Benchmark compensation for a {{title}} at a {{company size, stage, sector}} in {{geography}}.
Inputs:
- Specific role + scope (org size reporting in, P&L responsibility, public-company status): {{paste}}
- Stage of company + last raised round: {{paste — Series A vs PE vs public matters hugely}}
- Sector specifics (industry vertical + sub-vertical): {{paste}}
- Geography (HQ + remote-acceptable): {{paste}}
Output:
## Total comp band (annual)
| Component | P25 | P50 | P75 | P90 | Notes |
|---|---|---|---|---|---|
| Base | | | | | |
| Cash bonus / variable | | | | | Typical %, paid out at what plan |
| Equity (annual grant value) | | | | | Vesting, refresh frequency |
| Sign-on (one-time) | | | | | Cash + equity, vesting |
| Total comp | | | | | |
## Assumptions baked into the range
- Geographic anchor (e.g., NYC base 1.0, SF +5%, EU -20%)
- Stage anchor (Series C tech vs. mature PE-owned)
- Sector adjustment
- Public vs. private equity treatment
## Where the data is thin
Components where public data is thin (esp. private-company equity values) and where the range relies on extrapolation. Mark them.
## Comparable roles to also benchmark
Roles that look similar in title but differ in scope. Different "VP Engineering" at different stages can be a $200K vs $700K total comp difference.
## What's not in the range
- Severance / change-of-control terms
- Health, retirement, perks
- Deferred comp / RSU concentration policies
- Tax treatment by jurisdiction
## Sources
Every number with a source + date.
Hard rules:
- Date every data point — exec comp moves fast at frontier-AI companies especially
- Distinguish "all-in target comp" from "realized comp last year"
- Flag any range from <5 data points
- Don't extrapolate across stages without saying so explicitlyexecutive-compbenchmarkinghiring