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

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
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
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

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
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
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.

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.
April DunfordLenny’s Podcast
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.
Jeanne DeWitt GrosserLenny’s Podcast
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.
Emily KramerLenny’s Podcast
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.
Arielle JacksonLenny’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 · 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.

GPT-6 AstraChatGPT100Usable with a quick edit Opus 5.5Claude89Usable with a quick edit Sonnet 5.5API82Needs more work GPT-6.1 SolAPI82Needs more work Haiku 5.5API80Needs more work GPT-6 LunaAPI75Needs more work Gemini 4 ArgonAPI70Needs more work Gemini 3.8 FlashAPI68Needs more work Gemini 3.5 Flash-LiteGemini57Needs more work

Gemini 4 ArgonAPI

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 Source	Deals Worked	Won	Win Rate	Avg. ACV (Won)	Avg. Sales Cycle (Won)	Total ARR Won
:---	:---	:---	:---	:---	:---	:---
Product-Qualified (PQL)	25	19	76.0%	$71,047	63 days	$1,349,900 (73%)
Inbound Demo	15	6	40.0%	$55,067	86 days	$330,400 (18%)
Cold Outbound	25	3	12.0%	$36,800	190 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 Proposal	My Recommendation	Why
:---	:---	:---
1. Cap free plan at 3 users	Reject. 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 seats	Reject. 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 outbound	Modify 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 Residency	Sequence 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 Messaging	Focus 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

Gemini 3.8 FlashAPI

Needs more than a quick edit9 of 13 checks passed

The output invents Miro's tagline and calls Miro the category leader without evidence, requiring fact-checking before use. Otherwise the plan is solid.

Output

MEMORANDUM

TO: Chief Executive Officer FROM: VP Product DATE: October 24, 2023 SUBJECT: Counter-Proposal to CRO Enterprise GTM Plan: Path to $5M New Enterprise ARR

Executive Summary

Reaching $5M in new enterprise ARR next year is achievable, but Jordan’s draft will choke the very engine that powers our business.

Jordan’s proposal relies on a legacy top-down playbook: restricting free/self-serve adoption and deploying cold outbound reps against Fortune 2000 accounts. The data from our last 12 months shows this approach is commercially unviable: * Cold outbound fails: Outbound win rates are 16%, sales cycles take 190 days, ACV is low ($36.8k), and 68% of losses go to Miro because they already hold the enterprise standard. * Product-Qualified Leads (PQLs) dominate: Enterprise deals originating from existing Flowboard usage boast a 76% win rate, a 64-day cycle, and an average ACV of $72.6k.

Flowboard does not win by out-shouting Miro in cold enterprise RFPs. We win via Product-Led Sales (PLS): landing virally with teams via our free and self-serve plans, and expanding into six-figure IT-sponsored enterprise contracts once organic adoption takes root.

---

What to Change in Jordan’s Plan & Why

Jordan's CRO Proposal	VP Product Recommendation	Why (Data-Backed Rationale)
:---	:---	:---
1. Cap free plan at 3 users (today: unlimited users, 3 boards).	Keep unlimited users / 3 boards. Introduce team-level sharing limits, but preserve viral intra-company collaboration.	Free plans feed 70% of self-serve paying teams. In enterprise win interviews, buyers explicitly cited that having "300 people already on it" forced IT approval. Capping users kills viral distribution and hands bottom-up adoption to competitors.
2. Remove self-serve above 10 seats; force teams to talk to sales.	Keep self-serve checkout up to 50 seats. Trigger automated sales outreach at 15+ seats or multi-team domain clusters.	31,000 paying teams rely on friction-free checkout. Shunting 11-seat teams to AEs bogs sales down in sub-$5k transactions instead of closing $70k+ enterprise contracts.
3. Hire 8 AEs and 6 cold SDRs targeting the Fortune 2000.	Hire 4 AEs and 2 Product BDRs (totaling 7 AEs, 2 BDRs). Point them exclusively at internal expansion and high-intent inbound.	Cold outbound yielded just 4 wins in 12 months. Reps running outbound into the Fortune 2000 run directly into entrenched Miro enterprise agreements. Product BDRs mining our existing base will generate 4x higher pipeline value.
4. Enterprise features: SSO, SCIM, audit logs, residency.	Agree, with precise sequencing: Prioritize SAML SSO, SCIM, and Domain Capture/Admin Console immediately.	6 large accounts (e.g., Aldergate Bank, Fennick Holdings) have already viewed security pages and requested SSO. Domain capture turns rogue usage into an immediate enterprise contract trigger.
5. Messaging: "The visual collaboration platform for the enterprise."	Messaging: "Precision diagramming and structured collaboration teams actually adopt."	"Visual collaboration platform" is Miro’s tagline. We cannot beat the category leader at their own positioning; we win on structured diagramming clarity and viral ease-of-use.

---

1. Who We Sell To (Target ICP)

We do not target cold accounts. Our Enterprise ICP consists of: * Target Accounts: Mid-market and Enterprise companies (1,000–15,000+ employees), heavily indexing on engineering, architecture, product, and design organizations. * Entry Footprint: Organizations with $\ge$2 active Flowboard teams or $\ge$20 active users across free/self-serve tiers. * Economic Buyers: VP of IT / CISO (concerned with governance, security, consolidation) paired with internal VP/Director Champions in Product/Engineering. * Immediate Target List: The 24 large enterprises already using Flowboard (e.g., Corvel Logistics, Brightfield Bank). Six of these companies already have multiple teams, paying seats, and active requests for SSO—representing an immediate pipeline of ~$450k ARR.

---

2. The Product-Led Sales Engine: Product & Sales Alignment

Instead of sales acting as a barrier to product adoption, the product serves as the primary pipeline generation channel for sales.

``` [ Free Plan: Unlimited Users ] ──> [ Self-Serve Expansion (up to 50 seats) ] │ │ └───> [ Domain Consolidation Trigger ] <───┘ │ ▼ [ Enterprise Sales (SSO, Governance, Security) ] ```

1. Top of Funnel (Free): Maintain the unlimited-user tier to let individual squads adopt Flowboard without procurement hurdles. 2. Expansion Triggers (PQL Engine): Instrument automated alerts to the BDR/AE team when: * A single company domain crosses 20 active monthly users across workspaces. * A workspace admin visits `/security`, `/compliance`, or searches for "SSO". * Multiple corporate credit cards from the same domain are paying for disjointed self-serve accounts. 3. In-Product Enterprise Gates: * Domain Control & SSO: When IT attempts to enforce SSO, the domain is claimed, prompting an enterprise consolidation conversation. * Centralized Admin & Audit Logs: Free and self-serve plans lack cross-workspace audit logs, data retention policies, and SCIM provisioning.

---

3. Positioning Against Alternatives (Winning Against Miro)

In head-to-head enterprise RFPs against Miro, we lose (17 outbound losses last year were to Miro standards). Switching thousands of legacy boards is an impossible sell. We win by changing the battleground:

Dimension	Miro	Flowboard
:---	:---	:---
Core Value	Broad, freeform digital whiteboard. Can quickly become cluttered and unwieldy.	Structured, precision diagramming that stays organized in real time.
Target User	General business users, workshop facilitators, broad marketing.	Technical & Product teams: System architects, engineers, UX designers, technical PMs.
Enterprise Pitch	"Standardize everyone on a single massive whiteboard."	"Complement or replace messy whiteboards with structured architecture and technical execution workflows."
Pricing / Procurement	Expensive wall-to-wall licensing with heavy IT mandates.	Frictionless bottoms-up landing that consolidates high-value technical teams with zero onboarding friction.

Key Narrative: "Miro is where teams brainstorm; Flowboard is where technical teams design, architect, and build. Keep Miro for casual sticky-notes, or standardize on Flowboard for clean, mission-critical systems architecture."

---

4. Capacity Model & Math to $5M New Enterprise ARR

Jordan’s proposal to hire 8 AEs and 6 cold SDRs adds excessive headcount burn with terrible pipeline efficiency. By focusing on PQLs and high-intent inbound, our reps will achieve substantially higher conversion and velocity.

#### Operating Assumptions (Derived from Historical Data) * Average Enterprise ACV: $70,000 (historical PQL average is $72.6k; outbound was $36.8k). * Target ARR: $5,000,000 $\rightarrow$ Requires 72 closed enterprise deals. * Win Rate: 60% (blended between 76% historical PQL win rate and 40% inbound demo rate). * Deals Needed in Late-Stage Pipeline: $72 / 0.60 = \mathbf{120\text{ qualified opportunities}}$. * Sales Cycle: 65–75 days (allowing fast pipeline velocity and intra-year closes).

#### Staffing Requirements * Account Executives (AEs): * Experienced enterprise AE capacity on warm PQLs = 12 deals/year ($840k ARR quota). * 72 deals $\div$ 12 deals/rep = 6 fully productive AEs. * Plan: Retain our 3 current AEs; hire 4 new AEs (staggered: 2 in Q1, 2 in Q2 to account for ramp). Total = 7 AEs. * Business Development Reps (Product BDRs): * Hire 2 Product BDRs (not 6 cold outbound SDRs). * BDRs do not dial cold Fortune 2000 lists. They mine our 31,000 paying teams, identifying multi-license domains, mapping org charts, and securing meetings with IT directors and engineering leads. * Capacity: 2 BDRs generating 5 qualified enterprise pipeline meetings/month each = 120 qualified opportunities/year. * Total Headcount Investment: 6 new hires (4 AEs, 2 BDRs) vs. Jordan’s 14 new hires (8 AEs, 6 SDRs).

This delivers more than 50% savings in customer acquisition cost (CAC) while cutting execution risk.

---

5. Summary of Recommended Product & GTM Deliverables

1. Q1 Product Roadmap Enablers: * Ship SAML 2.0 SSO, SCIM user provisioning, and Centralized Domain Capture. * Build internal PLG scoring dashboard connecting Segment/Mixpanel product events to Salesforce/HubSpot (flagging $\ge$2 teams or SSO searches). 2. Q1 Pricing & Packaging: * Keep Free (unlimited users, 3 active boards). * Keep Self-Serve Pro/Team up to 50 seats. * Package SSO, SCIM, custom data retention, and audit logs exclusively in Enterprise. 3. Sales Enablement: * Arm sales with the "Architecture vs. Whiteboarding" competitive battlecards against Miro. * Launch warm outreach sequences immediately into the 24 identified large accounts already using Flowboard.

Claims the judge couldn’t find in the brief

Miro is the category leader.
'Visual collaboration platform' is Miro's tagline.

Grades and run details

Decision model 69 · LLM judge 71

Decision model checks

failUses the supplied evidence correctly86%
passAddresses the actual decision86%
passRespects explicit constraints37%
failIdentifies material uncertainty73%
failAvoids unsupported claims48%
passProduces the required deliverable72%
failFollows the deals data28%
passProtects the self-serve engine100%
passDoes the capacity sums94%
passPositioned against the real alternative73%
passSells against a pain the buyer feels95%
passDiagnoses message or channel first79%
passPlans beyond launch week91%

Run

Run: #1
API response time: 47 s
Submitted: 6 Oct 2026

GPT-6 LunaAPI

Needs more than a quick edit10 of 13 checks passed

The output contains factual errors in the large-company list numbers and a minor inaccuracy in the product-qualified cycle time, so a PM would need to re-check the data before using it.

Output

Flowboard enterprise plan: win through product-led adoption

Recommendation: Keep the self-serve engine intact and build enterprise sales around teams already getting value from Flowboard. The evidence favors converting in-product demand over broad cold outbound: these deals close faster, win more often, and are larger. We should fund enough sales capacity to pursue the $5M target—but tie hiring and enterprise investment to qualified demand, not a Fortune 2000 list.

Who we sell to

Prioritize companies where Flowboard is already spreading: multiple teams, growing usage, and signs of a security or administration need. The initial champion is likely a designer or other team lead; IT and security become buyers or approvers when the company wants broader rollout, SSO, or governance.

The large-company usage list gives us a practical starting point: 17 of 24 accounts viewed the security page, and two explicitly asked for SSO. Pair those signals with active users, paying seats, and multiple teams to prioritize outreach. Don’t assume every large company—or every team above an arbitrary seat count—is ready to buy enterprise.

How self-serve and sales work together

Protect the free plan. Today it has unlimited users, and it feeds 70% of new paying teams. Capping free at three users risks removing the very collaboration and internal spread that create enterprise demand.

Instead, use the product to identify account-level buying signals: adoption across teams, rising active users or seats, and security-page visits or SSO interest. Let teams continue to start, collaborate, and buy self-serve. Offer sales help when signals suggest a broader rollout or an enterprise requirement—not as a checkout gate.

Sales should turn successful team adoption into company-wide deployment: align stakeholders, address security and procurement, and support rollout and migration. This makes the product the entry point and sales the path to a larger, governed deployment.

What we say—and don’t say—against alternatives

“The visual collaboration platform for the enterprise” is too generic. Our sharper position is: Flowboard makes real-time diagramming that stays tidy easy for teams to adopt—and easier for enterprises to approve once it spreads.

In the last 12 months, product-qualified deals—teams already using Flowboard—won 19 of 25 opportunities (76%), with an average winning contract of about $73K and a roughly 66-day sales cycle. Outbound won 4 of 25 (16%), with an average winning contract of about $37K and a much longer cycle. Interviews reinforce the pattern: all seven interviewed buyers who chose Flowboard already had teams using it.

Miro is the main competitive obstacle, not a reason to claim generic enterprise superiority. Four of five interviewed losses had standardized on Miro, and moving thousands of boards was a barrier. Don’t lead with a rip-and-replace pitch. Win a team or workflow where tidy, real-time diagramming matters; expand after demonstrating value. Make migration and coexistence easier where we can.

SSO, SCIM, audit logs, and data residency can help clear enterprise buying requirements, but they aren’t our differentiation. Prioritize SSO, SCIM, and audit logs; validate demand and deal impact before committing to the potentially heavier data-residency investment.

Capacity and the $5M target

The 65 logged opportunities produced 29 wins worth about $1.86M—roughly in line with today’s $64K average contract. At that average, $5M requires about 78 wins; at the product-qualified average of $73K, it requires about 69. That is roughly 2.4–2.7 times the observed win output.

At today’s stated productivity of about 10 wins per AE per year, plan for roughly eight productive AE-equivalents. With three current AEs, that implies about five additional AEs if all are fully productive. Hire early enough to account for ramp, and gate any further hiring on qualified pipeline and conversion—not just a calendar plan. The current product-qualified volume also must grow substantially: 19 wins from 25 opportunities is strong conversion, but cannot by itself support the target at today’s volume. Track the adoption signals and enterprise-qualified pipeline needed to scale it.

What I’d change in Jordan’s plan

Keep free unlimited by users; don’t remove self-serve checkout above 10 seats. Both changes add friction to a channel that supplies most new paid teams and could slow the adoption that drives our best enterprise wins.
Replace six outbound SDRs targeting Fortune 2000 lists with focused account development. Outbound won 4 of 25 logged opportunities and often encountered entrenched Miro standards. Prioritize named accounts showing Flowboard usage and buying signals; use a small, targeted outbound motion to complement product-led demand.
Hire to the evidence-based capacity need, not 11 AEs by default. Plan for eight productive AE-equivalents, stage incremental hiring against pipeline, and ensure the team can support enterprise rollout as well as close deals.
Make enterprise features a buying enabler, not the headline. Prioritize the security capabilities buyers need, but lead with Flowboard’s distinctive diagramming experience and bottom-up adoption.

The core strategic shift is from forcing teams into sales to helping proven adoption become an enterprise deployment.

Claims the judge couldn’t find in the brief

Product-qualified deals won 19 of 25 opportunities (76%), average winning contract ~$73K, ~66-day sales cycle
17 of 24 large-company accounts viewed the security page, and two explicitly asked for SSO

Grades and run details

Decision model 77 · LLM judge 79

Decision model checks

failUses the supplied evidence correctly19%
passAddresses the actual decision82%
passRespects explicit constraints79%
partialIdentifies material uncertainty86%
partialAvoids unsupported claims19%
passProduces the required deliverable67%
failFollows the deals data43%
passProtects the self-serve engine100%
passDoes the capacity sums94%
passPositioned against the real alternative80%
passSells against a pain the buyer feels97%
passDiagnoses message or channel first72%
passPlans beyond launch week83%

Run

Run: #1
API response time: 33 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 1

Identifies material uncertaintyWrongWrongRight

Gemini 4 Argon · API

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

Gemini 3.8 Flash · API

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

GPT-6 Luna · API

It identifies that current product-qualified volume must grow, ties hiring to pipeline, and says to validate demand before committing to data residency.

All got wrong 2

Uses the supplied evidence correctlyWrongWrongWrong

Gemini 4 Argon · API

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.

Gemini 3.8 Flash · API

Claims that Miro is the category leader and that 'visual collaboration platform' is Miro's tagline are not in the supplied context.

GPT-6 Luna · API

The output states 17 of 24 accounts viewed the security page and two asked for SSO, but the data shows 16 and 6 respectively; also the product-qualified average cycle is 63 days, not 66.

Avoids unsupported claimsWrongWrongWrong

Gemini 4 Argon · API

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.

Gemini 3.8 Flash · API

It presents 'Miro is the category leader' and 'Miro's tagline' as facts without evidence, and 'cold outbound fails' as an unqualified conclusion.

GPT-6 Luna · API

The claim about 17 security-page views and two SSO requests is presented as fact but is incorrect, and the 66-day cycle is slightly off without being labelled as an estimate.

All mixed 1

Follows the deals dataMixedMixedMixed

Gemini 4 Argon · API

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

Gemini 3.8 Flash · API

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

GPT-6 Luna · API

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

All got right 9

Addresses the actual decisionRightRightRight

Gemini 4 Argon · API

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.

Gemini 3.8 Flash · API

The memo commits to a clear counter-proposal with specific changes, ICP, and capacity plan.

GPT-6 Luna · API

The output commits early to keeping self-serve intact and building on product-led adoption, and says hiring should be gated on qualified pipeline.

Respects explicit constraintsRightRightRight

Gemini 4 Argon · API

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

Gemini 3.8 Flash · API

The output is a memo to the CEO under 1,300 words, respecting the form and length.

GPT-6 Luna · API

The output stays within 1,300 words, covers all requested topics, and does not propose capping the free plan or removing self-serve checkout.

Produces the required deliverableRightRightRight

Gemini 4 Argon · API

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.

Gemini 3.8 Flash · API

The memo covers all requested elements: who to sell to, self-serve/sales alignment, positioning, capacity, and changes to Jordan's plan.

GPT-6 Luna · API

The output is a complete plan in memo form for the CEO, within the word limit, covering all required elements.

Protects the self-serve engineRightRightRight

Gemini 4 Argon · API

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

Gemini 3.8 Flash · API

It uses the 70% free-to-paid stat and PQL data to argue against capping, and keeps self-serve open up to 50 seats.

GPT-6 Luna · API

It explains that capping the free plan would remove the collaboration that creates enterprise demand, uses the 70% figure, and keeps self-serve open.

Does the capacity sumsRightRightRight

Gemini 4 Argon · API

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

Gemini 3.8 Flash · API

It calculates 72 deals at $70k ACV, 120 opportunities at 60% win rate, and 6 AEs, with checkable sums.

GPT-6 Luna · API

It calculates 69-78 deals needed, 8 productive AE-equivalents, and 5 additional AEs, with gating on pipeline.

Positioned against the real alternativeRightRightRight

Gemini 4 Argon · API

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

Gemini 3.8 Flash · API

It names Miro and the status quo (whiteboard photos) as alternatives, and positions on structured diagramming for technical teams.

GPT-6 Luna · API

It names Miro and the status quo as alternatives, positions on tidy real-time diagramming and starting without IT, and picks the segment already using Flowboard.

Sells against a pain the buyer feelsRightRightRight

Gemini 4 Argon · API

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

Gemini 3.8 Flash · API

The message leads with the pain of messy whiteboards and lack of adoption, supported by win/loss interviews.

GPT-6 Luna · API

The message leads with the value that the status quo lacks (tidy diagramming, adoption without IT), which aligns with the pain of losing a tool teams love and IT approval friction.

Diagnoses message or channel firstRightRightRight

Gemini 4 Argon · API

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

Gemini 3.8 Flash · API

It diagnoses cold outbound as a channel problem and Miro's positioning as a message problem, shifting spend to PLS.

GPT-6 Luna · API

It diagnoses outbound's poor results and shifts resources to product-qualified demand, effectively identifying channel as the primary issue.

Plans beyond launch weekRightRightRight

Gemini 4 Argon · API

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

Gemini 3.8 Flash · API

It describes ongoing PLS triggers, BDR mining, and a Q1 roadmap with scoring dashboard, not just launch.

GPT-6 Luna · API

It says to track adoption signals and enterprise-qualified pipeline, and to gate hiring on pipeline, providing an ongoing measure beyond launch.

Results

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

#	Model · Harness	Decision model	LLM judge	Runs	Critical failures
1	GPT-6 AstrawithChatGPT	95.8	100.0	2	None
2	Opus 5.5withClaude	94.1	85.2	2	None
3	GPT-6 LunawithAPI	88.5	89.3	2	None
4	GPT-6.1 SolwithAPI	93.8	78.0	2	None
5	Sonnet 5.5withAPI	89.9	77.7	2	None
6	Haiku 5.5withAPI	88.0	77.7	2	None
7	Gemini 3.8 FlashwithAPI	72.1	81.9	2	None
8	Gemini 4 ArgonwithAPI	74.0	70.3	2	None
9	Gemini 3.5 Flash-LitewithGemini	70.0	63.5	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	88	1.0×
Haiku 5.5 · API	80	3.3×
Gemini 3.5 Flash-Lite · Gemini	66	3.5×
Gemini 3.8 Flash · API	76	11×
GPT-6.1 Sol · API	84	16×
Gemini 4 Argon · API	69	18×
Sonnet 5.5 · API	80	46×
Opus 5.5 · Claude	90	75×
GPT-6 Astra · ChatGPT	98	81×

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

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

What AI gets right here, and what you’ll still have to catch

Reliably right

Where it slips

How it’s graded

Positioned against the real alternative

Sells against a pain the buyer feels

Diagnoses message or channel first

Plans beyond launch week

Plus our standard checks

The tasks

The outputs

Output

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

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

3. How Self-Serve and Sales Work Together

4. Positioning & What We Say Against Alternatives

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

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

Claims the judge couldn’t find in the brief

Grades and run details

Decision model checks

Run

Output

Executive Summary

What to Change in Jordan’s Plan & Why

1. Who We Sell To (Target ICP)

2. The Product-Led Sales Engine: Product & Sales Alignment

3. Positioning Against Alternatives (Winning Against Miro)

4. Capacity Model & Math to $5M New Enterprise ARR

5. Summary of Recommended Product & GTM Deliverables

Claims the judge couldn’t find in the brief

Grades and run details

Decision model checks

Run

Output

Flowboard enterprise plan: win through product-led adoption

Who we sell to

How self-serve and sales work together

What we say—and don’t say—against alternatives

Capacity and the $5M target

What I’d change in Jordan’s plan

Claims the judge couldn’t find in the brief

Grades and run details

Decision model checks

Run

Check by check

Where they differ 1

All got wrong 2

All mixed 1

All got right 9

Results

What you get for the cost

About the task

The PM job

Why it matters

What good looks like

Deliberately not measured