Plan headcount when AI is changing the workforce.
The board has asked for a 10% cut and a roadmap that still ships. The HR system shows people. The AI dashboard shows tools. Nothing shows you which tools can absorb which work, or what a contractor-to-agent swap would cost.
Flowstate gives you one ledger across humans, contractors and agents. Model the swap. Run the scenario. See the cost before you make it real.
AI productivity is real. So is AI cost. Plan against both.
The peer-reviewed evidence on AI-assisted engineering productivity is in. The next question is what it costs, and whether the swap saves money.
Controlled study of GitHub Copilot users: a 26.08% increase in weekly task completion. A real productivity lever, not vendor marketing.
MIT Economics, “Generative AI on High-Skilled Work” →Average 3.6 hours per week saved by developers using AI coding tools. At a 200-engineer org, that’s 37,400 hours back, or roughly 18 FTE of capacity reclaimed.
DX, AI Coding Assistant productivity research →For 500 developers: GitHub Copilot Business ~$114k/yr, Cursor Teams ~$192k/yr. A material decision, and one that compounds with the per-request token costs we’re also tracking.
DX, AI Coding Assistant pricing 2025 →The modules that solve this
Three products that turn a board mandate into a runnable plan, not a spreadsheet.
Scenario Planning
Model what-if scenarios for hybrid workforce changes. Like a git-diff for engineering costs.
Workforce Analytics
Real-time dashboards for headcount, cost and utilisation. The people-side of the ledger.
AI Spend Insights
The AI-side of the ledger. Cost per agent, per project, per person, reconcilable against the human cost it’s replacing.
See the swap before you commit to it.
Book a demo. We’ll model your next-quarter plan against your current ledger: humans, contractors, agents, all in one number.