{
  "version": "1.3.0",
  "releasedAt": "2026-05-20",
  "kpi": {
    "rogueId": "product.total_engineers",
    "slug": "total_engineers",
    "domain": "product",
    "defaultLabel": "Total Engineers",
    "description": "Headcount of engineers (software, infrastructure, security, data, ML) in the R&D organization, typically including full-time employees plus contractors at a defined FTE-equivalence factor. The \"capacity input\" side of all R&D ratios. Common pitfall: definition drift. Some companies include only software engineers, others include product managers and designers, others include all of R&D plus QA, plus support engineers. Boards should anchor the definition once and hold it stable — otherwise quarter-over-quarter comparisons are noise. Pair with `rd_monthly_spend` to derive fully-loaded cost-per-engineer.",
    "fieldType": "number",
    "unit": null,
    "maturity": "general",
    "suggestedForStages": [
      "seriesA",
      "seriesB",
      "seriesC",
      "public"
    ],
    "defaultOwningFunctions": [
      "R&D"
    ],
    "stageRelevance": {
      "seriesA": "recommended",
      "seriesB": "recommended",
      "seriesC": "recommended",
      "public": "recommended"
    },
    "definitionSource": {
      "tier": "editorial",
      "sourceName": "imboard Editorial",
      "sourceUrl": null,
      "sectionRef": null,
      "publicationDate": "2026-04-01",
      "attributionNotice": null
    },
    "formula": "Count of engineering headcount (FTE + contractor FTE-equivalence). Define inclusion explicitly: SWE-only vs SWE+PM+Design vs all-of-R&D-including-QA. Hold the definition stable across quarters; surface the definition in a footnote.",
    "whyItMatters": "Capacity denominator for every R&D ratio — `rd_efficiency`, ARR-per-engineer, cost-per-engineer, throughput-per-engineer. The board reads this to gauge whether team growth is keeping pace with revenue and product-surface-area growth.",
    "interpretationGuidance": "No single benchmark; the right number depends on product complexity, business model, and platform vs. point-solution architecture. The SaaS Capital Annual Survey reports revenue-per-employee for its private SaaS panel (see revenue-per-employee section of the latest edition) — pair `total_engineers` with company-wide headcount and ARR to derive both engineer-density (engineers ÷ total headcount) and ARR-per-engineer. Industry folk-wisdom, not citation-grade: engineer density of 25–40% is typical at product-led growth-stage SaaS; lower at sales-led, higher at infrastructure / platform companies.",
    "relatedKpiIds": [
      "product.rd_monthly_spend",
      "product.rd_efficiency",
      "product.capacity_allocation_pct",
      "product.innovation_capacity_pct",
      "hr.arr_per_fte"
    ],
    "metricBasis": {
      "timeBasis": "point_in_time",
      "production": "primary"
    }
  }
}