Tasks / Growth

Write a GTM plan

Can the model pick the customers who value the difference most, position against what they do today, and build a go-to-market that lasts beyond launch day?

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 18 graded outputs by 9 models. 44% were usable with at most a quick edit.

Reliably right

  1. Positioned against the real alternative100% pass
    Names Miro, photos/slides, and doing nothing as alternatives, and ties the message to real-time tidy diagramming and starting without IT.
    GPT-6 Astra · ChatGPT · Enterprise, without killing the engine
  2. Sells against a pain the buyer feels100% pass
    The message addresses the governance and control pain that IT buyers feel when teams adopt tools without oversight, supported by SSO requests and security-page visits in the data.
    GPT-6 Astra · ChatGPT · Enterprise, without killing the engine
  3. Protects the self-serve engine100% pass
    Uses the 70% free-to-paid stat and product-qualified deal data to argue against capping the free plan, and keeps self-serve open.
    GPT-6 Astra · ChatGPT · Enterprise, without killing the engine

Where it slips

  1. Uses the supplied evidence correctly28% pass
    The claim 'Five of our six losses on existing-user deals ended in no decision' is not supported by the data (4 no-decision, 2 Miro), so a statement about the current situation is invented.
    Opus 5.5 · Claude · Enterprise, without killing the engine
  2. Avoids unsupported claims39% pass
    Presents the incorrect 'five of six no decision' figure as established fact, which is an unsupported claim about the current situation.
    Opus 5.5 · Claude · Enterprise, without killing the engine
  3. Follows the deals data67% pass
    Although it compares by source, the computed product-qualified ACV and sales cycle are wrong, so it does not correctly follow the deals data.
    GPT-6.1 Sol · API · Enterprise, without killing the engine

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. Positioned against the real alternative

    Does the plan name what the target customer does today without this product (including the status quo or doing nothing), and tie the message to the value that alternative lacks?

    Passes when Names the real alternative and the differentiated value against it, and picks the segment that cares most about that value.

  2. Sells against a pain the buyer feels

    Is the core message built on a pain or risk the target buyer already feels, with evidence from the material, rather than on generic upside like saving time?

    Passes when Leads with the pain the evidence shows buyers care about, and uses that evidence to choose the message.

  3. Diagnoses message or channel first

    Does the plan work out whether the problem is the message (people reach it but don't convert) or the channels (the right people never see it), and spend accordingly?

    Passes when Uses conversion and reach data to say which it is, and puts the effort there.

  4. Plans beyond launch week

    Does the plan say how demand keeps coming after launch, with the ongoing engine and what's measured over months, rather than treating launch day as the whole plan?

    Passes when Gives the ongoing motion after launch and the measures that show whether it's working over time.

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 · and 3 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 Flowboard. The board wants $5M of new enterprise ARR next year, and our CRO, Jordan Hale, has drafted the enterprise go-to-market below. The CEO has asked for your version before the board meeting: who we sell to, how the self-serve product and the sales team work together, what we say against the alternatives, the capacity it takes, and what you'd change in Jordan's plan and why. No more than 1,300 words. The files are attached.

What the model was given6 items: About Flowboard, today.md, cro_enterprise_plan.md, enterprise_deals_last_12_months.csv, large_companies_using_flowboard.csv (companies over 1,000 employees with active self-serve or free teams), enterprise_win_loss_interviews.md
About FlowboardOnline whiteboards and diagramming for teams. Free plan, self-serve paid plans, and an enterprise plan sold by a small sales team.
today.md5 lines · Download
# Today

- Self-serve: 31,000 paying teams; free plan feeds 70% of new paying teams.
- Enterprise: 46 customers, average contract $64,000.
- Sales team: 3 account executives, closing about 10 enterprise deals a year each.
cro_enterprise_plan.md8 lines · Download
# Enterprise plan (CRO, draft for the board)

Target: $5M new enterprise ARR next year.
1. Cap the free plan at 3 users (today: unlimited users, 3 boards each), so teams have to talk to us.
2. Route every team over 10 seats to sales; remove self-serve checkout above 10 seats.
3. Hire 8 account executives and 6 SDRs; SDRs work outbound lists of Fortune 2000 companies.
4. Enterprise features: SSO, SCIM, audit logs, data residency.
…
enterprise_deals_last_12_months.csv65 rows · Download
deal,source,outcome,sales_cycle_days,acv_usd,lost_to
E-200,Outbound,won,201,32700,
E-201,Product-qualified (teams already using Flowboard),won,62,97000,
E-202,Product-qualified (teams already using Flowboard),won,61,108000,
E-203,Outbound,lost,192,,Miro (company standard)
E-204,Outbound,lost,204,,Miro (company standard)
E-205,Product-qualified (teams already using Flowboard),won,77,54200,
…
large_companies_using_flowboard.csv (companies over 1,000 employees with active self-serve or free teams)company,employees,teams_using_flowboard,active_users_30d,paying_seats,viewed_security_page_30d,asked_for_sso Aldergate Bank,15000,2,18,10,yes,yes Brightfield Bank,2400,6,54,36,yes,yes Corvel Logistics,15000,5,45,22,yes,yes Dunmore Holdings,4800,3,12,4,yes,yes Eastlake Health,1200,3,30,14,yes,yes Fennick Holdings,4800,8,48,30,yes,yes Galloway Retail,9000,9,36,20,yes,no Hartwell Group,1200,4,48,21,yes,no Iverson Retail,1200,3,18,9,yes,no Juniper Retail,1200,3,24,10,yes,no Kestrel Logistics,4800,1,12,6,yes,no Linton Group,1200,2,10,4,no,no Marlowe Group,2400,2,10,7,no,no Northcote Retail,9000,2,10,6,yes,no Oakhurst Group,9000,3,36,18,yes,no Pemberton Health,1200,1,6,2,yes,no Quayside Bank,4800,2,12,4,no,no Redfern Group,15000,3,18,10,no,no Stanway Health,9000,3,30,12,no,no Thornbury Bank,15000,3,24,12,no,no Upton Bank,9000,3,33,23,yes,no Varden Bank,2400,3,12,5,no,no Whitmore Bank,4800,2,8,5,no,no Yardley Logistics,15000,2,8,4,yes,no
enterprise_win_loss_interviews.md5 lines · Download
# Enterprise win/loss interviews (12 buyers, this year)

- Won (7): every win had teams already using Flowboard. "Our designers refused to give it up." "IT approved it because 300 people were already on it."
- Lost (5): four had standardised on Miro company-wide; switching meant migrating thousands of boards. One stayed on whiteboard photos and slides.
- What buyers said Flowboard does that Miro doesn't: real-time diagramming that stays tidy, and a free plan teams can start on without IT.
What a strong answer doesThe answer key the graders mark against

Builds enterprise sales on top of the self-serve engine instead of throttling it. The deals file shows product-qualified deals (teams already using Flowboard) won 19 of 25 at an average of about $72,600 and about 63 days, against outbound winning 4 of 25 at about $36,800 and about 190 days; product-qualified wins were about $1.38M of the $1.86M won. The free plan feeds 70% of new paying teams. So capping the free plan at three users and removing self-serve checkout above ten seats would choke the pipeline the enterprise business depends on, and the interviews say IT approved Flowboard because teams were already on it. Proposes product-led sales: AEs work the large-company list (multiple teams, SSO requests, security-page visits) with SSO and admin controls as the bridge, while keeping self-serve open. Positions against Miro and the status quo, not 'visual collaboration for the enterprise': where a company has standardised on Miro, don't lead with a migration; win where teams already use Flowboard, on tidy real-time diagramming and starting without IT. Reads outbound's poor results as a message problem as well as a channel one. Works out capacity: $5M at about $72,000 is about 70 deals, far more than three AEs close (about 30 a year), so it needs AE hiring focused on product-qualified accounts rather than SDR outbound lists. Plans the ongoing motion and the measures (product-qualified accounts, conversion, cycle time) beyond the first quarter.

Critical failures (cap the score at 40)
  • Endorses capping the free plan at three users or removing self-serve checkout above ten seats
Task

Staff-level · v1.1

The outputs

9 setups answered this brief.

Needs more than a quick edit9 of 13 checks passed

Several factual errors (PQL ACV, outbound win count, Miro loss count) must be corrected before use, and the inconsistency in the table damages credibility.

Output

To: CEO From: VP Product Subject: Enterprise GTM Plan: Hitting $5M New ARR via Product-Led Sales

Here is my assessment of Jordan’s enterprise draft and an alternative go-to-market plan to hit the board's $5M new enterprise ARR target next year.

If we execute Jordan’s traditional top-down outbound playbook, we will starve our self-serve engine and miss the $5M target. Our data shows we already have a repeatable, high-margin enterprise motion—it is Product-Led Sales (PLS), not cold outbound.

---

1. The Data: What’s Working vs. What’s Failing

An analysis of all 65 enterprise opportunities over the last 12 months ($1.86M total new ARR across 28 wins) reveals three starkly different motions:

Lead SourceDeals WorkedWonWin RateAvg. ACV (Won)Avg. Sales Cycle (Won)Total ARR Won
:---:---:---:---:---:---:---
Product-Qualified (PQL)251976.0%$71,04763 days$1,349,900 (73%)
Inbound Demo15640.0%$55,06786 days$330,400 (18%)
Cold Outbound25312.0%$36,800190 days$147,200 (8%)*

\Note: 4 outbound wins totaling $147.2k (16% win rate).*

Why Cold Outbound Fails: 18 of our 21 outbound losses were to "Miro (company standard)." Win/loss interviews confirm that when Miro is entrenched, ripping and replacing thousands of boards top-down is a non-starter. Outbound AEs spend 6+ months chasing $37k deals with an 84% failure rate.

Why PQLs Win: Every single buyer in our win interviews already had teams using Flowboard ("Our designers refused to give it up"; "IT approved it because 300 people were already on it"). PQLs close 3x faster, at nearly 2x the ACV, and win 76% of the time. Notably, 4 of our 6 PQL losses were to "No decision" (not Miro)—meaning with better IT/security packaging and multi-threading, our PQL win rate could exceed 80%.

---

2. Who We Sell To (ICP & Target Accounts)

We do not sell to cold Fortune 2000 IT buyers. We sell to mid-market and enterprise companies (1,000+ employees) where Flowboard already has grassroots adoption across multiple teams.

We have two immediate buyer personas within these accounts: 1. The Champions (Design, Product, & Engineering Leads): They adopt Flowboard bottoms-up because our real-time diagramming stays tidy (unlike Miro’s freeform sprawl). 2. The Economic/Economic-Gatekeeper Buyer (IT, InfoSec, Procurement): Triggered when usage hits critical mass, shadows IT thresholds, or requires SSO/security reviews.

Immediate Pipeline: Looking at our user base today, we have 24 enterprises (>1,000 employees) with active self-serve/free footprints: * Tier 1 (Immediate Sales Ready - 6 Accounts): Aldergate Bank, Brightfield Bank, Corvel Logistics, Dunmore, Eastlake Health, and Fennick Holdings. All 6 have multiple teams (up to 54 active users), visited our security page in the last 30 days, and explicitly asked for SSO. At our $71k PQL ACV, these 6 accounts alone represent ~$425k in near-term ARR. * Tier 2 (High-Intent Expansion - 10 Accounts): Companies like Galloway Retail (9 teams, 36 active users) and Hartwell Group (4 teams, 48 active users) that viewed our security page in the last 30 days. * Tier 3 (Nurture/Expand - 8 Accounts): Large enterprises (e.g., Redfern, Thornbury Bank) with 2–3 isolated teams where we need to bridge internal silos before pitching IT.

---

3. How Self-Serve and Sales Work Together

Self-serve is not competing with enterprise sales; self-serve is our enterprise customer acquisition cost (CAC) engine. Today, 70% of our 31,000 paying teams come from the free plan.

Instead of erecting paywalls that block adoption, Product and Sales will run a 4-step Land-Consolidate-Close loop:

1. Frictionless Land (Product): Keep the free plan unlimited in users (3 boards/user) and keep self-serve checkout completely open. Let teams inside 5,000-person companies spread Flowboard virally across departments without needing IT or procurement approval. 2. Domain Aggregation & PQL Scoring (Product + Data): Build internal tooling that groups accounts by corporate email domain (`@aldergate.com`). Trigger an automatic PQL alert to Sales when a domain hits any of these thresholds: * $\ge 3$ separate teams or $\ge 25$ active users across an enterprise domain. * Admin/user views the Security page or clicks "Request SSO / Enterprise." * Self-serve spend crosses $5,000/year across corporate credit cards. 3. In-Product "Trojan Horse" Prompts (Product): Show non-intrusive prompts to workspace admins at large domains: "8 other teams at Corvel Logistics use Flowboard. Want to consolidate billing and unlock SSO?" 4. Consultative Consolidation (Sales): Sales reaches out to Champions and IT not with a cold pitch, but with an audit: "You have 54 users across 6 teams paying on separate credit cards. Let’s consolidate your billing, put them under SSO/SCIM, and give you a volume tier."

---

4. Positioning & What We Say Against Alternatives

Jordan’s proposed messaging ("The visual collaboration platform for the enterprise") puts us head-to-head against Miro on their home turf. We will lose that fight.

Our Positioning: "Real-time diagramming and whiteboarding that actually stays tidy—built for product, design, and engineering teams, and ready for enterprise IT."

How We Win Against the Alternatives: * Against "Miro is our company standard" (Our #1 Loss Reason): Don't ask IT to rip and replace Miro company-wide. Position Flowboard as the specialized diagramming standard for technical/design teams where Miro is too messy, OR build a 1-click Miro Board Importer so entrenched teams can migrate without losing thousands of boards (directly solving the objection from 4 of our 5 loss interviews). * Against Status Quo / "No Decision" (Our #1 PQL Loss Reason): Arm champions with an ROI & Security Kit showing IT the risk of unmanaged "shadow IT" diagrams living on personal/fragmented accounts, making enterprise consolidation the safest choice.

---

5. What I Would Change in Jordan’s Plan (and Why)

Jordan’s ProposalMy RecommendationWhy
:---:---:---
1. Cap free plan at 3 usersReject. Keep unlimited users (3 boards).Our win/loss interviews explicitly state our free plan is why we beat Miro. Capping at 3 users kills viral multi-player collaboration and chokes off 70% of our self-serve pipeline.
2. Kill self-serve checkout >10 seatsReject. Keep self-serve open; alert Sales in parallel.Forcing an 11-person team onto a demo call creates friction and drives them to Miro. Let them buy on a credit card—a 20-seat self-serve team is our best enterprise PQL.
3. Hire 8 AEs + 6 SDRs for F2000 outboundModify to 5 new AEs (8 total) + 2 Product-Led SDRs.Cold outbound has a 16% win rate, 190-day cycle, and $37k ACV. Hiring 6 cold SDRs wastes ~$700k+ in burn. We need Product-Led SDRs who mine our 31,000 paying teams for multi-team expansion.
4. Build SSO, SCIM, Audit Logs, Data ResidencySequence carefully: Ship SSO, SCIM, & Domain Discovery Q1. Defer Data Residency.SSO and SCIM unlock our 24 warm enterprise accounts immediately. Add Admin Domain Discovery (so IT can see/claim existing teams) and a Miro Importer. Defer Data Residency—it is a multi-quarter infrastructure sinkhole, and zero lost deals cited it.
5. Generic Enterprise MessagingFocus on "Tidy Real-Time Diagramming + Zero-Friction IT Governance."Differentiates us on what users actually love while answering IT's security needs.

---

6. Capacity & Math to Hit $5M New ARR

To hit $5M in new enterprise ARR next year, here is the capacity math:

  • Deal Volume Needed: At our PQL average ACV of $71,000, $5M requires ~70 closed-won deals (vs. 28 this year).
  • Pipeline Needed: Assuming a conservative 65% blended win rate on PQL/warm inbound deals, Sales needs to work ~108 qualified enterprise opportunities next year.
  • AE Capacity: Today, 3 AEs close ~10 deals/year each (30 total) while wasting half their time on 200-day outbound losses. Focused purely on 63-day PQLs and warm inbound, a ramped AE can comfortably close 12–14 deals/year (~$850k–$1M ARR/AE).
  • Hiring Plan:
  • Keep our 3 current AEs (expected yield: ~36–40 deals / $2.7M ARR).
  • Hire 5 new AEs in Q1 (ramping to ~6–7 deals each in Year 1 = ~32 deals / $2.3M ARR).
  • Hire 2 Product-Led SDRs (to map org charts inside our 31,000 paying teams and connect AEs with IT/Procurement) and 1 Sales Engineer (to handle security reviews and accelerate the 63-day cycle).

Bottom Line: We don't need to break our product to build an enterprise business. By turning our 31,000 self-serve teams into our enterprise hunting ground, shipping SSO/SCIM + Domain Claiming in Q1, and scaling to 8 PQL-focused AEs, we will hit the $5M target while accelerating—not cannibalizing—self-serve growth.

Claims the judge couldn’t find in the brief

  • Product-qualified average ACV (won) is $71,047.
  • Cold outbound: 25 deals, 3 won (12% win rate).
  • 18 of our 21 outbound losses were to Miro.
  • Self-serve is not competing with enterprise sales; self-serve is our enterprise customer acquisition cost (CAC) engine.

Grades and run details

Decision model 73 · LLM judge 71
Decision model checks
  • failUses the supplied evidence correctly91%
  • passAddresses the actual decision83%
  • passRespects explicit constraints48%
  • partialIdentifies material uncertainty31%
  • failAvoids unsupported claims70%
  • passProduces the required deliverable56%
  • failFollows the deals data56%
  • passProtects the self-serve engine100%
  • passDoes the capacity sums86%
  • passPositioned against the real alternative98%
  • passSells against a pain the buyer feels100%
  • passDiagnoses message or channel first94%
  • passPlans beyond launch week95%
Run
Run
#1
API response time
27 s
Submitted
13 Oct 2026

Check by check

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

Got wrong 3

Uses the supplied evidence correctlyWrong

Multiple facts are incorrect (PQL average ACV, outbound win count, Miro loss count), so not every statement about the current situation is supported by the evidence.

Identifies material uncertaintyWrong

Does not name specific unknowns that could change the decision or explain how they would be resolved.

Avoids unsupported claimsWrong

States interpretations and forecasts (e.g., 'self-serve is our enterprise CAC engine', 'Jordan's plan will starve our self-serve engine') as fact without hedging.

Mixed 1

Follows the deals dataMixed

Computes win rate, deal size, and cycle by source and builds the motion on product-qualified accounts.

Got right 9

Addresses the actual decisionRight

Commits clearly to a product-led sales motion early in the memo, addressed to the CEO, even if it does not explicitly state what would change the call.

Respects explicit constraintsRight

Memo is under 1,300 words, addressed to CEO, and the plan does not endorse capping the free plan or removing self-serve checkout.

Produces the required deliverableRight

Produces a complete memo covering who we sell to, self-serve/sales interplay, positioning, capacity, and changes to the CRO plan, within length and for the CEO.

Protects the self-serve engineRight

Uses the 70% free-plan contribution and product-qualified deal data to show the cost of capping, and keeps self-serve open.

Does the capacity sumsRight

Calculates ~70 deals needed at $71k, pipeline needed, and AE capacity with checkable sums.

Positioned against the real alternativeRight

Names the real alternatives (Miro company standard, status quo/no decision) and ties message to tidy diagramming and frictionless adoption.

Sells against a pain the buyer feelsRight

Leads with pain of messy diagrams and unmanaged shadow IT, supported by buyer quotes from the interviews.

Diagnoses message or channel firstRight

Identifies that outbound fails because it targets Miro-entrenched accounts (channel misalignment) and misaligned messaging, and pivots effort to product-qualified accounts.

Plans beyond launch weekRight

Describes an ongoing land-consolidate-close loop with PQL scoring and product-led SDRs, not a one-time launch.

Results

Every setup we’ve tested on this task type, across all its tasks and repeats, graded on the current checklist. Calibrated.

#Model · HarnessTask scoreDecision modelLLM judgeRunsCritical failures
1GPT-6 AstrawithChatGPT95.8100.02None
2Opus 5.5withClaude94.185.22None
3GPT-6 LunawithAPI88.589.32None
4GPT-6.1 SolwithAPI93.878.02None
5Sonnet 5.5withAPI89.977.72None
6Haiku 5.5withAPI88.077.72None
7Gemini 3.8 FlashwithAPI72.181.92None
8Gemini 4 ArgonwithAPI74.070.32None
9Gemini 3.5 Flash-LitewithGemini70.063.52None

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.607080901001×3×10×30×100×Cost per output, relative to the cheapest setup (log scale) →↑ Task scoreGPT-6 Astra · ChatGPT: task score 98, 81× the cheapestOpus 5.5 · Claude: task score 90, 75× the cheapestGPT-6 Luna · API: task score 88, the cheapestGPT-6.1 Sol · API: task score 84, 16× the cheapestSonnet 5.5 · API: task score 80, 46× the cheapestHaiku 5.5 · API: task score 80, 3.3× the cheapestGemini 3.8 Flash · API: task score 76, 11× the cheapestGemini 4 Argon · API: task score 69, 18× the cheapestGemini 3.5 Flash-Lite · Gemini: task score 66, 3.5× the cheapestGPT-6 Astra · ChatGPTOpus 5.5 · ClaudeGPT-6 Luna · APIGPT-6.1 Sol · APISonnet 5.5 · APIHaiku 5.5 · APIGemini 3.8 Flash · APIGemini 4 Argon · 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 · API881.0×
Haiku 5.5 · API803.3×
Gemini 3.5 Flash-Lite · Gemini663.5×
Gemini 3.8 Flash · API7611×
GPT-6.1 Sol · API8416×
Gemini 4 Argon · API6918×
Sonnet 5.5 · API8046×
Opus 5.5 · Claude9075×
GPT-6 Astra · ChatGPT9881×

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

Taking a product or add-on to market with marketing and sales.

Why it matters

Launch plans fail by trying to reach everyone, by selling upside nobody feels, and by treating launch day as the whole plan.

What good looks like

  • One primary segment: those who value the difference most
  • Positions against what customers do today
  • Sells against a pain the buyer feels, with evidence
  • Diagnoses whether the problem is the message or the channel
  • Plans beyond launch week

Deliberately not measured

  • Creative copywriting quality
Capability tested

Go-to-market judgement

The failure we’re looking for

Every channel, every segment, and nothing after launch day

Grading

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