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Latest drop: Haiku 5.5 · 8 Oct
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.

    Bangaly KabaLenny’s Podcast

  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.

    Hamilton HelmerLenny’s Podcast

  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.

    Gokul RajaramLenny’s Podcast

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.

GPT-6 AstraChatGPT87Usable with a quick editSonnet 5.5API87Usable with a quick editGPT-6.1 SolAPI85Usable with a quick editHaiku 5.5API81Usable with a quick editGPT-6 LunaAPI75Needs more workOpus 5.5Claude71Needs more workGemini 3.8 FlashAPI67Needs more workGemini 3.5 Flash-LiteGemini56Needs more work
GPT-6 LunaAPI

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
GPT-6.1 SolAPI

Usable with a quick edit10 of 12 checks passed

The output is a well-reasoned, complete strategy memo with correct evidence; a product manager could use it with light edits to wording or emphasis without re-checking facts or logic.

Output

Cadence: Next-Year Strategy

To: CEO and executive team From: VP Product Decision: Make multi-location mid-market customers our growth engine—not enterprise.

1. Diagnosis: Our constraint is profitable, repeatable growth

I think the enterprise-first plan is wrong for next year. Enterprise may become attractive, but our current evidence does not justify hiring ten enterprise AEs, adding a solutions team, and committing the core product team to enterprise features simultaneously. That would scale a motion we have not yet made repeatable.

Our strongest business is already mid-market:

SegmentCurrent ARR¹Gross marginCAC paybackNRRAnnual logo churn
------:---:---:---:---:
SMB self-serve$6.8M78%31 months88%34%
Mid-market$12.9M81%9 months118%7%
Enterprise$3.3M64%26 months104%9%

¹Customers multiplied by average ARR.

Mid-market contributes approximately 56% of current ARR, has the best retention and margins, and expands through additional locations and seats. Its 61% win rate against our main competitor suggests a competitive advantage worth reinforcing.

Enterprise has larger contracts, but not better economics. Sales take nine months; five of the last eight deals required custom features, consuming approximately 70 engineer-weeks. Those deals impose an opportunity cost beyond their acquisition expense: the core team cannot simultaneously build bespoke workflows and improve the product that drives our best-performing segment. Enterprise NRR of 104% provides little evidence that expansion will compensate for that burden.

SMB is also not an efficient growth engine today. Trial conversion is 4%, annual churn is 34%, and SMB generates 62% of support tickets. Unlimited phone support on a predominantly $79/month plan is a service promise poorly matched to customer value.

We should validate how support costs enter reported gross margin and payback before constructing a fully loaded profitability model. But the segment ranking is clear enough to act.

The central problem is resource allocation: we are tempted by large contracts while underinvesting in the customers where acquisition, retention, expansion, and product fit already reinforce one another.

2. Guiding policy: Win repeatable multi-location growth

Where we play: Businesses with hourly workers operating multiple locations, within our existing mid-market segment. We will refine that profile by industry, location count, and integration needs using our strongest retained and expanding cohorts—not assume every mid-market customer is equally attractive.

How we win: Make it easier to run scheduling, time tracking, and payroll handoffs consistently across locations. Land with a repeatable implementation, then grow as customers add locations and seats.

What we stop:

  • Do not execute the proposed enterprise hiring plan. No ten-AE expansion or dedicated solutions-team buildout next year.
  • Stop allowing individual prospects to commandeer the core roadmap. Custom workflows are not a strategic product category.
  • Stop optimizing SMB for signup volume while ignoring conversion, churn, and support burden.
  • Stop promising unlimited phone support to new low-price SMB customers. Change existing commitments carefully at renewal, with notice and clear alternatives.

We will retain and serve existing enterprise customers and accept selective new opportunities that fit the standard product. Enterprise remains an option to prove—not the company’s organizing strategy.

3. Coherent actions for next year

A. Build the multi-location operating backbone

Owners: Product and Engineering

Commit at least 70% of planned product capacity to the mid-market growth loop and its enabling reliability work.

Prioritize the three requests supported by current customer evidence:

  1. Multi-location reporting: Give operators a consistent view across sites.
  2. Payroll integrations: Reduce manual handoffs and implementation friction; prioritize providers used by our target customers.
  3. Shift templates: Make repeatable scheduling easier across locations.

In Q1, confirm priority and scope through customer research, usage data, and lost-deal analysis. Ship in staged releases during Q2–Q3, then use Q4 to improve adoption and remove rollout friction. Success means customers using these capabilities—not merely features released.

SSO and audit logs enter the roadmap only where they unlock repeatable demand from our target segment or address necessary security obligations. We will not bundle them with speculative custom workflows.

B. Align selling and customer success around location expansion

Owners: Sales and Customer Success

Reallocate growth investment toward mid-market rather than enterprise headcount. Increase selling capacity in stages, conditional on cohort payback remaining healthy.

Create a standard qualification and implementation playbook. Establish an explicit location-expansion plan for suitable customers, including rollout milestones, adoption checkpoints, and commercial packaging that makes expansion straightforward.

Track why we win against our main competitor and turn that evidence into positioning, demonstrations, and onboarding. Product adoption, selling, and expansion should reinforce the same promise.

C. Repair SMB economics without abandoning customers

Owners: Growth and Support

For new customers, introduce clear support tiers, reserving phone support for appropriately priced plans. Improve onboarding and self-service around the largest ticket drivers. Test packaging and onboarding changes before broad rollout.

Do not increase SMB acquisition spending until conversion and cohort payback improve. Existing customers receive a transparent transition, not a surprise withdrawal of service.

D. Put enterprise behind an investment gate

Owners: CEO, Sales, Finance, and Product

Require executive approval for exceptions, with engineering effort and opportunity cost recorded before signing. Prefer standard-product deals; do not hide custom development inside revenue targets.

Reconsider a dedicated enterprise expansion only when successive cohorts demonstrate materially improved margins, payback approaching 12–15 months, and wins that do not depend on bespoke core-team work. A handful of large bookings is insufficient evidence.

4. How we will know it is working

Finance will establish consistent cohort definitions and quarterly reporting in Q1. Our proposed operating targets are:

  • Mid-market: NRR at least 120%; annual logo churn no worse than 7%; gross margin at least 80%; CAC payback no worse than 12 months as we scale.
  • Competitive position: Maintain at least a 60% win rate against our main competitor, using a consistent opportunity definition.
  • Product impact: Improve time to activate additional locations and adoption of reporting, integrations, and templates against Q1 baselines.
  • SMB repair: Lower tickets per customer and support cost per customer, improve trial conversion, and shorten new-cohort payback without worsening retention.
  • Execution discipline: Deliver the agreed mid-market capacity allocation and report every enterprise customization exception.

These are targets, not a revenue forecast. Finance should translate the strategy into a funded operating plan.

Bottom line: Next year should prove that Cadence can compound a repeatable advantage. Mid-market already shows that pattern. Enterprise currently does not.

Grades and run details

Decision model 83 · LLM judge 85
Decision model checks
  • passUses the supplied evidence correctly26%
  • passAddresses the actual decision100%
  • passRespects explicit constraints49%
  • passIdentifies material uncertainty48%
  • partialAvoids unsupported claims43%
  • passProduces the required deliverable72%
  • partialReads the segment economics36%
  • passTells the CEO plainly100%
  • passDiagnosis before prescription100%
  • partialProposes tests that could fail78%
  • partialNames an advantage that's hard to copy70%
  • passSays what it gives up100%
Run
Run
#1
API response time
43 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.

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.

GPT-6.1 Sol · API

The operating targets for mid-market and SMB lack explicit actions if missed; only the enterprise gate specifies what each result triggers.

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.

GPT-6.1 Sol · API

Does not name a durable advantage or barrier that would prevent a well-funded competitor from copying the multi-location focus and features.

All got right 10

Uses the supplied evidence correctlyRightRight
GPT-6 Luna · API

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

GPT-6.1 Sol · API

All facts and figures about the current situation are directly from the supplied context or correct arithmetic; nothing is invented.

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.

GPT-6.1 Sol · API

Commits early to mid-market as the growth engine, says the enterprise plan is wrong, and states conditions for reconsidering enterprise.

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.

GPT-6.1 Sol · API

Memo is within 1,200 words, includes all requested sections, and addresses the CEO directly.

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.

GPT-6.1 Sol · API

Acknowledges uncertainty in support cost accounting and sets explicit, measurable conditions for revisiting enterprise.

Avoids unsupported claimsRightRight
GPT-6 Luna · API

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

GPT-6.1 Sol · API

Interpretations are clearly framed as diagnosis or opinion, not as established facts.

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.

GPT-6.1 Sol · API

Complete strategy memo with diagnosis, policy, actions, and metrics, usable by the exec team as is.

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.

GPT-6.1 Sol · API

Works through payback, retention, and support costs for all three segments, correctly concluding mid-market is strongest, SMB is inefficient, 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.

GPT-6.1 Sol · API

Directly tells the CEO the enterprise-first plan is wrong, with supporting numbers and a clear alternative.

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.

GPT-6.1 Sol · API

Diagnosis names resource allocation as the crux, and all major actions reallocate resources toward mid-market and away from enterprise and SMB inefficiencies.

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.

GPT-6.1 Sol · API

Explicitly lists stops: enterprise hiring, custom work, SMB signup optimization, and unlimited phone support for low-price plans.

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 AstraChatGPT83.388.52None
2Haiku 5.5API77.180.82None
3Sonnet 5.5API77.180.82None
4GPT-6.1 SolAPI79.276.92None
5GPT-6 LunaAPI77.176.92None
6Opus 5.5Claude83.365.42None
7Gemini 3.8 FlashAPI68.857.72None
8Gemini 3.5 Flash-LiteGemini60.442.32None

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)

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

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