If you're searching for fair equity grant first hire startup benchmark, you're trying to solve a real problem, not collect definitions. This guide walks through it step by step, the way we'd explain it to a founder sitting across the table.
Quick Answer
Fair equity grant first hire startup benchmark comes down to your specific numbers, not a generic rule of thumb — the fastest way to get a real answer is to model it against your actual cap table instead of a spreadsheet estimate.
- Start from your real numbers, not an industry average
- Revisit this every time you issue new equity or close a round
- Use a live cap table so the math updates automatically
The Equity Question Every Founder Faces
The Equity Question Every Founder Faces. Here's what that covers: how much is "fair"? too little = they leave, too much = you give away the company, carta data: median first hire gets 1.49% of fully diluted shares, and how it plays out in practice.
How much is "fair"? Too little = they leave, too much = you give away the company
How much is "fair"? Too little = they leave, too much = you give away the company. This is the step most founders underestimate — worth getting right before it turns into a bigger cleanup job later.
Carta data: Median first hire gets 1.49% of fully diluted shares
Carta data: Median first hire gets 1.49% of fully diluted shares. It sounds minor until it isn't, usually right when an investor or new hire is looking at the numbers. Carta publishes first-hire equity benchmarks but doesn't help individuals apply them.
But that's an aggregate—YOUR number depends on YOUR situation
But that's an aggregate—YOUR number depends on YOUR situation. Get this wrong early and it compounds quietly until your next round forces the issue.
Interactive: Figure out YOUR first hire equity
Interactive: Figure out YOUR first hire equity. This is exactly the kind of detail that's easy to skip and expensive to fix retroactively.
Benchmarks by Role
Benchmarks by Role. Here's what that covers: engineering first hire: 0.5% - 2.0%, sales first hire: 0.25% - 1.5%, and how it plays out in practice. This is where benchmark actually shows up on your cap table.
Engineering first hire: 0.5% - 2.0%
Engineering first hire: 0.5% - 2.0%. Get this wrong early and it compounds quietly until your next round forces the issue. This is an emotional decision for founders.
Sales first hire: 0.25% - 1.5%
Sales first hire: 0.25% - 1.5%. This is exactly the kind of detail that's easy to skip and expensive to fix retroactively. Lovie: education + calculator + assurance = differentiation.
Marketing/Operations first hire: 0.2% - 1.0%
Marketing/Operations first hire: 0.2% - 1.0%. Most spreadsheet-based cap tables miss this until someone asks a question they can't answer on the spot.
Your industry matters
Your industry matters. — specifically, AI startups grant MORE equity.
Factors That Change Equity Sizing
Factors That Change Equity Sizing. Here's what that covers: stage at hire, salary cut, and how it plays out in practice. This is where series a actually shows up on your cap table.
Stage at hire
Stage at hire. — specifically, pre-seed vs seed vs Series A.
Salary cut
Salary cut. — specifically, if they take less cash, more equity.
Seniority/title
Seniority/title. — specifically, founding member = higher %.
Runway
Runway. Are you bootstrapped or funded?
Lovie's First Hire Equity Calculator
Lovie's First Hire Equity Calculator. Here's what that covers: input: role, seniority, salary reduction, input: your funding stage, and how it plays out in practice.
Input: Role, seniority, salary reduction
Input: Role, seniority, salary reduction. It sounds minor until it isn't, usually right when an investor or new hire is looking at the numbers.
Input: Your funding stage
Input: Your funding stage. Get this wrong early and it compounds quietly until your next round forces the issue.
Output: Recommended equity % + range
Output: Recommended equity % + range. This is exactly the kind of detail that's easy to skip and expensive to fix retroactively.
See: Comparison to Carta benchmark data
See: Comparison to Carta benchmark data. Most spreadsheet-based cap tables miss this until someone asks a question they can't answer on the spot.
The Psychology of Equity Grants
The Psychology of Equity Grants. Here's what that covers: ownership mentality: equity changes behavior, retention: 4-year vesting means 4-year commitment, and how it plays out in practice.
Ownership mentality: Equity changes behavior
Ownership mentality: Equity changes behavior. This is exactly the kind of detail that's easy to skip and expensive to fix retroactively.
Retention: 4-year vesting means 4-year commitment
Retention: 4-year vesting means 4-year commitment. Most spreadsheet-based cap tables miss this until someone asks a question they can't answer on the spot.
Fairness: Equal salary, equal equity? Not always
Fairness: Equal salary, equal equity? Not always. This is the step most founders underestimate — worth getting right before it turns into a bigger cleanup job later.
Growth: First hire's equity should feel generous enough to say yes
Growth: First hire's equity should feel generous enough to say yes. It sounds minor until it isn't, usually right when an investor or new hire is looking at the numbers.
Interactive Scenario: Equity As Retention Tool
Interactive Scenario: Equity As Retention Tool. Here's what that covers: simulate: grant too little = they leave at year 2, simulate: grant too much = you regret it at series a, and how it plays out in practice.
Simulate: Grant too little = they leave at Year 2
Simulate: Grant too little = they leave at Year 2. This is the step most founders underestimate — worth getting right before it turns into a bigger cleanup job later.
Simulate: Grant too much = you regret it at Series A
Simulate: Grant too much = you regret it at Series A. It sounds minor until it isn't, usually right when an investor or new hire is looking at the numbers.
Simulate: Grant "right amount" = mutual success
Simulate: Grant "right amount" = mutual success. Get this wrong early and it compounds quietly until your next round forces the issue.
See financial outcome of each scenario
See financial outcome of each scenario. This is exactly the kind of detail that's easy to skip and expensive to fix retroactively.
Lovie's Advantage
Lovie's Advantage. Here's what that covers: carta: data + analysis, no personalization, pulley: no guidance on equity fairness, and how it plays out in practice.
Carta: Data + analysis, no personalization
Carta: Data + analysis, no personalization. Get this wrong early and it compounds quietly until your next round forces the issue.
Pulley: No guidance on equity fairness
Pulley: No guidance on equity fairness. This is exactly the kind of detail that's easy to skip and expensive to fix retroactively.
Lovie: Data-driven, calculator + guidance + cap table integration
Lovie: Data-driven, calculator + guidance + cap table integration. Most spreadsheet-based cap tables miss this until someone asks a question they can't answer on the spot.
None of this has to live in a spreadsheet you're afraid to open. For more on fair equity grant first hire startup benchmark, Lovie Cap Table is built to handle it alongside formation, funding, and equity tracking — not as three separate tools.
