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

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
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
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

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
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
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.

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.
Hamilton HelmerLenny’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 · 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.

GPT-6.1 SolAPI93Usable with a quick edit GPT-6 AstraChatGPT93Usable with a quick edit GPT-6 LunaAPI91Usable with a quick edit Haiku 5.5API91Usable with a quick edit Sonnet 5.5API89Usable with a quick edit Opus 5.5Claude86Usable with a quick edit Gemini 3.5 Flash-LiteGemini45Needs more work Gemini 3.8 FlashAPI43Needs more work

Gemini 3.8 FlashAPI

Needs more than a quick edit4 of 10 checks passed

The memo contains unsupported factual claims and lacks explicit kill criteria and uncertainty, so a PM would need to re-check evidence and add decision triggers before using it.

Output

MEMORANDUM

TO: Ruth, CEO FROM: Product Management DATE: October 24, 2023 SUBJECT: The 1000x Vision for Shared Finances: From Single-Player Budgeting to Household Financial OS

---

1. The 1000x Vision: The Multiplayer Financial OS

Personal budgeting apps historically fail for a fundamental reason: single-player personal finance is a guilt-driven chore. Users log in alone, feel judged by their charts, and abandon the app. Our baseline data proves this: solo budgeters retain at just 17% at six months and convert to Premium at 4%.

The 1000x version is not a shared spreadsheet. It is the Multiplayer Operating System for Household Wealth.

Money is rarely an individual pursuit; it is relational. It starts with split rent and weekend trips, matures into cohabiting couples managing cash flow and homeownership, expands into allowances and financial literacy for teenagers, and extends to coordinating care for aging parents.

Today, this lifecycle is fragmented across split-pay apps, text threads, shared spreadsheets, and awkward conversations. By owning multi-user coordination, Pocketbook shifts from a disposable tracking utility into permanent household infrastructure.

When Pocketbook becomes the default operating system across generations: * Organic K-factor is built-in: Every core user acquires at least one other user (16% of our couples already pull in a third within 12 months). * Churn approaches zero: Uncoupling a multi-user financial ecosystem requires mutual consensus and massive operational friction. * Monetization expands exponentially: Instead of a single $6/month subscription, we become the rail for high-margin financial services: multi-party savings vaults, high-yield family accounts, teen debit, and estate planning.

---

2. The Mechanism: Why This Works

Our data reveals three self-reinforcing dynamics:

1. Ambient Awareness Replaces Interrogation: Couples open the app nearly 3x as often as solo users (11 days/month vs. 4), with the majority of sessions prompted by partner-spend notifications ("Alex spent $48 at the grocery store"). It eliminates the dreaded "Where did the money go this month?" conversation. Awareness becomes continuous, passive, and low-friction.

2. Micro-Communication Over Macro-Confrontation: 41% of couples actively leave transaction notes in month one—despite the feature being an unpromoted afterthought. Money management is fundamentally emotional. In-line transaction context ("Grabbed dinner for us," "Deposit for Lake Tahoe") de-escalates tension and transforms the app into a collaborative communication channel.

3. Radical Business Model Asymmetry: Moving a user from solo to multiplayer completely resets their unit economics: * Retention: Jumps from 17% (solo) to 58% (couples) and 71% (3+ households). * Premium Conversion: Surges from 4% (solo) to 19% (couples) and 31% (households).

Multiplayer finance is not a niche sub-segment; it is the single most potent retention and monetization engine in the business.

---

3. What We Build First (Q1 Delivery)

We should not ask users to fully merge their finances on day one. Shared budgets retain best when anchored to a specific, high-intent moment: a shared vacation, moving in together, or managing monthly rent.

Our Q1 MVP focuses on "Shared Spaces" around focused financial goals.

* Frictionless Shared Spaces (Category/Goal Sharing): Allow users to invite a partner to co-manage specific categories (e.g., Groceries, Rent, Vacation) without exposing full private accounts. Users link relevant cards/accounts with one-click permission toggles. * Contextual "Money Talk" Threading: Turn transaction notes into a first-class feature: lightweight 1-to-1 in-line comments, emoji reactions, and receipts attached directly to shared transactions. * Smart Multiplayer Notifications: Refine event triggers to drive collaborative habits: shared budget thresholds (e.g., "You've both spent 80% of Dining Out"), payment confirmations, and automated weekly digests. * Contextual Invitation Ingress: Prompts triggered right after a user logs a multi-party expense (e.g., high dining or travel bill): "Split or manage this together with a partner."

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4. How We’ll Know It’s Working

We will validate this initiative across three horizons:

#### A. Input & Activation Metrics (First 30–60 Days) * Invite Completion Rate: Solo-to-couple invite send rate > 12% (up from 3%), with an invitee acceptance rate > 40%. * Activation Moment: > 50% of accepted invites configure at least one Shared Space within 48 hours. * Engagement Velocity: Shared cohort achieves ≥ 8 active app days per user/month, with > 45% using in-line transaction comments or reactions in Month 1.

#### B. Retention & Conversion Metrics (3–6 Months) * Cohort Retention: 6-month retention for Shared Space creators and invitees remains ≥ 50% (maintaining current couple performance as we scale). * Monetization Pull-Through: Free-to-Premium conversion on multiplayer cohorts remains ≥ 15%.

#### C. Expansion Signal (6–12 Months) * Household Viral Loop: ≥ 10% of couples onboard a 3rd member (child, dependent, or shared roommate) within 9 months, validating the transition from couple utility to household operating system.

---

Conclusion

Ana's shared budgets proposal is not just an incremental feature to appease our backlog; it is the blueprint for our entire product transformation. By executing the Q1 MVP, we take our first step away from a commoditized, high-churn personal tracker and establish the foundation of an indispensable, multiplayer household financial network.

Claims the judge couldn’t find in the brief

single-player personal finance is a guilt-driven chore. Users log in alone, feel judged by their charts, and abandon the app.
Money management is fundamentally emotional.
Today, this lifecycle is fragmented across split-pay apps, text threads, shared spreadsheets, and awkward conversations.

Grades and run details

Decision model 55 · LLM judge 36

Decision model checks

failUses the supplied evidence correctly5%
passAddresses the actual decision31%
partialRespects explicit constraints33%
failIdentifies material uncertainty50%
failAvoids unsupported claims87%
passProduces the required deliverable72%
passFinds the mechanism in the data99%
passExtreme, then back to buildable98%
partialProposes tests that could fail86%
partialThe big version gets stronger as it grows49%

Run

Run: #1
API response time: 21 s
Submitted: 6 Oct 2026

Check by check

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

Got wrong 5

Uses the supplied evidence correctlyWrong

The output makes unsupported claims about the current situation (guilt-driven chore, emotional nature, fragmented lifecycle) that are not in the supplied context.

Identifies material uncertaintyWrong

The output does not name any unknowns that could change the decision or say how they would be resolved.

Avoids unsupported claimsWrong

Interpretations like 'guilt-driven chore', 'fundamentally emotional', and 'fragmented across split-pay apps' are presented as established fact without being labelled as hypotheses.

Proposes tests that could failWrong

The metrics have thresholds and windows, but the output does not state what action each outcome would trigger (e.g., kill, pivot, scale).

The big version gets stronger as it growsWrong

The output names compounding mechanisms (built-in acquisition, switching costs) but does not include a test of whether the effect is large enough to matter.

Mixed 1

Addresses the actual decisionMixed

The memo does not state what result or condition would change the decision to build the MVP; it only lists success metrics without linking them to a pivot or kill decision.

Got right 4

Respects explicit constraintsRight

The output is a memo to the CEO, under 900 words, and includes the requested sections (ambitious version, mechanism, first step, how to know it's working).

Produces the required deliverableRight

The memo is complete, in the right form, within the word limit, and a PM could act on it with light edits.

Finds the mechanism in the dataRight

The memo cites retention, conversion, notification, and note-usage data to identify shared money decisions as the mechanism, not just budgeting.

Extreme, then back to buildableRight

It pushes the idea to a 'Multiplayer Operating System for Household Wealth' and works back to a concrete first step (Shared Spaces) that tests the same mechanism.

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 · Harness	Decision model	LLM judge	Runs	Critical failures
1	Haiku 5.5withAPI	85.5	100.0	2	None
2	GPT-6 AstrawithChatGPT	93.0	91.3	2	None
3	GPT-6.1 SolwithAPI	90.7	87.1	2	None
4	GPT-6 LunawithAPI	88.2	83.0	2	None
5	Opus 5.5withClaude	92.7	78.4	2	None
6	Sonnet 5.5withAPI	90.7	74.2	2	None
7	Gemini 3.8 FlashwithAPI	52.5	39.0	2	None
8	Gemini 3.5 Flash-LitewithGemini	50.5	34.8	2	None

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.

Nobody beats these on both score and cost

Task score and relative cost by setup
Setup	Task score	Relative cost (cheapest = 1)
GPT-6 Luna · API	84	1.0×
Haiku 5.5 · API	93	2.1×
Gemini 3.5 Flash-Lite · Gemini	40	2.9×
Gemini 3.8 Flash · API	43	9.1×
GPT-6.1 Sol · API	89	15×
Sonnet 5.5 · API	81	31×
Opus 5.5 · Claude	84	59×
GPT-6 Astra · ChatGPT	92	74×

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

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