After scaling to 300 employees created more problems than it solved, Briq's founder now believes headcount is a poor measure of success. He argues that ARR per employee is the true "flex," promoting capital efficiency and focus over a bloated team size.

The era of bloated headcount is over. Market expectations for efficiency have fundamentally changed, driven by AI and a post-2021 correction. The minimum acceptable revenue per employee for a public SaaS company has doubled from ~$200k to a new standard of $400k-$500k.

The operating model for SaaS has inverted post-2021. Previously, growth came at the cost of declining efficiency ('200% headcount to grow 100%'). The new benchmark is to achieve hyper-efficiency at the margin, demanding teams grow revenue at double the rate of their headcount expansion.

Efficiency gains from AI will create a new normal where B2B companies target $1-2 million in revenue per employee. This is a dramatic increase from the previous SaaS benchmark and means startups will operate with significantly smaller teams, exacerbating job displacement and wealth disparity.

A new generation of AI application companies are being run with extreme leanness and efficiency. They are achieving revenue-per-employee figures between $500K and $5M, dwarfing the public software company average of ~$400K and signaling a fundamental shift in scalable operating models.

The burn multiple, a classic SaaS efficiency metric, is losing its reliability. Its underlying assumptions (stable margins, low churn, no CapEx) don't hold for today's fast-growing AI companies, which have variable token costs and massive capital expenditures, potentially hiding major business risks.

The fastest-growing AI companies reach $100M in revenue significantly quicker than their SaaS predecessors. Counterintuitively, this isn't due to aggressive spending but overwhelming product demand, allowing them to spend less on sales and marketing while achieving 2.5x faster growth.

AI-native companies grow so rapidly that their cost to acquire an incremental dollar of ARR is four times lower than traditional SaaS at the $100M scale. This superior burn multiple makes them more attractive to VCs, even with higher operational costs from tokens.

Fueled by massive inbound demand, some AI B2B companies scale to $50M ARR with sales teams of five or fewer. This represents a 20x reduction in sales headcount compared to the traditional SaaS playbook, which would require over 100 reps to achieve the same revenue milestone.