WhatA platform that uses real-time labor market data, AI productivity metrics, and financial modeling to help tech companies right-size their engineering teams instead of panic-hiring and panic-firing in cycles.
SignalThe tech industry is stuck in a destructive boom-bust hiring cycle — companies massively overhired during ZIRP and COVID, then slashed headcount, and now struggle to figure out the right team size in an AI-augmented world.
Why NowThe simultaneous collision of post-ZIRP correction, AI-driven productivity gains, and the worst tech employment contraction in a generation means every CTO is asking 'how many engineers do I actually need' for the first time.
MarketCTOs and VP Engs at mid-to-large tech companies; $5B+ TAM in workforce analytics/planning; competitors like Visier and Orgvue don't address the AI productivity variable at all.
MoatProprietary dataset combining engineering output metrics with labor market data creates a compounding data advantage that improves predictions over time.
Tech employment now significantly worse than the 2008 or 2020 recessionsView discussion ↗ · Article ↗ · 1,029 pts · March 6, 2026
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