Tasks / Strategy

1000x an idea

Can the model expand an idea's ambition while keeping it tethered to a real mechanism?

Task type v1.0 · 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. 56% were usable with at most a quick edit.

Reliably right

  1. Extreme, then back to buildable100% pass
    Pushes from two-person sharing to the extreme household as the unit (any number of members, live pantry state, learning routines, delivery integration), then works back to the scoped two-person build that tests coordination.
    Haiku 5.5 · API · Sharing a shopping list, 1000x
  2. Finds the mechanism in the data100% pass
    Uses the retention, conversion, session frequency, notification triggers, note usage, and invitation context to identify shared money decisions as the core mechanism, not just budgeting.
    GPT-6.1 Sol · API · Budgets for two
  3. Finds the mechanism in the data97% pass
    Names household coordination as the core value (multiple members, claiming items, no duplicate buying), backs it with the 71%/22% retention gap, 38% second-device items, and duplicate tickets, and keeps coordination at the center of both the big vision and the first step.
    Haiku 5.5 · API · Sharing a shopping list, 1000x

Where it slips

  1. Proposes tests that could fail41% pass
    The proposed test does not name a numeric threshold for the primary outcome; it only says to set minimum detectable effects and thresholds before launch, which is a process, not a specific threshold.
    GPT-6.1 Sol · API · Budgets for two
  2. The big version gets stronger as it grows61% pass
    The memo names a demand network as a compounding mechanism but does not propose a test of whether that network effect would be large enough to matter, nor does it ask that question.
    GPT-6 Astra · ChatGPT · Sharing a shopping list, 1000x
  3. Avoids unsupported claims66% pass
    The statements about most financial decisions being made by more than one person and happening in texts/arguments/spreadsheets are presented as established fact without support from the supplied evidence.
    Sonnet 5.5 · API · Budgets for two

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. The big version gets stronger as it grows

    Does the ambitious version name a mechanism that makes it more valuable or harder to copy as it grows (each new user adding value for others, or a barrier a competitor couldn't buy), and ask whether that effect would be large enough to matter?

    Passes when Names the mechanism, how it compounds with scale, and a test of whether the effect is big enough to matter.

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 · Extreme, then back to buildable · Proposes tests that could fail · and 1 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 a PM at Pocketbook. Ana has proposed shared budgets for couples; before we commit next quarter, our CEO wants the 1000x version (her note is below). Write the memo, in no more than 900 words: the most ambitious version of the idea, the mechanism that makes it work, and then what we build first and how we'll know it's working. The data is attached.

What the model was given5 items: About Pocketbook, ana_idea.md, ceo_note.md, usage_by_user_group.csv, what_shared_budgets_do.md
About PocketbookA personal budgeting app: connect your accounts, set budgets, track spending. Free, with Premium at $6 a month.
ana_idea.md3 lines · Download
# The idea (from Ana, PM)

"Let people share a budget with their partner. It's our most requested feature after bank sync for more banks."
ceo_note.md1 lines · Download
From Ruth (CEO): "Before we commit next quarter to Ana's idea, show me the 1000x version. How big could this get? Then bring it back to what we build first and how we'll know it's working. Keep it under 900 words."
usage_by_user_group.csv3 rows · Download
user_group,users,retained_at_6_months_pct,invited_someone_pct,invitee_joined_pct,premium_conversion_pct
Solo budgeters,182000,17,3,22,4
Couples sharing one budget,24600,58,100,100,19
Households (3+ people on one budget),3900,71,100,100,31
what_shared_budgets_do.md6 lines · Download
# What shared budgets do (from the data team)

- Couples who share a budget open the app on more days than solo users (11 a month against 4) and most sessions start from a notification about the other person's spending ("Alex spent $48 at the grocery store").
- 41% of couples add a "money talk" note to a transaction in their first month; the note feature was built as an afterthought.
- 16% of couples add a third person within a year (a teenager, a parent they support).
- Shared budgets started from an invite link in a shared-expenses moment (rent, a holiday) retain best.
What a strong answer doesThe answer key the graders mark against

Finds the mechanism in the data: shared money decisions, not budgeting. Couples sharing a budget retain at 58% against 17% for solo budgeters, convert to Premium at 19% against 4%, open the app on 11 days a month against 4 (mostly from notifications about the other person's spending), and use transaction notes as 'money talk'; households of 3+ retain at 71% and convert at 31%. Every shared budget brings in at least one new user by design, and 16% of couples add a third person. So the 1000x version is the place a household runs its money together (shared goals, who pays for what, conversations on transactions, extended family), growing through invitations at shared-expense moments (rent, holidays). Asks whether the effect is large enough to matter: each new member makes the budget more useful to the others, so it compounds. Works back to a first step that keeps the mechanism: shared budgets launched from an invite at a shared-expense moment, with spending notifications and transaction notes built in, measured on invites accepted, retention of invited users, and Premium conversion for couples, with thresholds.

Task

Staff-level · v1.0

The outputs

8 setups answered this brief.

Usable with a quick edit8 of 10 checks passed

The memo is well-structured, data-driven, and actionable. A quick edit to label the willpower claim as a hypothesis would resolve the only unsupported statement.

Output

Memo: Shared budgets, the 1000x version

To: Ruth | From: Product | Re: Ana's shared-budgets proposal

The short version

The big opportunity isn't a "share a budget" setting. It's turning Pocketbook from a tool one person uses alone into the place a household runs its money and talks about it. Our current users already show this. People who share a budget are 14% of our users. They account for about 36% of users still with us at six months and about 45% of Premium subscribers.

GroupUsersRetained at 6 moPremium
Solo182,00017% (~30,900)4% (~7,300)
Couples24,60058% (~14,300)19% (~4,700)
Households (3+)3,90071% (~2,800)31% (~1,200)

The 1000x version

Every household's money runs through Pocketbook: couples first, then the teenager, the parent you support, the roommates, the trip group. Each group recruits its next member at the moment money is shared. We stop selling budgeting discipline to individuals and become the shared ledger and conversation for the people you split life with. The business model becomes a household plan, not a per-person subscription.

The growth engine is the key difference. Solo budgeting apps grow one user at a time through marketing. A household product grows through its members. Each shared rent payment, holiday or new dependent is a chance to recruit someone.

The mechanism: three loops

1. The other person is the reason to open the app. Couples open Pocketbook 11 days a month, against 4 for solo users. Most of those sessions start from a notification about the partner's spending ("Alex spent $48 at the grocery store"). Solo budgeting runs on willpower, which fades. Shared budgeting runs on another person, who keeps giving you reasons to open the app.

2. The product is the money conversation. 41% of couples add a "money talk" note to a transaction in their first month. They do this even though notes were an afterthought. Couples are using us to talk about money, not just to track it. Talk is the habit that holds a household together.

3. Groups grow, and they start at shared-expense moments. 16% of couples add a third person within a year, and households retain best of all (71%). Shared budgets that start from an invite link during rent or a holiday retain best.

Today the growth loop barely works. 3% of solo users invite someone, and 22% of those invitees join. That's under 1 new member per 100 solo users. This is the biggest lever we have.

What could make this wrong

The numbers above are not proof that sharing causes retention. Couples who found today's sharing are self-selected: committed, organised, probably already engaged. The 100% invite and join rates for shared groups are true by definition, not a result.

The real question is whether a solo user nudged into sharing starts behaving like today's couples (58% retention) or stays like a solo user (17%). The plan below is built to answer that.

We also need to confirm how the 19% and 31% Premium rates are counted, per person or per budget, before designing any household pricing.

What we build first (next quarter)

Couples only. We build three things, aimed at the moments the data says matter:

  1. "Share this" on a transaction or bill. Rent, a trip, a big purchase each generate an invite link that opens straight into a shared budget. This targets the entry point that retains best, instead of a buried settings page.
  2. Partner activity notifications, on by default. Users get simple controls over what their partner sees, for example categories only or purchases over $X. Privacy is a real risk in couples' money; getting the defaults wrong will cause harm and generate support tickets.
  3. Notes upgraded to replies on transactions. This turns the afterthought into a lightweight conversation thread.

Not this quarter: - 3+ person households - Roommate or trip groups - Household pricing

These come only if the couples loop proves causal.

How we'll know it's working

We'll run a holdout: a random slice of solo users who don't see the new invite prompts. That lets us measure impact rather than selection.

Leading indicators (readable within the quarter):

MetricTodayTarget
Solo users who invite someone3%8–10%
Invitees who join22%35%+
New members per 100 solo usersunder 1about 3
Active days per month, new couples (first 30 days)—9+ (vs 11 for today's couples)
New couples adding a note in month one—35%+ (vs 41% today)

Lagging indicators (we'll have early reads; full answer after the quarter): - 3-month retention of new couples against the holdout, as an early read. 6-month retention against the holdout as the verdict. - Premium conversion of new couples against the holdout.

Decision rule: We commit to the household roadmap if both of these hold: - Couples formed through the new flows retain at least twice as well as the holdout at 3 months. - They are active more than 8 days a month.

If they look like solo users, we've learned the uplift is mostly selection. In that case shared budgets stay a solid retention feature for people who already want it, not a growth strategy. That is still worth shipping, but it's a 2x, not a 1000x.

The ask: One quarter for one squad to build the three couples features and the holdout. The household decision goes on the next planning cycle, made on real evidence.

Claims the judge couldn’t find in the brief

  • Solo budgeting runs on willpower, which fades.

Grades and run details

Decision model 90 · LLM judge 82
Decision model checks
  • passUses the supplied evidence correctly30%
  • passAddresses the actual decision94%
  • passRespects explicit constraints41%
  • passIdentifies material uncertainty100%
  • partialAvoids unsupported claims34%
  • passProduces the required deliverable88%
  • passFinds the mechanism in the data100%
  • passExtreme, then back to buildable100%
  • partialProposes tests that could fail36%
  • passThe big version gets stronger as it grows96%
Run
Run
#1
Time to output
46 s
Submitted
5 Oct 2026

Check by check

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

Got wrong 1

Avoids unsupported claimsWrong

Presents 'Solo budgeting runs on willpower, which fades' as an established fact without labelling it as a hypothesis, and the evidence does not support it.

Mixed 1

Uses the supplied evidence correctlyMixed

The claim 'Solo budgeting runs on willpower, which fades' is a statement about the current situation not found in the supplied context and not derivable from it.

Got right 8

Addresses the actual decisionRight

Commits to building couples features first with a holdout, and sets a clear decision rule for the household roadmap based on retention and activity thresholds.

Respects explicit constraintsRight

Delivers a memo to Ruth under 900 words that covers the 1000x version, mechanism, first build, and success metrics.

Identifies material uncertaintyRight

Names selection bias, definitional invite rates, and the open question of whether nudged solo users will behave like existing couples, and proposes a holdout to resolve it.

Produces the required deliverableRight

The memo is complete, correctly addressed, within the word limit, and actionable by the CEO with at most light edits.

Finds the mechanism in the dataRight

Cites the retention, conversion, and behavior differences (11 vs 4 days, notifications, notes, shared-expense invites) and names shared money decisions and conversation as the mechanism.

Extreme, then back to buildableRight

Pushes to a household money platform where every household runs its money through Pocketbook, then works back to a concrete first step of couples-only features that test the same mechanism.

Proposes tests that could failRight

Each test has numeric thresholds (e.g., 8-10% invite rate, 35%+ join, 9+ active days, 2x retention vs holdout), a measurement window (within quarter for leading, 3-6 months for lagging), and a clear action for each outcome.

The big version gets stronger as it growsRight

Names growth through members at shared-expense moments as the compounding mechanism, and tests whether the effect is large enough to matter via the holdout and decision rule.

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 88% of 118 checks.

#Model · HarnessTask scoreDecision modelLLM judgeRunsCritical failures
1Haiku 5.5withAPI85.5100.02None
2GPT-6 AstrawithChatGPT93.091.32None
3GPT-6.1 SolwithAPI90.787.12None
4GPT-6 LunawithAPI88.283.02None
5Opus 5.5withClaude92.778.42None
6Sonnet 5.5withAPI90.774.22None
7Gemini 3.8 FlashwithAPI52.539.02None
8Gemini 3.5 Flash-LitewithGemini50.534.82None

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.304050607080901001×3×10×30×Cost per output, relative to the cheapest setup (log scale) →↑ Task scoreHaiku 5.5 · API: task score 93, 2.1× the cheapestGPT-6 Astra · ChatGPT: task score 92, 74× the cheapestGPT-6.1 Sol · API: task score 89, 15× the cheapestGPT-6 Luna · API: task score 84, the cheapestOpus 5.5 · Claude: task score 84, 59× the cheapestSonnet 5.5 · API: task score 81, 31× the cheapestGemini 3.8 Flash · API: task score 43, 9.1× the cheapestGemini 3.5 Flash-Lite · Gemini: task score 40, 2.9× the cheapestHaiku 5.5 · APIGPT-6 Astra · ChatGPTGPT-6.1 Sol · APIGPT-6 Luna · APIOpus 5.5 · ClaudeSonnet 5.5 · APIGemini 3.8 Flash · APIGemini 3.5 Flash-Lite · Gemini
Nobody beats these on both score and cost
Task score and relative cost by setup
SetupTask scoreRelative cost (cheapest = 1)
GPT-6 Luna · API841.0×
Haiku 5.5 · API932.1×
Gemini 3.5 Flash-Lite · Gemini402.9×
Gemini 3.8 Flash · API439.1×
GPT-6.1 Sol · API8915×
Sonnet 5.5 · API8131×
Opus 5.5 · Claude8459×
GPT-6 Astra · ChatGPT9274×

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

Finding the bigger version of a good idea.

Why it matters

Ambition without mechanism is fan fiction. The useful version pushes to the extreme, then works back to something buildable.

What good looks like

  • Names the mechanism that scales
  • Keeps the core insight
  • Works back to a first step you could build

Deliberately not measured

    Capability tested

    Ambitious expansion

    The failure we’re looking for

    Bigger adjectives, same idea

    Grading

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