Free planner · Nothing stored
Sales Capacity Planner for Scale-ups
Enter your current ARR, next year's target, your median deal size and how long a deal takes to close. It returns how many reps to hire and when each one starts, the meetings they have to run to get there, and what the year costs.
This model is for enterprise ACV and a real sales cycle, not high-volume transactional PLG. The $25K deal-size chip is a sensitivity, not the motion.
AssumptionsFailure haircut 30% · Max hires 2/mo · 1 SE per 2.5 AEs · 1 BDR per 2.5 AEs · Leadership on · Cash comp
Leadership auto-staffs: a sales leader at 5+ AEs, a BDR manager at 3+ BDRs, an SE lead at 3+ SEs.
Swipe to see all columns
| Role | Base | Variable | OTE |
|---|---|---|---|
| Enterprise AE | |||
| Sales engineer | |||
| BDR | |||
| Sales leader (Area VP) | |||
| BDR manager | |||
| SE lead (Field CTO) |
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01The Hiring ScheduleMax build: 18 AEs by month 9, and the window still tops out.
The hiring scheduleThe max build: 18 new seats.
Front-loaded at 2 hires a month. Cell shading steps with production intensity: the capacity staircase, made visible.
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02Expected BurnBudget $5.37M of in-year build comp, $7.14M across the org.
Expected burnThe build costs $5.37M in year one.
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03Sales Activity MathBook 1,479 discovery meetings, 31 a week across the team.
Companion page This math says how many meetings. It does not say where they come from. The weekly pipeline plan: six fields, a research prompt built for one account, and the loop that decides Monday instead of hoping on Thursday. Companion page The calendar says when. The scorecard says who. Stage gates, AE / BDR / SE / FDE / GTM engineer selection, ramp gates, and the ungated hiring kit.Sales activity mathThe activity math behind the $6.21M.
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04Unit CapacityBank $600K from each new seat in year one, $1.00M a year at steady state.
Unit capacityA rep is a $600K asset in year one.
Bookings ramp, one new seatThe workbook behind this page ships free: download the xlsx.
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05The BridgeExit at $8.62M, $1.38M short of the target, after the 30% haircut.
The bridgeYou need $7.59M of net-new logo ARR.
After the 30% failure haircut, that takes $10.84M of gross seat capacity. The carried bench brings $3.62M; hiring covers the rest.
$1.38M short of the $10.00M target. Extend the window, raise the deal size, or shorten the cycle.
36 is the whole org build. 18 is AEs.
Scenario · not a guaranteed lift
AI changes the math.
The planner above does not change. A seat is still $1.0M a year at full ramp and about $600K in year one. I do not cut ramp because a vendor sold a copilot. What the 2026 data supports is a labeled scenario I can compare, not a new default.
The Bridge Group's 2026 AE study puts average ramp at 6.2 months, the highest in that study's history. 48% of AEs hit quota. Median quota sat at $960K on 4.6x OTE. The cycle slider on this page still picks the ramp band. I leave it there.
ICONIQ's State of GTM 2026 (January 2026 survey, 150-plus B2B companies) is the per-FTE picture. AI-embedded GTM posted about $640K of net-new ARR per GTM employee against about $370K without that embedding. That is a different unit from the $1.0M AE seat in Unit Capacity. I keep them on separate lines.
The same ICONIQ cut, recapped by SaaStr, has 67% of ramped AEs at quota when AI is fully embedded, against 59% when it is not. I will run that as a sensitivity. I will not load it into quota until it repeats for two quarters.
Net-new ARR per GTM employee
ICONIQ 2026. Scenario comparison, not this planner's seat math.
ICONIQ: about $370K net-new ARR per GTM employee without AI embedding, about $640K with it.
Source: ICONIQ, Leaner, Smarter, Flatter / State of GTM 2026. About $640K vs $370K.
Ramped AEs at quota
ICONIQ via SaaStr. Observational. I do not treat the gap as a hire plan.
ICONIQ via SaaStr: 59% of ramped AEs at quota without full AI embedding, 67% with it.
Source: ICONIQ via SaaStr, Faster Closes. Shorter Contracts. Leaner Teams.
Gong Labs, State of Revenue AI 2026 is the at-bats reminder. Attainment fell from 52% to 46%. Gong says the cause is fewer opportunities per rep, not a lower win rate. Frequent AI users showed 77% higher revenue per rep. Vendor data, on Gong customers. That is why Sales Activity Math still prints the meetings you have to book. A copilot that does not add held meetings does not change the bridge.
Bain's 2025 technology report estimates sellers spend about 25% of their time selling, and that AI could roughly double that. Estimate, not a measured result on this page. Bain's 2026 B2B Growth Agenda (1,125 executives) says spend is shifting to AI over new reps, and tech sales hiring that grew 18% a year from 2017 to 2022 now grows under 1% a year. Fewer, better-equipped seats. Still seats.
Shar Babaie framed the 2027 planning fight on LinkedIn: if AI makes a rep 15% more productive, should quota go up 15%? My answer is no, not on the first print. I leave the lift on this scenario line. The planner's Advanced steady-state override is the lever if you want to model a number you already believe. I do not ship that override set.
Deal execution still sits on the Playbook. Agents still sit on Pipeline Gen. If you believe this scenario, you still have to hire the people who can run it. That is Team Buildout.
Sources, all third-party: The Bridge Group, AE Models, Motions & Metrics 2026; ICONIQ, State of GTM 2026; SaaStr recap of ICONIQ; Gong Labs, State of Revenue AI 2026; Bain, AI Is Transforming Productivity, but Sales Remains a New Frontier; Bain, The New Sales Productivity Equation; Shar Babaie on LinkedIn. None of these numbers are mine. The $1.0M seat and the 6.2-month ramp stay.
This is one module of a 31-page Sales Playbook.
The full Sales Playbook covers the nine-stage system, the AI-native engine, the team, and the operating cadence. It is on this site, free and ungated.
If the planner sized the seats, start at Enterprise AE.