Founder Comp Playbook logo

Founder Comp Playbook

Organization
LeadMagic
founder-comp-playbook

Founder guide to GTM compensation — what you can afford, how to set OTE and equity, budget guardrails, valuing packages for candidates, and negotiation scripts when cash is tight. Covers hiring first AE/SDR/VP and founder-side offer/counter-offer tactics. Use when a founder asks how to comp sales hires, negotiate offers, explain equity, or defend quota math. Triggers on: "founder comp", "how much to pay first AE", "negotiate sales offer as founder", "comp budget startup", "what equity to offer", "candidate wants more money", "can't afford VP Sales salary", "founder hiring compensation".

Overview

PublisherLeadMagic
Repositorygtm-skills
Skill namefounder-comp-playbook
Stars
72
Forks
18
Bundled files
10
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 10 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by LeadMagic on GitHub. Read the source before you install it.

Installation

Install the Founder Comp Playbook AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/LeadMagic/gtm-skills/tree/main/skills/founder-led/founder-comp-playbook
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/LeadMagic/gtm-skills.git /tmp/gtm-skills
mkdir -p .claude/skills
cp -r /tmp/gtm-skills/skills/founder-led/founder-comp-playbook .claude/skills/founder-comp-playbook
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Founder Comp Playbook in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Founder Comp Playbook on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Founder Comp Playbook is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Founder Comp Playbook

Overview

Founders lose hires in two ways: underpaying with mystery (candidate ghosts after RepVue check) or overpaying with hero OTE (runway dies in 9 months). Cash-constrained founders must negotiate with total package math — OTE, quota, equity, ramp, and trajectory — not emotional number-matching.

This skill is the founder-specific comp layer: what you can afford by ARR stage, how to value equity honestly, employer negotiation scripts, and when to walk. Canonical GTM comp strategy → executive-compensation/references/gtm-compensation-strategy.md (Pattern 35). IC bands + templates → gtm-role-descriptions. Close mechanics → gtm-recruiting. VP/CRO clauses → executive-compensation.

Not legal advice. Offer letters → employment-compliance.

When to Use

  • "How much should I pay my first AE?"
  • "Candidate wants $20K more — what do I do?"
  • "How do I explain our equity grant?"
  • "Can we afford a VP Sales?"
  • "Founder comp budget for sales team"
  • "Negotiate without matching Google cash"
  • "What quota goes with $140K OTE?"
  • "Post-acquisition retention comp" / "earn-out employment package"

Authoritative Foundations

  • Jason Lemkin. Founder closes 10–20 deals before first AE. VP Sales before ~$2M ARR: high failure rate. Don't hire title before motion.
  • Mark Roberge. Quota:OTE ~5:1 — if you raise OTE, raise quota proportionally or you overpay for under-delivery.
  • David Skok. Payroll + S&M as % of ARR must fit unit economics; comp is not separate from CAC.
  • Bridge Group / RepVue (2025–2026). Candidates arrive with crowdsourced attainment data — your posted range must match reality.
  • Sam Jacobs / Pavilion. Executive hires expect multi-gate variable and peer calibration — not handshake promises.

Step-by-Step Process

Phase 1 — Can You Afford This Hire?

Load references/founder-comp-budget.md. Quick guardrails:

Company ARRMax fully-loaded sales payroll % ARRTypical first hire
<$500KFounder only + contractorsNo FTE AE yet
$500K–$1.5M15–25% ARR1 full-stack AE
$1.5M–$5M20–35% ARRAE + SDR or 2 AEs
$5M–$15M25–40% ARRManager + pod
$15M+Board-modeledVP / CRO

Fully loaded = base + employer taxes + benefits + variable at target + tool cost per rep (gtm-tool-cost-model).

Bootstrap rule: If hire pushes runway below 12 months without revenue lift, delay or use contractor (hiring-contractors).

Phase 2 — Set the Range (Before Sourcing)

Use references/comp-benchmarks-2026.md (synced with gtm-role-descriptions H1 2026 bands).

HirePublish in JDInternal ceiling
First AE$120–150K OTE+10% for proven unicorn
SDR #1$60–75K OTEMatch market, not discount
VP Sales$220–280K OTE+Pavilion band check

Founder mistake: Posting "$80–200K OTE" — signals chaos. Post narrow band.

Phase 3 — Value the Package (Show the Math)

Candidates care about expected earnings, not headline OTE.

Expected cash = base + (variable × expected attainment %)
ComponentFounder must explain
Quota$700K ARR for $140K OTE (5:1)
Team attainment"68% hit quota last year" (honest)
Ramp50% Q1, 75% Q2 quota
Equity0.5% FD, 4yr/1yr cliff, current $8M post → $40K paper
Signing bonusBridge if they leave forfeited bonus

Template: templates/founder-offer-walkthrough.md

Equity honesty: Share last 409A or post-money valuation range, option count, FD%, and refresh policy. Hiding FD% kills trust.

Phase 4 — Founder Negotiation Levers (Cash Tight)

Priority order when candidate pushes:

LeverCost to companyCandidate value
Lower quota (with lower OTE)LowHigh — earnability
Steeper ramp Q1–Q2MediumHigh
Equity + refresh commitmentDilutionHigh at seed–B
Signing bonus (one-time)CashMedium
Territory / ICP tierLowHigh for AE
Title / path to leadLowMedium
Base increase without quota fixHigh ongoingShort-term

Never: Raise OTE without quota adjustment (breaks 5:1).
Never: Promise "we'll fix comp after 90 days" without writing it.

Scripts: references/founder-negotiation-scripts.md

Phase 5 — Candidate Asks (Playbook)

AskFounder response
"+$15K OTE""Let's model quota at 5:1 — that's $75K more quota. Or we hold OTE and add 0.05% equity + $10K signing."
"Match current $160K OTE""Share comp plan. We'll match cash if attainment ≥100% last 4Q and motion fits."
"More equity"Show FD% table by role (references/comp-benchmarks-2026.md). Offer refresh at 12 mo on attainment.
"Guaranteed year-one"Signing bonus only — not guaranteed variable.
"Competing offer deadline Friday"Pre-draft counters before finals; respond in 24h with written package.

Walk away if: won't share attainment, demands 2× market with no proof, needs enterprise comp for SMB motion.

Phase 6 — Executive Hires (VP / CRO)

Founders often cannot compete on cash alone.

StageFounder move
$3–8M ARRVP not CRO; equity-heavy; system-building gates
$8–15M ARRPavilion peer comp check; board approval
Bootstrap profitableProfit-share or bonus vs inflated base

Load executive-compensation — never handshake CRO packages.

Phase 7 — Founder Receiving Comp (Advisor / Acqui / Side Role)

When founder is the candidate (advisor, operating partner, post-exit):

  • Anchor on cash + equity + time — not vanity title
  • Advisor: 0.1–0.5% over 2yr vest or $2–10K/mo cash retainer
  • Negotiate: pro-rata, information rights, acceleration on change of control
  • advisor-recruitment, equity-management

Output Format

RequestDeliverable
AffordabilityPayroll % ARR model + runway impact
First hire compOTE band + quota + equity table
NegotiationCounter-offer script + lever matrix
Candidate walkthroughtemplates/founder-offer-walkthrough.md filled
VP packageRedirect to executive-compensation + board memo

Quality Check

  • Payroll % ARR within stage guardrails
  • Quota:OTE ~5:1 documented
  • Published JD range matches written offer
  • Equity FD% and valuation context shared
  • Ramp schedule in offer
  • Team attainment disclosed (or first-hire ramp explicit)
  • Written offer within 48–72h of verbal yes

Common Pitfalls

  1. Hire before motion. Comp can't fix unproven product. Fix: founder closes 10–20 first.
  2. OTE vanity contest. $180K OTE / $900K quota beats $200K / $2M quota. Fix: show math.
  3. Equity hand-wave. "We'll be generous later." Fix: grant numbers in writing.
  4. Geo bait-and-switch. Offer remote then cut 20%. Fix: band in JD.
  5. Skip RepVue check. Candidates know your reputation. Fix: align posted vs paid.

Execution Artifacts

  • references/framework-notes.md
  • templates/output-template.md
  • scripts/check-output.py
  • references/gtm-compensation-strategy.md — master playbook (cross-link)
  • references/comp-by-role-stage.md — stage matrix
  • the executive-compensation skill (ote-calculator-template.md) — quota math
  • references/founder-comp-budget.md — ARR-stage payroll guardrails
  • references/founder-negotiation-scripts.md — employer scripts by scenario
  • references/comp-benchmarks-2026.md — dated ranges (sync with role-descriptions)
  • templates/founder-offer-walkthrough.md — candidate-facing package explainer
  • templates/founder-counter-offer.md — structured counter template Cross-skill: saas-outcomes/references/exit-metrics-matrix.md (payroll vs ARR at exit scale)

Post-Close Retention (Earn-Out Context)

When sale includes earn-out + employment, model total package — base, bonus, rollover, earn-out — not salary alone. Load exiting-company/references/negotiating-earn-out.md:

  • Prefer retention bonus (time-based) separate from performance earn-out
  • Negotiate role/title before close; comp band should match founder-comp-budget.md guardrails
  • At-will termination with full earn-out forfeiture → walk or re-trade (counsel required)
  • Worksheet: exiting-company/templates/earn-out-term-sheet-review.md

Related Skills

  • gtm-role-descriptions — JD + IC comp templates
  • gtm-recruiting — sourcing, close timeline, inclusive hiring
  • executive-compensation — VP/CRO clauses
  • solo-founder-gtm — when to hire + lean stack
  • financial-modeling — runway impact of payroll
  • saas-outcomes — bootstrap vs venture comp philosophy
  • exiting-company — earn-out and retention package negotiation

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Founder Comp Playbook AI skill do?

Founder guide to GTM compensation — what you can afford, how to set OTE and equity, budget guardrails, valuing packages for candidates, and negotiation scripts when cash is tight. Covers hiring first AE/SDR/VP and founder-side offer/counter-offer tactics. Use when a founder asks how to comp sales hires, negotiate offers, explain equity, or defend quota math. Triggers on: "founder comp", "how much to pay first AE", "negotiate sales offer as founder", "comp budget startup", "what equity to offer", "candidate wants more money", "can't afford VP Sales salary", "founder hiring compensation".

Why use Founder Comp Playbook on TypingMind?

Because you install it once and use it with any model. Founder Comp Playbook is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Founder Comp Playbook in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LeadMagic/gtm-skills/tree/main/skills/founder-led/founder-comp-playbook. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Founder Comp Playbook?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Founder Comp Playbook?

As many as you like. As long as a model supports skills, you can use Founder Comp Playbook with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Founder Comp Playbook AI skill free?

Yes. It is published on GitHub by LeadMagic under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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