with 10–249 employees. Our UK revenue is concentrated in the 10–49 and 50–249 segments: about 23% of customers but roughly 60%+ of revenue, with 71–78% retention. Taking a blended ~$620 ARPU, 1% of 1.1M firms is about 11,000 customers and roughly $7M ARR, not $50M. The deck's own logic, applied to the right segment, gives a much smaller prize.

3. The $5M year-one target is not credible. At $620 ARPU, $5M needs about 8,000 paying US customers in twelve months. It took us five years to reach 14,800 UK customers, with a product that is already built. At $150, it needs 33,000, which only works if we sell to the segment that churns most.

4. Q1 is not feasible. The US needs state-by-state payroll tax rules. Our team estimates nine months for the first ten states alone. Q1 launch means either launching with almost no state coverage or launching with a product we can't legally run for most prospects. A firm with employees in an unsupported state cannot onboard at all.

5. "Get there first" is the wrong reason. US payroll is a crowded market with entrenched incumbents, and a competitor's raise means they face the same state-tax build we do. Being early doesn't create a moat in payroll. Being correct on compliance does.

6. The budget doesn't match the plan. Six US quota-carrying reps at a fully loaded cost of roughly $150–180K each is about $1M a year before marketing, tax build, legal, compliance, or US support. That leaves very little of the $2.5M for everything else. (These are my estimates. Please check them against Finance's hiring costs.)

---

What would sink it

  • Compliance liability. Wrong withholding or filing in a state is our error, with penalties landing on our customers. One public failure in an early state would damage referrals across the whole US business.
  • Selling to the wrong segment. If sales pursues sole traders and 2–9 employee firms because the TAM looks big, we'll be acquiring customers at $150 ARPU who churn at 67–82% within a year. CAC payback will never work.
  • Hiring ahead of proof. Six reps with quotas before we know which buyer, which price, and which state set will produce a pipeline we can't convert.
  • Support load. Multi-state questions are hard, and US support can't be staffed from London on a launch timeline.
  • Burn without a gate. If US spend starts before UK growth is secure, a US miss would hit our core business's cash position.

---

What's less scary than it looks

  • The product already works where it matters. Our best UK segments retain at 71–78%. We don't need a new product thesis, just a US version of what works.
  • The tax build is bounded. Nine months for ten states is a real cost, but it's finite. Ten states cover roughly half the US population, so coverage is a sequencing problem. We could also evaluate licensing state tax content from a vendor to cut the timeline.
  • The competitor raise is validation. It shows investors believe in US SMB payroll demand. It also shows we'd be competing in a market where a credible challenger still needs years to build coverage.
  • We don't need a Q1 launch to have a US business. A focused pilot can prove demand within two quarters at a fraction of the cost.

---

What I'd propose instead

I'd ask the board to approve a staged program with explicit gates.

Redefine the market in the deck. The target customer is a US business with 10–249 employees. That's about 1.1M firms and a credible multi-million-dollar opportunity, and we should say so.

Stage 1: Validate (months 0–6, ~$300K). Sign 40–60 design-partner firms with 10–249 employees across two states, one large state and one with simpler rules. Test activation, willingness to pay at $600+ ARPU, and 90-day engagement. Also test a partner channel: accountants and bookkeepers serve our best-fit firms and may be cheaper to reach than direct sales.

Stage 2: Build (months 6–15, ~$800K). Build or license state coverage for the top ten states. Hire one or two sales and customer success people, with the founder leading enterprise-style deals. Gate: pilot cohort retention tracking to 70%+ and CAC payback under 18 months.

Stage 3: Scale (only after gates). Expand sales headcount and marketing against measured unit economics.

Revised target: $1M US ARR by month 24, which is roughly 1,600 customers at $620 ARPU. That is ambitious but defensible, and it's the number the board should hold us to.

The ask: Approve Stages 1 and 2 (about $1.1M) now, with Stage 3 contingent on gate review. Do not approve a $2.5M Q1 launch with a $5M year-one target.

---

I know this is a harder message than the deck. But a board that approves the current plan will be disappointed in twelve months. A board that approves a gated path will get real evidence before committing the big money. I'd rather take the second case to them.

Claims the judge couldn’t find in the brief

  • US payroll is a crowded market with entrenched incumbents.

Grades and run details

Decision model 85 · LLM judge 82
Decision model checks
  • failUses the supplied evidence correctly22%
  • passAddresses the actual decision99%
  • passRespects explicit constraints50%
  • passIdentifies material uncertainty94%
  • partialAvoids unsupported claims66%
  • passProduces the required deliverable90%
  • passRebuilds the market size98%
  • passFinds the timeline that sinks it100%
  • passTigers, not paper tigers57%
  • passFinds the need behind the idea61%
Run
Run
#1
API response time
31 s
Submitted
8 Oct 2026

Needs more than a quick edit8 of 10 checks passed

The output includes unsupported claims about US payroll rules (federal/local) and market stickiness that a PM would need to verify before using, so it cannot be used without re-checking evidence.

Output

MEMO: US launch plan, challenge review To: CEO | From: VP Product

Bottom line: The direction is defensible, but the plan isn't ready for the board. The market is about a fifth the size the deck claims, the Q1 launch date conflicts with our own engineering estimate, and the $5M year-one target is unreachable. I'd take a staged version instead.

---

What the plan gets wrong

1. The $5B market is wrong by roughly 5x. The deck multiplies all 33.2M US small businesses by $150. But 27.1M of them have no employees, so they have no payroll to run. Our own UK data shows how little this segment is worth to us:

  • Sole traders are 41% of UK customers but only about 20% of revenue, and just 18% are still with us at 12 months.
  • Firms with 10+ staff are 23% of customers but about 63% of revenue, with 71–78% retention.

Our proven segment in the US is the 1.1M firms with 10–249 employees. At our UK blended revenue for that group (about $870 per customer), that's roughly $1B. "Even 1%" is about $10M, not $50M. I'd exclude the ~5M micro-employers. In the UK, 2–9 staff firms pay $150 and only 33% stay a year.

2. The timeline contradicts itself. The team estimates 9 months of work for the first 10 states. A Q1 launch means selling a product that doesn't exist, or one that only works in a few states. Ten states is also only about half the US population, by my rough estimate, so a national sales team would be pitching to prospects we can't serve.

3. $5M ARR in year one is out of reach. It exceeds the ARR we built in five years in the UK. At ~$870 per customer it needs about 5,700 customers, roughly 950 per rep from a standing start. With a 9-month build, year-one revenue would be close to zero.

4. "A competitor raised" isn't a reason to launch now. We can't win a spending race with $2.5M against a funded rival. Payroll is also a sticky, slow-switching category, so launching early earns us little. Launching with wrong tax calculations would cost us far more.

What would sink it

  • Compliance failures. A wrong withholding or a missed filing means customers pay penalties and blame us. In the UK, rules are built in and we know them. In the US we'd face federal, state and local rules, each with its own filings. One bad quarter in the first cohort could end our reputation with the segment we need.
  • Targeting the wrong customer. If the sales team chases volume, it will sign small firms that churn at UK micro-segment rates. Acquisition cost would never pay back.
  • Draining the UK business. Nine months of engineering on tax rules comes out of the roadmap for the business that funds everything. UK retention in the smallest segments is already weak, and we'd be neglecting it.
  • Burning the budget before learning anything. Six hires plus a 9-month build could consume most of $2.5M, about 64% of current ARR, before we know whether US customers retain like UK ones. I need to confirm whether the $2.5M includes the engineering cost. If it doesn't, the real ask is larger.
  • Missing the target. A $5M goal that slips will damage board confidence in everything else we present.

What's less scary than it looks

  • The smaller market is still big. About $1B is over 200x our current ARR. We don't need $5B to justify the US.
  • The competitor raise. It validates demand, but funding doesn't fix the state-by-state build, which slows them as well. Nothing here is lost by launching in 12–18 months instead of 3.
  • The 9-month estimate. It's a well-scoped build with a known end date, and a tax-calculation partner or API might shorten it. I'd evaluate build vs. buy before committing.
  • UK retention in micro-segments. It looks alarming, but it's a UK issue we'd avoid importing by targeting 10–249 staff firms, where our retention is strongest.

What I'd propose instead

Phase 0 (now to ~Q3, ~$0.5–0.7M): - Decide build vs. buy for the tax engine. - Pick 3–4 launch states by density of 10–249 staff firms. - Recruit 15–20 design-partner customers. - Hire a US head of sales/GTM and one compliance specialist, not six reps.

Phase 1 (launch in 3–5 states once compliance is proven, ~$1M): - Sell only to 10–249 staff firms with 2 reps and dedicated onboarding. - Set the target at about 300 customers and ~$0.25–0.3M ARR twelve months after launch. That's my estimate, based on UK segment pricing.

Phase 2 (release the remaining ~$1M, expand states and team) only if we hit gates: - 12-month retention of at least 70% in the first cohort. - Zero material filing errors. - Acquisition cost paying back within an agreed window.

This puts about $0.5–0.7M at risk before we learn anything, rather than $2.5M, and it gives the board a credible plan with checkpoints.

Before the board meeting

  1. Reconcile ARR. Our segment table implies about $4.66M (customers × average revenue), but the deck and company profile say $3.9M. A board member will do this multiplication. We need to know whether the gap is discounting, churn timing, or stale data.
  2. Confirm what the $2.5M covers, particularly engineering and compliance.
  3. Restate the market as ~$1B core, with the logic shown.
  4. Check price transfer. UK per-segment pricing may not hold in the US, so the design-partner phase should test willingness to pay.

I'm happy to walk through the numbers before you finalize the deck.

Grades and run details

Decision model 85 · LLM judge 73
Decision model checks
  • failUses the supplied evidence correctly23%
  • passAddresses the actual decision81%
  • passRespects explicit constraints59%
  • passIdentifies material uncertainty99%
  • partialAvoids unsupported claims68%
  • passProduces the required deliverable82%
  • passRebuilds the market size99%
  • passFinds the timeline that sinks it100%
  • passTigers, not paper tigers78%
  • passFinds the need behind the idea30%
Run
Run
#1
API response time
46 s
Submitted
6 Oct 2026

Needs more than a quick edit8 of 10 checks passed

The 76% revenue share error would require rechecking the data and correcting the figure before use. A product manager could not use it as-is without fixing that factual mistake.

Output

To: CEO and Board From: VP Product Subject: US expansion: approve validation, not the proposed launch

Recommendation: Do not approve the current Q1 launch, six-person sales team, or $5M year-one ARR commitment. The US opportunity deserves investigation, but this plan mistakes a large business population for an addressable payroll market, ignores our strongest customer evidence, and commits to distribution before establishing product readiness.

What the plan gets wrong

1. The market calculation counts the wrong customers at the wrong price.

Of 33.2 million US small businesses, 27.1 million have no employees. They are not a credible default market for an employer payroll product. Some may have relevant needs, but we must establish those rather than count every sole proprietor.

Our UK results argue against prioritizing this population:

SegmentCustomersAnnual revenue/customer12-month retention
------:---:---:
Sole trader6,100$15018%
2–9 staff5,300$15033%
10–49 staff2,900$62071%
50–249 staff480$2,40078%

Customers with 10–249 staff represent roughly 23% of customers but 76% of annual revenue implied by this data. The relevant starting market is the approximately 1.1 million US employers in that size range, narrowed further by geography, payroll complexity, and product fit.

At our UK segment prices, that population represents $682 million–$2.64 billion in hypothetical annual revenue—not a validated TAM. We lack its size mix, US willingness to pay, and the share we could actually serve. “Even 1%” supplies no acquisition strategy.

2. The year-one target has no operating bridge.

At $150 annually, $5 million ARR requires about 33,333 active customers—more than twice our entire UK customer base after five years. At $620, it requires approximately 8,065; at $2,400, 2,083.

With six sellers, the $620 scenario requires each to acquire about 1,344 customers annually before allowing for ramp time or churn. There is no evidence here for the lead volume, conversion, onboarding capacity, pricing, or retention necessary.

The $2.5 million budget is an allocation, not an acquisition model. We need separate estimates for compliance engineering, operations, support, acquisition, and contingency.

3. “Why now” is competitive anxiety, not customer evidence.

A competitor’s fundraising neither proves demand for Halyard nor makes our product ready. Being first matters less than paying employees correctly and retaining employers.

What would sink it

Compliance failure is the existential risk. Payroll mistakes create customer harm, remediation costs, and reputational damage. The team estimates nine months merely to build rules for the first ten states. Unless work is already sufficiently advanced, that contradicts Q1 readiness. Rule implementation also does not establish filing, remittance, testing, exception handling, or operational readiness.

A state-limited launch must constrain employee locations and payroll complexity—not merely customer headquarters. Multi-state employers can breach that boundary immediately.

Retention could make growth economically hollow. Even our best UK segments lose 22–29% of customers by month twelve. We should investigate whether this reflects business closures, product failures, poor fit, or measurement issues. We cannot assume better US performance while adding regulatory and operational complexity.

Premature hiring could consume the budget before learning occurs. Six sellers cannot compensate for an unready product or an unidentified buyer. Low-price segments are particularly unlikely to support conventional sales-led acquisition.

What is less scary than it looks

We do not need nationwide coverage or millions of customers to establish a worthwhile business. A tightly bounded employer segment offers ample room for a meaningful foothold.

Nor must we automatically build the entire US payroll stack ourselves. A payroll infrastructure partner could reduce time and technical risk. It would not remove our obligations to customers, integration risk, or the need to understand liability and unit economics.

Finally, our UK data contains a genuine positive signal: larger employers pay substantially more and retain substantially better. That is a credible hypothesis to test—not proof that it transfers to the US.

What I propose instead

Approve a staged US validation program, with a first tranche capped at $300,000 and further spending conditional on evidence.

  1. Validate the buyer over 8–12 weeks. Start with 10–49-person employers, where we have the strongest combination of customer volume, revenue, and retention. Interview buyers and test paid commitments at US-specific prices. In parallel, diagnose UK churn and compare build-versus-partner economics.
  1. Choose one narrowly serviceable footprint. Select geography based on customer demand and compliance feasibility. Explicitly exclude unsupported employee locations and payroll cases. Do not announce a live-payroll date before readiness is independently reviewed.
  1. Run a paid, founder-led pilot with 20–30 employers. Hire US payroll/compliance expertise before a sales team. Measure payroll accuracy and timeliness, onboarding effort, support costs, willingness to pay, and early retention. Early results will not substitute for twelve-month retention evidence.
  1. Release expansion funding only against gates. Require no unresolved critical payroll defects, demonstrated operational controls, positive contribution economics, and a credible acquisition model targeting under twelve-month CAC payback. Hire sellers only after that motion is repeatable.

Replace $5 million ARR with a conditional first-year objective of 100–200 paying employers after readiness, roughly $62,000–$124,000 annualized at the UK 10–49 price benchmark. That is a learning milestone, not a forecast.

The board should fund the next decision, not an unsupported promise of scale.

Claims the judge couldn’t find in the brief

  • 10-249 staff represent 76% of annual revenue.

Grades and run details

Decision model 100 · LLM judge 73
Decision model checks
  • passUses the supplied evidence correctly50%
  • passAddresses the actual decision99%
  • passRespects explicit constraints55%
  • passIdentifies material uncertainty100%
  • passAvoids unsupported claims38%
  • passProduces the required deliverable84%
  • passRebuilds the market size82%
  • passFinds the timeline that sinks it100%
  • passTigers, not paper tigers78%
  • passFinds the need behind the idea57%
Run
Run
#1
API response time
51 s
Submitted
6 Oct 2026

Check by check

Where the outputs differ comes first. Open a check to read the judge’s reasons. “Mixed” means the two graders disagreed.

Where they differ 2

Uses the supplied evidence correctlyWrongWrongMixed
Haiku 5.5 · API

Claim that US payroll is a crowded market with entrenched incumbents is unsupported by supplied context.

Sonnet 5.5 · API

The output claims US payroll involves 'federal, state and local rules' but the supplied context only mentions state-by-state tax rules, and it presents 'payroll is a sticky, slow-switching category' as fact without support.

GPT-6.1 Sol · API

The memo incorrectly states that 10-249 staff represent 76% of annual revenue; the correct figure from the data is 63%.

Avoids unsupported claimsWrongWrongMixed
Haiku 5.5 · API

States the US payroll market is crowded with entrenched incumbents as a fact without evidence or hedging.

Sonnet 5.5 · API

It presents 'payroll is a sticky, slow-switching category' as an established fact, and 'federal, state and local rules' as a given, neither of which is in the supplied evidence.

GPT-6.1 Sol · API

The 76% revenue share is presented as a fact from the data but is incorrect, making it an unsupported claim.

All got right 8

Addresses the actual decisionRightRightRight
Haiku 5.5 · API

Commits to a staged plan with gates, rejecting Q1 launch, framed for CEO, with conditions for scaling.

Sonnet 5.5 · API

The memo commits to a staged alternative early, frames it for the CEO, and specifies gates that would change the call.

GPT-6.1 Sol · API

The memo clearly recommends not approving the launch and proposes a staged validation program with conditions, framed for the CEO and board.

Respects explicit constraintsRightRightRight
Haiku 5.5 · API

Memo is within 1,000 words and addressed to CEO as requested.

Sonnet 5.5 · API

The output is a memo under 1,000 words addressed to the CEO, respecting the form and length constraint.

GPT-6.1 Sol · API

The output is a memo under 1,000 words, addresses the CEO and board, and respects the requested form.

Identifies material uncertaintyRightRightRight
Haiku 5.5 · API

Identifies unknowns (buyer, price, state set, build time) and uses gates to resolve them with measurable triggers.

Sonnet 5.5 · API

It names specific unknowns (budget coverage, ARR discrepancy, US pricing transfer) and says how to resolve them before the board meeting.

GPT-6.1 Sol · API

It names unknowns like US willingness to pay, size mix, and retention causes, and ties further funding to evidence gates.

Produces the required deliverableRightRightRight
Haiku 5.5 · API

Memo format, to CEO, actionable, and within the word limit.

Sonnet 5.5 · API

The memo is complete, in the right form for the CEO, within the word limit, and actionable with light edits.

GPT-6.1 Sol · API

The memo is complete, within word limit, and directly usable by the CEO and board with a clear recommendation and plan.

Rebuilds the market sizeRightRightRight
Haiku 5.5 · API

Uses employer counts and retention data to show relevant market is ~1.1M firms, 1% worth ~$7M ARR, not $50M, with working.

Sonnet 5.5 · API

It rebuilds the market using employer counts and UK retention data, arriving at ~$1B for the 1.1M 10-249 employee businesses, showing the working.

GPT-6.1 Sol · API

It rebuilds the market using employer counts and UK retention, arriving at 1.1M businesses and $682M-$2.64B, showing the working.

Finds the timeline that sinks itRightRightRight
Haiku 5.5 · API

Names the 9-month build and explains that Q1 launch is infeasible without state coverage.

Sonnet 5.5 · API

It names the 9-month state tax build and explains that a Q1 launch is impossible and the $5M year-one target unreachable.

GPT-6.1 Sol · API

It names the 9-month build and states it contradicts Q1 readiness, directly linking it to the year-one target.

Tigers, not paper tigersRightRightRight
Haiku 5.5 · API

Ranks risks, dismisses competitor raise as less scary, and surfaces TAM churn error as the hidden sink.

Sonnet 5.5 · API

It ranks risks, dismisses the competitor-raise worry as less scary because funding doesn't speed the state build, and surfaces the ARR discrepancy as an unspoken issue.

GPT-6.1 Sol · API

It ranks compliance failure as existential, dismisses the competitor fear as less scary, and surfaces the unspoken need for product readiness.

Finds the need behind the ideaRightRightRight
Haiku 5.5 · API

States the opportunity is real and offers staged validation as an alternative, displacing the full Q1 $2.5M launch.

Sonnet 5.5 · API

It identifies the need for US growth and offers a phased alternative with lower cost and risk, stating what it displaces (the aggressive Q1 launch and $5M target).

GPT-6.1 Sol · API

It identifies the need for a viable US entry, proposes a staged validation alternative, and states what it displaces (the $5M ARR target, Q1 launch, sales team) and its cost ($300k).

Results

Every setup we’ve tested on this task type, across all its tasks and repeats, graded on the current checklist. Calibrated. Where our PM checked the graders by hand, they agreed on 76% of 75 checks.

#Model · HarnessTask scoreDecision modelLLM judgeRunsCritical failures
1GPT-6 LunawithAPI100.090.92None
2Haiku 5.5withAPI92.590.92None
3GPT-6.1 SolwithAPI100.086.42None
4GPT-6 AstrawithChatGPT100.079.42None
5Sonnet 5.5withAPI88.374.82None
6Opus 5.5withClaude88.379.421 capped
7Gemini 3.5 Flash-LitewithGemini79.649.721 capped
8Gemini 3.8 FlashwithAPI87.972.721 capped

What you get for the cost

No setup scores within 5 points of the leader at half its cost or less here, so the leader is also the best value.

Task score against relative cost for each setup. The table below has the same figures.4050607080901001×3×10×30×Cost per output, relative to the cheapest setup (log scale) →↑ Task scoreGPT-6 Luna · API: task score 93, the cheapestHaiku 5.5 · API: task score 92, the cheapestGPT-6.1 Sol · API: task score 91, 11× the cheapestGPT-6 Astra · ChatGPT: task score 88, 60× the cheapest (1 of 2 outputs estimated)Sonnet 5.5 · API: task score 78, 37× the cheapestOpus 5.5 · Claude: task score 62, 59× the cheapest (1 of 2 outputs estimated), 1 critical failureGemini 3.5 Flash-Lite · Gemini: task score 50, 1.9× the cheapest (1 of 2 outputs estimated), 1 critical failureGemini 3.8 Flash · API: task score 50, 9.5× the cheapest, 1 critical failureGPT-6 Luna · APIHaiku 5.5 · APIGPT-6.1 Sol · APIGPT-6 Astra · ChatGPTSonnet 5.5 · APIOpus 5.5 · ClaudeGemini 3.5 Flash-Lite · GeminiGemini 3.8 Flash · API
Cost partly estimated (app runs with no usage meter)At least one critical failure
Task score and relative cost by setup
SetupTask scoreRelative cost (cheapest = 1)
GPT-6 Luna · API931.0×
Haiku 5.5 · API921.4×
Gemini 3.5 Flash-Lite · Gemini501.9× (partly estimated)
Gemini 3.8 Flash · API509.5×
GPT-6.1 Sol · API9111×
Sonnet 5.5 · API7837×
Opus 5.5 · Claude6259× (partly estimated)
GPT-6 Astra · ChatGPT8860× (partly estimated)

Cost is each output’s tokens at the model’s list price, shown relative to the cheapest setup. Runs done in an app have no usage meter, so theirs are estimated from the same setup’s measured runs. How we compare cost

About the task

The PM job

Pressure-testing a proposal before committing a team to it.

Why it matters

The useful critic finds the one assumption everything rests on. Theatrical negativity is easy to generate and useless in a planning meeting.

What good looks like

  • Identifies the load-bearing assumption
  • Separates the risks that could kill it from the ones that only look scary
  • Uses the supplied evidence, not generic risks
  • Proposes the cheapest way to test the assumption

Deliberately not measured

  • Tone
  • Number of objections raised
Capability tested

Evidence-based critique

The failure we’re looking for

Theatrical negativity without evidence

Grading

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

Variants

Vanilla prompt (core) · With Roast Me skill · Staff level: a company bet with a long evidence pack