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 16 graded outputs by 8 models. 50% were usable with at most a quick edit.

Reliably right

  1. Positioned against the real alternative100% pass
    It names the real alternatives (accountant-run payroll with mistakes, owner spreadsheet with risk) and ties the message to confidence and accuracy that those alternatives lack.
    GPT-6 Astra · ChatGPT · Payroll, for the people who fear it
  2. 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
  3. Does the capacity sums100% pass
    Works out deals needed (69-80), qualified opportunities (134), and AE-years (8) with checkable arithmetic.
    GPT-6 Astra · ChatGPT · Enterprise, without killing the engine

Where it slips

  1. Avoids unsupported claims47% 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
  2. Uses the supplied evidence correctly52% 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
  3. Identifies material uncertainty73% pass
    The plan does not name specific unknowns that could change the decision, nor does it say how they would be resolved or what would trigger a pivot.
    Gemini 3.8 Flash · API · Payroll, for the people who fear it

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 2 written for each task, which you’ll see in the tasks below.

The tasks

Read the brief, then compare up to three outputs, each with the LLM judge’s verdict on every check. Highlights mark what a PM had to fix.

The brief

You're the PM for Ledgerly Payroll, a new add-on for our accounting product, launching to existing customers on 3 November. Marketing has drafted the launch plan below. Write the go-to-market plan you'd run instead (or the changes you'd make to theirs), in no more than 900 words: who we go after first, what we say to them, through which channels, and how we'll know it's working over the following three months. The files are attached.

What the model was given5 items: About Ledgerly, marketing_launch_draft.md, customers_by_size_and_payroll_method.csv (penalty notices: share who told us they got a payroll penalty notice last year), beta_headline_test.csv (two versions of the in-app payroll page, shown at random to beta customers), customer_calls.md
About LedgerlyAccounting software for small businesses: invoicing, bank feeds, bookkeeping. 8,000 paying customers. Payroll is a new add-on at $6 per employee per month.
marketing_launch_draft.md7 lines · Download
# Draft launch plan (Head of Marketing)

- Launch day 3 November: press release announcing Ledgerly as "the first Financial Operating System for small business".
- Paid social and search ads to new prospects: $60,000 in November.
- In-app banner to all 8,000 customers: "Run payroll in minutes".
- Webinar in launch week.
- Success measure: press mentions and sign-ups in launch week.
customers_by_size_and_payroll_method.csv (penalty notices: share who told us they got a payroll penalty notice last year)employees,current_payroll,customers,penalty_notices_last_year_pct 1-4,Owner does it in a spreadsheet,3140,4 1-4,Accountant runs it,1020,6 5-25,Owner does it in a spreadsheet,690,19 5-25,Accountant runs it,1480,23 5-25,Another payroll tool,1210,7 26-50,Another payroll tool,460,5
beta_headline_test.csv (two versions of the in-app payroll page, shown at random to beta customers)headline,landing_page_visits,started_setup,ran_first_payroll "Run payroll in minutes, right where you do your books",4210,92,38 Never get a payroll penalty again,4160,268,117
customer_calls.md10 lines · Download
# Customer calls about payroll (excerpts, September)

1. Bakery, 12 staff: "My accountant does payroll. Last spring they filed late and I got a $1,400 penalty. I don't know what I'm paying them for."
2. Plumbing firm, 18 staff: "Time isn't the issue. I'm scared of getting it wrong. The tax office letter was the worst week of my year."
3. Design studio, 3 staff: "It's me and two freelancers. A spreadsheet's fine."
4. Café group, 22 staff: "We use another tool, it's OK. Switching sounds like a nightmare mid-year."
5. Physio clinic, 9 staff: "I'd move tomorrow if it meant one less thing that can go wrong with the tax office."
…
What a strong answer doesThe answer key the graders mark against

Picks customers with 5 to 25 employees whose accountant runs payroll (1,480 customers, 23% had a penalty notice) and those doing it in a spreadsheet (690, 19%), not the smallest businesses (happy with a spreadsheet) or those on another payroll tool (switching mid-year is the barrier). Builds the message on fear of penalties and errors, not time: in the beta, 'Never get a payroll penalty again' got about three times as many setups as 'Run payroll in minutes' (268 against 92 from similar traffic, 6.4% against 2.2%) and more first payrolls (117 against 38), and the calls say the same. Reads this as a message problem, not a channel problem: the existing customer base already sees the page, so fix the message and reach existing customers in-app and through their accountants before spending $60,000 on ads to strangers. Drops the 'Financial Operating System' category claim. Plans beyond launch week: prompts around payroll and tax deadlines, accountant referrals, and monthly measures such as payroll attach in the target segment, first payrolls run, and penalties avoided.

Critical failures (cap the score at 40)
  • Keeps 'Run payroll in minutes' as the lead message despite the headline test
Task

Mid-level · v1.0

The outputs

8 setups answered this brief.

Usable with a quick edit12 of 12 checks passed

The plan is evidence-based, actionable, and covers all required elements; a PM could execute it with only minor wording adjustments.

Output

Ledgerly Payroll go-to-market plan | 3 November–31 January

1. Start with customers who have the clearest problem

First priority: existing customers with 5–25 employees who currently run payroll themselves or rely on an accountant. That’s 2,170 customers: 690 spreadsheet users and 1,480 whose accountant runs payroll. In these groups, 19% and 23%, respectively, said they received a payroll penalty notice last year. Treat that as a signal of pain—not proof that Ledgerly would prevent penalties.

Lead with accountant-run customers who want more visibility and control, while making clear Ledgerly isn’t accusing their accountant of poor work. Follow with spreadsheet users in the same size band, for whom a simpler alternative to manual payroll may appeal.

Defer broader prospecting. Among customers with 1–4 employees, reported penalty notices are lower (4–6%); several calls also suggest some are content with free spreadsheets. Customers already using another payroll tool reported fewer notices (7% for 5–25 employees), and one call highlighted switching friction. Test those groups later, after validating onboarding and migration. Don’t prioritize 26–50-employee customers until we know the product and support experience fit their needs.

2. Say what we can support—not what we can’t promise

The beta headline test is a useful directional signal:

  • “Never get a payroll penalty again”: 268/4,160 visitors started setup (6.4%); 117 ran first payroll (2.8%).
  • “Run payroll in minutes…”: 92/4,210 started (2.2%); 38 ran first payroll (0.9%).

The penalty-focused version performed better, but don’t use “Never get a payroll penalty again” unless Ledgerly can substantiate that guarantee. Instead test responsible variants such as:

  • “More confidence in payroll, alongside your books.”
  • “Take control of payroll and reduce the risk of costly mistakes.”

Be explicit that payroll is $6 per employee per month. Emphasize control, confidence and working in the same accounting product—not guaranteed outcomes or unverified features. Tailor the message: “Keep a closer eye on payroll” for accountant-run customers; “Move beyond the spreadsheet” for owner-run customers.

3. Use customer channels before buying reach

  • Before launch: Segment the 2,170 priority customers and invite a small cohort to try setup. Interview users who start but don’t finish; check readiness, support capacity and any limitations before broad promotion.
  • Launch, 3 November: Send segmented email to the priority cohort and show a targeted in-app message when those customers use Ledgerly. Link directly to a clear product and pricing page, not a generic announcement. Offer a live, practical webinar on setup and common payroll concerns, with time for questions.
  • During November–January: Follow up based on behavior: a setup reminder for visitors who don’t start, and personal onboarding or support for customers who start but don’t run payroll. Invite accountant-run customers to involve their accountant where appropriate. Expand in-app promotion to other segments only after reviewing early results.
  • Earned media: A factual product announcement is fine, but don’t make press mentions the launch objective. Skip the $60,000 broad paid campaign to new prospects until existing-customer activation and retention are proven.

4. Measure adoption and outcomes for three months

Track weekly by customer segment and by funnel step: eligible → reached → product-page visit → setup started → setup completed → first payroll run → repeat payroll run. Report both counts and conversion rates; compare messages with a randomized test where possible.

Use the beta as a benchmark, not a forecast. A reasonable initial goal is to beat its stronger variant’s 6.4% visit-to-setup-start and 2.8% visit-to-first-payroll rates in the priority cohort. Also set a three-month target for repeat payroll runs among first-time users, and review setup abandonment to find where customers get stuck.

Pair adoption metrics with guardrails: payroll-related support contacts, failed or corrected runs, cancellations/refunds, and customer feedback about confidence and accuracy. Review weekly with Product, Support and Marketing. If activation is weak, fix onboarding or clarify the offer before adding spend. If customers run payroll but don’t repeat, investigate reliability, fit and switching friction before expanding the campaign.

Grades and run details

Decision model 100 · LLM judge 100
Decision model checks
  • passUses the supplied evidence correctly77%
  • passAddresses the actual decision93%
  • passRespects explicit constraints66%
  • passIdentifies material uncertainty83%
  • passAvoids unsupported claims63%
  • passProduces the required deliverable82%
  • passPicks the segment with the pain100%
  • passUses the headline test77%
  • passPositioned against the real alternative98%
  • passSells against a pain the buyer feels96%
  • passDiagnoses message or channel first99%
  • passPlans beyond launch week100%
Run
Run
#1
API response time
17 s
Submitted
5 Oct 2026

Check by check

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

Got right 12

Uses the supplied evidence correctlyRight

All factual claims about the current situation are directly supported by the supplied data or arithmetic.

Addresses the actual decisionRight

The output commits to a clear primary segment, message, channels, and measures, and states conditions for expanding later.

Respects explicit constraintsRight

The plan stays under 900 words, does not lead with 'save time', and avoids paid ads to new prospects as the main channel.

Identifies material uncertaintyRight

It identifies that the penalty message needs substantiation, treats the beta as directional, and specifies how weak activation or repeat usage would change the approach.

Avoids unsupported claimsRight

Interpretations like 'want more visibility' are tied to call evidence and not presented as established fact; hypotheses are hedged.

Produces the required deliverableRight

The output is a complete go-to-market plan with segment, message, channels, and three-month measures, within the word limit.

Picks the segment with the painRight

It targets 5–25 employee customers with accountant-run or spreadsheet payroll, cites penalty rates, and explains why smaller and tool-using segments are deferred.

Uses the headline testRight

It cites the beta test results and builds the message on penalty and accuracy concerns, even while avoiding the unsubstantiated guarantee.

Positioned against the real alternativeRight

It names the real alternatives (accountant, spreadsheet, another tool) and ties the message to confidence and reduced risk that those alternatives lack.

Sells against a pain the buyer feelsRight

The core message leads with penalty fear and accuracy, supported by call quotes and the beta test, not generic time-saving.

Diagnoses message or channel firstRight

It uses conversion data to diagnose that message matters more than reach, and focuses on in-app and email to existing customers before buying ads.

Plans beyond launch weekRight

The plan includes ongoing follow-up, behavior-based nudges, and three-month funnel and guardrail metrics beyond launch week.

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 AstrawithChatGPT100.0100.02None
2Opus 5.5withClaude96.085.22None
3GPT-6 LunawithAPI94.289.32None
4GPT-6.1 SolwithAPI93.878.02None
5Sonnet 5.5withAPI98.177.72None
6Haiku 5.5withAPI94.277.72None
7Gemini 3.8 FlashwithAPI73.981.92None
8Gemini 3.5 Flash-LitewithGemini74.263.52None

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 100, 81× the cheapestOpus 5.5 · Claude: task score 91, 75× the cheapestGPT-6 Luna · API: task score 90, the cheapestGPT-6.1 Sol · API: task score 84, 16× the cheapestSonnet 5.5 · API: task score 84, 46× the cheapestHaiku 5.5 · API: task score 82, 3.3× the cheapestGemini 3.8 Flash · API: task score 77, 11× the cheapestGemini 3.5 Flash-Lite · Gemini: task score 68, 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 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 · API901.0×
Haiku 5.5 · API823.3×
Gemini 3.5 Flash-Lite · Gemini683.5×
Gemini 3.8 Flash · API7711×
GPT-6.1 Sol · API8416×
Sonnet 5.5 · API8446×
Opus 5.5 · Claude9175×
GPT-6 Astra · ChatGPT10081×

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