Tasks / Strategy

Develop product strategy

Can the model make a coherent choice grounded in the evidence, rather than list aspirations?

Task type v1.1 · 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. 38% were usable with at most a quick edit.

Reliably right

  1. Produces the required deliverable100% pass
    Complete strategy document in the requested form, length, and for the named reader; the board could act on it.
    GPT-6 Astra · ChatGPT · Supply or demand for a stalled marketplace
  2. Diagnosis before prescription100% pass
    Diagnosis: students can't find the right tutor; actions (intake, recommendations, rematch, manual matching) directly address it.
    GPT-6 Astra · ChatGPT · Supply or demand for a stalled marketplace
  3. Tells the CEO plainly100% pass
    It clearly states the enterprise-first plan is wrong for next year, backs it with numbers, and presents the alternative.
    GPT-6 Astra · ChatGPT · Enterprise, says the CEO

Where it slips

  1. Names an advantage that's hard to copy11% pass
    Does not name a benefit and a barrier that a well-funded competitor couldn't copy; no moat is identified.
    GPT-6 Astra · ChatGPT · Supply or demand for a stalled marketplace
  2. Proposes tests that could fail42% pass
    The SMB pilot lacks a numeric threshold for success; while the payback guardrail has a threshold and action, not every proposed test/gate meets the full requirement.
    GPT-6 Astra · ChatGPT · Enterprise, says the CEO
  3. Avoids unsupported claims44% pass
    Presents 'root cause: we've let the loudest requests set the roadmap' and 'SMB remains our top-of-funnel' as facts without labelling them as hypotheses or citing evidence.
    Haiku 5.5 · API · Enterprise, says the CEO

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. Diagnosis before prescription

    Does the strategy name the crux, the specific obstacle or opportunity the evidence points to, and do the proposed actions follow from that diagnosis?

    Passes when States one crux grounded in the supplied evidence, and each major action visibly addresses it.

  2. Names an advantage that's hard to copy

    Does the strategy say what will make its position hard for an informed, well-funded competitor to copy (a benefit customers value plus a barrier to copying it), rather than relying on being first, on features, or on funding?

    Passes when Names the benefit and the barrier, and why a capable competitor couldn't simply replicate it.

  3. Says what it gives up

    Does the strategy name what the company will stop doing, or deliberately not do, in order to pursue it?

    Passes when Names at least one real thing being dropped or declined, with the reason it loses out.

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 · Proposes tests that could fail · 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 Cadence. Our CEO wants a strategy for next year the exec team can rally behind, and believes it's enterprise (the note is below). Write the strategy memo, in no more than 1,200 words: the diagnosis, the guiding policy (where we play and what we stop), the coherent actions for next year, and how we'll know it's working. Tell the CEO if you think they're wrong. The files are attached.

What the model was given6 items: About Cadence, ceo_note.md, unit_economics_by_segment.csv, enterprise_detail.md, mid_market_detail.md, smb_detail.md
About CadenceStaff scheduling and time tracking, sold to businesses with hourly workers.
ceo_note.md1 lines · Download
From the CEO: "I want a strategy for next year that the exec team can rally behind. I believe it's enterprise. Tell me if I'm wrong."
unit_economics_by_segment.csv3 rows · Download
segment,customers,avg_arr_usd,gross_margin_pct,support_cost_per_customer_year_usd,cac_usd,payback_months,net_revenue_retention_pct,logo_churn_year_pct
SMB self-serve,6200,1100,78,610,740,31,88,34
Mid-market,890,14500,81,1900,9800,9,118,7
Enterprise,34,96000,64,21000,118000,26,104,9
enterprise_detail.md4 lines · Download
# Enterprise detail

- Average sales cycle: 9 months. 5 of the last 8 deals needed custom features (built by the core team, about 14 engineer-weeks each).
- The CEO's plan: "Win enterprise. Hire 10 enterprise AEs and a solutions team, and build SSO, audit logs and custom workflows this year."
mid_market_detail.md5 lines · Download
# Mid-market detail

- Best-retaining segment. Expansion comes from adding locations and seats.
- Top requests: multi-location reporting, payroll integrations, shift templates.
- Win rate against our main competitor: 61%.
smb_detail.md4 lines · Download
# SMB self-serve detail

- 62% of support tickets come from SMB accounts. Free trial converts at 4%.
- Most SMB customers are on the $79/month plan with unlimited phone support.
What a strong answer doesThe answer key the graders mark against

Diagnoses from the unit economics: mid-market is the engine (payback 9 months, NRR 118%, churn 7%, wins 61% against the main competitor); SMB self-serve loses money once support and churn are counted (about $1,100 a year at 78% gross margin is about $860, minus $610 of support, leaves about $250 a year against $740 to acquire, with 34% leaving each year; payback 31 months, NRR 88%) and generates 62% of tickets; enterprise is slow and expensive (payback 26 months, 64% gross margin, 9-month cycles, 5 of 8 deals needing about 14 engineer-weeks of custom work). Tells the CEO the enterprise bet is wrong for next year: it would pull the core team into custom work and stretch payback. Policy: win mid-market, expanding on locations and seats; stop subsidising SMB support (change the plan or pricing, self-serve support, raise the entry price) rather than abandon it; serve enterprise only where it buys the product as is. Coherent actions: mid-market roadmap (multi-location reporting, payroll integrations, shift templates), SMB support and pricing changes, no custom enterprise work. Names what it gives up and how it'll know (mid-market NRR and payback, SMB support cost per customer).

Critical failures (cap the score at 40)
  • Recommends hiring the enterprise team and building custom workflows as next year's main strategy
Task

Staff-level · v1.0

The outputs

8 setups answered this brief.

Needs more than a quick edit10 of 12 checks passed

The memo lacks a competitive moat and specific test thresholds with trigger actions; adding these would require more than a quick edit without reworking the reasoning.

Output

To: CEO and Executive Team From: VP Product Subject: Next year’s strategy: win the mid-market, fix the cost to serve

Diagnosis

I think you’re wrong that enterprise should be our primary strategy next year. Enterprise can be a selective opportunity, but the evidence does not support building the company around it.

Mid-market is our strongest growth engine: it has the best retention (118% net revenue retention, 7% logo churn), a 61% win rate against our main competitor, and clear expansion paths through more locations and seats. Its requested improvements—multi-location reporting, payroll integrations and shift templates—reinforce the core scheduling product rather than pull us into one-off work. At $14,500 average ARR, it represents roughly $12.9 million of ARR across 890 customers.

Enterprise has only 34 customers and about $3.3 million of ARR. Its economics and delivery model are less attractive: 64% gross margin, $21,000 annual support cost per customer, 26-month reported CAC payback, and a nine-month sales cycle. Five of the last eight deals required custom features, consuming about 70 engineer-weeks in total. Hiring 10 AEs and building custom workflows would scale a motion we have not shown is repeatable. SSO and audit logs may be worthwhile if they serve a broader, standard product—not as the opening move in a bespoke enterprise program.

SMB is also not where we should prioritize growth investment. It has 6,200 customers, but 34% annual logo churn, 88% NRR, and 62% of support tickets. Unlimited phone support on the $79 plan appears poorly matched to the segment’s economics.

One caution: the reported payback figures do not reconcile consistently with ARR, gross margin and support cost. We should standardize their definition before using them to allocate capital.

Guiding policy

Play to win multi-location mid-market employers with hourly workforces. Make Cadence the easiest dependable way to schedule and track time across locations, with strong payroll connections and repeatable workflows.

Stop treating enterprise as the company’s growth thesis. Do not hire 10 enterprise AEs or build customer-specific workflows with the core team. Pursue enterprise deals only when they fit the standard product, support attractive economics and do not displace mid-market priorities.

Stop subsidizing SMB support through unlimited phone service on the entry plan. Keep serving SMB customers, but shift the offer toward scalable self-service and appropriately priced support—not a broad retreat from the segment.

Coherent actions for next year

  1. Make the mid-market roadmap the top product priority. Deliver multi-location reporting, payroll integrations and shift templates in that order, validating scope with customers and tying releases to adoption and expansion. Build configurable, reusable capabilities; decline requests that create customer-specific branches.
  1. Focus go-to-market on repeatable mid-market wins. Equip sales and onboarding around multi-location use cases, implementation playbooks and expansion from existing locations and seats. Invest in customer success where it can turn adoption into expansion and reduce avoidable churn.
  1. Set an enterprise investment gate. Pause the proposed 10-AE hiring plan. Evaluate SSO and audit logs as reusable platform capabilities, but fund them only with evidence of demand beyond individual deals. Require enterprise opportunities to fit the standard product; price implementation and customization explicitly, and do not commit core engineering to bespoke workflows. Revisit enterprise hiring only when deals are repeatable and payback is demonstrably attractive.
  1. Repair SMB service economics without breaking the customer experience. Move entry-plan support toward self-service, improve onboarding and help content, and test paid higher-touch support. Measure the effect on conversion and retention before making a broad pricing or support change.
  1. Create one trusted segment-economics view. Reconcile CAC payback and consistently include gross margin, support, implementation and custom engineering costs. Review it quarterly before adding segment-specific capacity.

How we’ll know it’s working

  • Mid-market: NRR rises from 118% to at least 120%; logo churn falls from 7% to 6% or less; win rate stays at or above 60%. Track ARR expansion from added locations and seats, plus adoption of the three roadmap investments.
  • Enterprise: No broad AE expansion; custom core-engineering work falls sharply, with a target of no more than two engineer-weeks per won deal. Track fully loaded payback and sales-cycle length before increasing investment.
  • SMB: Reduce support tickets per customer and support cost per customer; improve trial conversion from 4% without worsening churn. Make any support-tier changes conditional on those customer outcomes.
  • Company-wide: Review segment ARR, gross profit after support and implementation, and fully loaded CAC payback together. Growth that depends on unrepeatable engineering or uneconomic service is not success.

This strategy does not abandon enterprise or SMB. It puts our next year’s scarce product and hiring capacity behind the segment with the clearest evidence of repeatable growth, while setting firm conditions for investing more elsewhere.

Grades and run details

Decision model 79 · LLM judge 77
Decision model checks
  • passUses the supplied evidence correctly52%
  • passAddresses the actual decision98%
  • passRespects explicit constraints64%
  • passIdentifies material uncertainty70%
  • partialAvoids unsupported claims30%
  • passProduces the required deliverable87%
  • partialReads the segment economics56%
  • passTells the CEO plainly100%
  • passDiagnosis before prescription100%
  • partialProposes tests that could fail77%
  • failNames an advantage that's hard to copy47%
  • passSays what it gives up100%
Run
Run
#1
API response time
29 s
Submitted
6 Oct 2026

Needs more than a quick edit8 of 12 checks passed

The memo contains an unsupported factual claim about market expectations, requiring evidence re-check, and lacks a clear competitive moat, so a PM would need to redo some reasoning.

Output

Memo: Next Year's Strategy

To: CEO From: VP Product Re: Where we play next year, and why I don't think it's enterprise

You asked me to tell you if you're wrong. I think you are, at least for next year. Enterprise isn't a bad market. But our numbers say our winning position is somewhere else, and an enterprise push would starve that position of the engineering time and sales capacity it needs. Below is the case and what I propose instead.

---

1. Diagnosis

Cadence runs three different businesses, and only one of them is working well.

SegmentARRAnnual gross profit after support, per customerCACPaybackNRRLogo churn
SMB self-serve$6.8M$248$74031 mo88%34%
Mid-market$12.9M$9,845$9,8009 mo118%7%
Enterprise$3.3M$40,440$118,00026 mo104%9%

(Gross profit after support = ARR × gross margin − support cost. Total ARR is about $23M.)

Mid-market is the business. - It is 56% of ARR. - It pays back CAC in 9 months. - It grows on its own: 118% NRR on $12.9M means about $2.3M of net new ARR next year before we sign a single new logo. - We win 61% of the time against our main competitor. - Expansion comes naturally as customers add locations and seats.

Enterprise looks big per logo but is weak as a business today. - Gross margin is 64%, versus 81% in mid-market. - Each customer costs $21K a year to support. - CAC is $118K, payback takes 26 months, and the sales cycle is 9 months. - The hidden cost is engineering. 5 of the last 8 deals needed custom features, at about 14 engineer-weeks each, built by the core team. That is roughly 70 engineer-weeks diverted from the product that 890 mid-market customers pay for.

SMB is roughly break-even and pulling capacity away from everything else. - Each customer generates $248 a year after support. - With 34% annual churn, the average customer lives about 3 years. Lifetime contribution is roughly $730, against $740 of CAC. - SMB produces 62% of our support tickets. The cause is structural: we offer unlimited phone support on a $79/month plan, so support costs ($610) eat more than half of revenue ($1,100). - Trial conversion is 4%.

The core problem: we are trying to be everything to everyone. The cost shows up in two places. The roadmap gets hijacked by single enterprise deals, and the support budget gets consumed by SMB.

Why the enterprise plan makes this worse. Assume 10 new AEs close 20 enterprise logos next year, which is optimistic given a 9-month cycle and ramp time. - That adds about $1.9M of ARR. - It costs about $2.4M in CAC. - If 5 of every 8 deals still need custom work, it consumes about 175 engineer-weeks, or 3–4 engineer-years, on custom features alone. - That is before the work on SSO, audit logs, and custom workflows. - Most of that ARR would land late in the year and pay back in year three.

Meanwhile, the mid-market roadmap would stall in the segment where we already win.

---

2. Guiding Policy

Where we play: We will be the best scheduling and time-tracking platform for multi-location operators with hourly workforces, from roughly 10 to a few hundred locations. Mid-market is the core. Every product, sales, and support decision should first answer one question: does this help a mid-market customer win, stay, or add locations?

What we stop: 1. Custom feature builds for single deals. If a feature isn't on the roadmap for a segment, we don't build it to close one logo. 2. The 10-AE enterprise hiring plan. We redeploy that budget (see below). 3. Unlimited phone support on the $79 plan. That plan moves to in-app help, chat, and a knowledge base. Phone support becomes a paid tier. 4. Custom workflows as a product initiative. This is a services business disguised as a feature.

What we deliberately keep: - Our 34 enterprise customers, served well on the standard product. - Inbound enterprise deals that can close without custom work. - SSO and audit logs. Upper mid-market buyers increasingly expect these, so they serve the core rather than a new segment.

---

3. Coherent Actions for Next Year

These actions reinforce each other. Product makes mid-market expansion easier. Go-to-market (GTM) captures that expansion. Fixing SMB frees money and support capacity to fund both.

Product (mid-market roadmap, Q1–Q3) - Multi-location reporting. This is the top request, and it directly drives location expansion, our main source of NRR. - Payroll integrations. We will prioritize the top 3–4 providers by customer count. Integrations increase switching costs and reduce churn. - Shift templates. This reduces setup time for each new location, so expansion becomes cheap for the customer and for us. - SSO and audit logs. These are table stakes for larger mid-market accounts. We will scope them tightly and avoid gold-plating. - Engineering capacity rule: zero engineer-weeks go to one-off custom builds.

Go-to-market - Redirect the enterprise AE budget. Fund roughly 4–5 mid-market AEs and 3–4 account managers whose job is location and seat expansion inside existing accounts. A 9-month payback and 118% NRR make this the most efficient growth dollar we have. - Build a competitive playbook. Codify why we win 61% against our main competitor, and target that competitor's mid-market base. - Handle enterprise inbound on the standard product. One senior AE and the existing team qualify enterprise leads. A deal requiring custom work is a no unless the feature is already on the roadmap.

SMB economics - Restructure support. Move the $79 plan to digital-first support and introduce a higher tier that includes phone support. The target is cutting SMB support cost per customer from $610 to under $350. - Overhaul onboarding and trials. A 4% conversion rate signals weak activation. Fixing onboarding should also reduce tickets. - Find out whether SMB feeds mid-market. We need to learn how many mid-market customers started on SMB. If SMB is a real feeder, we keep it as a low-cost funnel. If not, we run it purely for margin.

Enterprise - Improve margins on the existing base. Standardize their configurations and reduce bespoke support. - Track demand without chasing it. We log every enterprise request, so that if we return to enterprise later, we can build a standard product rather than custom one-offs.

---

4. How We'll Know It's Working

Leading indicators (quarterly) - Multi-location reporting and payroll integrations shipped by end of Q2. - Engineer-weeks spent on custom deal work: 0. - SMB support tickets per customer down 30% by Q3. - Mid-market win rate against our main competitor: 61% → 65%.

Outcomes (year-end) - Mid-market NRR ≥ 120%, up from 118%. - Mid-market new-logo ARR grows at least 25%, with payback held at ≤ 12 months. - SMB support cost per customer under $350, and SMB contribution per customer roughly doubled. - Enterprise gross margin above 70%, up from 64%, with no logo churn among the top 10.

When we would revisit enterprise: I'm not saying never. I'd reopen the question in Q3 if either of these happens: - Mid-market customers are outgrowing us into enterprise-scale deployments, meaning enterprise becomes the natural next step for our core. - We close at least 3 enterprise deals on the standard product.

Either signal would mean enterprise has become an extension of our strength rather than a separate bet. At that point, a focused enterprise motion built on a product we actually have would make sense.

---

Bottom line: The exec team can rally behind this: win multi-location mid-market, stop subsidizing segments that don't pay. It builds on where we already win, funds itself by fixing SMB economics, and keeps enterprise open as a future option rather than a costly bet. I'd welcome the chance to pressure-test this with you before the offsite.

Claims the judge couldn’t find in the brief

  • Upper mid-market buyers increasingly expect SSO and audit logs.
  • Integrations increase switching costs and reduce churn.

Grades and run details

Decision model 88 · LLM judge 62
Decision model checks
  • passUses the supplied evidence correctly25%
  • passAddresses the actual decision100%
  • passRespects explicit constraints49%
  • passIdentifies material uncertainty98%
  • partialAvoids unsupported claims51%
  • passProduces the required deliverable83%
  • passReads the segment economics90%
  • passTells the CEO plainly100%
  • passDiagnosis before prescription100%
  • partialProposes tests that could fail72%
  • partialNames an advantage that's hard to copy78%
  • passSays what it gives up100%
Run
Run
#1
Time to output
44 s
Submitted
5 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 correctlyRightMixed
GPT-6 Luna · API

All factual claims about the current situation are taken directly from the supplied context or follow by arithmetic.

Opus 5.5 · Claude

The memo claims that 'Upper mid-market buyers increasingly expect these' (SSO and audit logs) without support from the supplied context, inventing a fact about the current market.

Avoids unsupported claimsRightWrong
GPT-6 Luna · API

Uses cautious language ("I think", "appears") for interpretations and does not present forecasts as established fact.

Opus 5.5 · Claude

Presents 'Upper mid-market buyers increasingly expect these' as fact without evidence, and 'Integrations increase switching costs' as an established cause, neither supported by the supplied context.

All got wrong 2

Proposes tests that could failWrongWrong
GPT-6 Luna · API

The 'How we'll know' section lacks specific numeric thresholds for SMB and enterprise tests, does not define measurement windows, and does not state what actions would follow if targets are missed.

Opus 5.5 · Claude

The leading indicators (e.g., SMB tickets down 30%, mid-market NRR ≥120%) lack stated actions for when they are not met; only the enterprise revisit gates have triggers and actions.

Names an advantage that's hard to copyWrongWrong
GPT-6 Luna · API

The memo describes benefits (easiest way to schedule, payroll connections) but does not name a barrier that would prevent a capable competitor from copying the position.

Opus 5.5 · Claude

Does not name a specific advantage that is hard for a well-funded competitor to copy, nor explain why they couldn't simply replicate the mid-market focus.

All got right 8

Addresses the actual decisionRightRight
GPT-6 Luna · API

Commits early to rejecting enterprise as the primary strategy, proposes mid-market focus, and states conditions for revisiting enterprise.

Opus 5.5 · Claude

Commits early to disagreeing with the CEO's enterprise bet, proposes an alternative, and specifies conditions (mid-market outgrowing, 3 standard enterprise deals) that would reopen the question.

Respects explicit constraintsRightRight
GPT-6 Luna · API

The memo addresses all requested sections, stays under 1,200 words, and directly tells the CEO they are wrong.

Opus 5.5 · Claude

The memo is under 1200 words, addresses the CEO, includes diagnosis, guiding policy, actions, and how we'll know, and tells the CEO they are wrong.

Identifies material uncertaintyRightRight
GPT-6 Luna · API

Identifies the inconsistent payback figures as an uncertainty that could affect capital allocation, and notes the need to standardize definitions; sets repeatability and payback as conditions to revisit enterprise.

Opus 5.5 · Claude

Identifies the unknown of whether SMB feeds mid-market and proposes to learn it; bounds enterprise uncertainty with specific revisit triggers.

Produces the required deliverableRightRight
GPT-6 Luna · API

Complete strategy memo with diagnosis, policy, actions, and metrics, well under the word limit and usable by the CEO and exec team.

Opus 5.5 · Claude

Delivers a complete strategy memo in the requested form, with all required sections, and is actionable for the CEO.

Reads the segment economicsRightRight
GPT-6 Luna · API

Works through retention, support cost, and payback for all three segments, concludes mid-market is the strongest, enterprise is slow and costly, and implies SMB is uneconomic by calling for an end to subsidizing its support.

Opus 5.5 · Claude

Works through payback, retention, and support cost for all three segments, correctly concluding mid-market is strongest, SMB loses money, and enterprise is slow and costly.

Tells the CEO plainlyRightRight
GPT-6 Luna · API

States directly that the CEO is wrong about enterprise as the primary strategy, backed by segment numbers.

Opus 5.5 · Claude

Clearly and respectfully tells the CEO they are wrong for next year, with evidence from the numbers.

Diagnosis before prescriptionRightRight
GPT-6 Luna · API

Diagnosis identifies mid-market as the engine and enterprise/SMB issues; each major action visibly addresses those findings.

Opus 5.5 · Claude

States the core problem (trying to be everything to everyone) grounded in the data, and each major action addresses that problem.

Says what it gives upRightRight
GPT-6 Luna · API

Explicitly stops enterprise AE hiring, custom engineering work, and unlimited phone support for SMB, with reasons.

Opus 5.5 · Claude

Explicitly lists what the company will stop: custom feature builds, enterprise AE hiring, unlimited phone support, custom workflows, with reasons.

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 84% of 76 checks.

#Model · HarnessTask scoreDecision modelLLM judgeRunsCritical failures
1GPT-6 AstrawithChatGPT83.388.52None
2Haiku 5.5withAPI77.180.82None
3Sonnet 5.5withAPI77.180.82None
4GPT-6.1 SolwithAPI79.276.92None
5GPT-6 LunawithAPI77.176.92None
6Opus 5.5withClaude83.365.42None
7Gemini 3.8 FlashwithAPI68.857.72None
8Gemini 3.5 Flash-LitewithGemini60.442.32None

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.4050607080901001×3×10×30×100×Cost per output, relative to the cheapest setup (log scale) →↑ Task scoreGPT-6 Astra · ChatGPT: task score 87, 84× the cheapest (1 of 2 outputs estimated)Haiku 5.5 · API: task score 80, 1.7× the cheapestSonnet 5.5 · API: task score 78, 27× the cheapestGPT-6.1 Sol · API: task score 77, 12× the cheapestGPT-6 Luna · API: task score 74, the cheapestOpus 5.5 · Claude: task score 71, 68× the cheapest (1 of 2 outputs estimated)Gemini 3.8 Flash · API: task score 61, 8.1× the cheapestGemini 3.5 Flash-Lite · Gemini: task score 49, 3.1× the cheapest (1 of 2 outputs estimated)GPT-6 Astra · ChatGPTHaiku 5.5 · APISonnet 5.5 · APIGPT-6.1 Sol · APIGPT-6 Luna · APIOpus 5.5 · ClaudeGemini 3.8 Flash · APIGemini 3.5 Flash-Lite · Gemini
Nobody beats these on both score and costCost partly estimated (app runs with no usage meter)
Task score and relative cost by setup
SetupTask scoreRelative cost (cheapest = 1)
GPT-6 Luna · API741.0×
Haiku 5.5 · API801.7×
Gemini 3.5 Flash-Lite · Gemini493.1× (partly estimated)
Gemini 3.8 Flash · API618.1×
GPT-6.1 Sol · API7712×
Sonnet 5.5 · API7827×
Opus 5.5 · Claude7168× (partly estimated)
GPT-6 Astra · ChatGPT8784× (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

Writing a strategy memo that leadership can act on.

Why it matters

Strategy that doesn't choose isn't strategy. Models write fluent strategic prose easily; making a choice the evidence supports and naming what it gives up is harder.

What good looks like

  • Diagnoses the one obstacle that matters before prescribing
  • Makes one clear choice and names what is sacrificed
  • Grounds the choice in the supplied evidence
  • Surfaces the tension or contradiction in the data
  • Defines how we would know it is working

Deliberately not measured

  • Market sizing accuracy beyond the supplied data
  • Financial modelling
Capability tested

Choosing where to play and what not to do, from supplied evidence

The failure we’re looking for

Strategic-sounding aspirations without a diagnosis or a choice

Grading

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