Opinion
The road to $100M ARR goes through “revenue per engineer”
"In the race to $100M ARR, the leanest runners will lead - and redefine what a 'team' can achieve," writes Liad Shnell, CTO at Viber.
CTOs everywhere are doubling down on AI adoption, but the landscape is getting crowded fast. The surge of new tools has many leaders entering full-blown FOMO mode, unsure which solution will still matter next quarter. Measuring the payoff is harder still. Some teams track active coding days, others obsess over AI acceptance rates, and a few audit what percentage of production code was drafted by a model. The productivity lift is clear - but the industry hasn’t landed on how to measure it consistently.
There was a time when headcount was the ultimate status symbol - add more engineers, lease another floor, squeeze in another row of desks, and revenue would surely follow.
Growth equaled bodies. Or so we thought.
Fast-forward to 2025, and the prize isn’t the stopwatch - it’s the scale. A single LLM-powered squad can ship what used to take entire departments. Revenue per engineer (RPE) has emerged as the real bragging right, forcing boards to ask not just how fast you grow, but how lean you do it.
Lean SaaS contenders, small enough to fit in one elevator, are now racing toward the $100M ARR milestone. Capacity no longer scales linearly with headcount. That line broke the moment generative AI started writing tests, drafting docs, and spinning up infrastructure on voice command.
Walk any modern engineering floor and the shift is palpable. Designers generate on-brand visuals in minutes through generative plugins. Analysts interrogate live traffic in plain English. QA teams watch as entire test environments are conjured before their coffee cools. Product managers still own the “why” and the “what,” but developers - now backed by copilots - deliver the “how” at warp speed. Engineers operate as self-contained product pods. Queues vanish. Hand-offs evaporate. RPE climbs.
Blank-slate projects amplify the effect. Hand an AI-native team a paragraph of product vision, and by lunch, working code, infrastructure, and monitoring are already in motion. Giants that once allocated a year for rewrites are now carving monoliths into greenfield spinouts - self-funded, cloud-native, fully compliant, AI-instrumented. They’re done refactoring. They’re compounding.
And here’s the catch: the economics shift with them. Fewer engineers can now generate the same - or better - output, trimming burn and boosting velocity. Releases ship faster, churn drops, ARR grows. The biggest players have noticed. They’re reorganizing into P&L-driven units to reclaim startup speed without giving up scale. Even Wall Street is recalibrating: when lean teams can sprint to nine-figure revenue, the IPO clock stops ticking. The new-issue pipeline thins.
This shift doesn’t just change tooling - it changes how CTOs need to think. For a decade, engineering leaders were trained to optimize for velocity, quality, and stability. Today, they also need to consider profitability per engineer. RPE isn’t just a finance metric - it’s a strategic lens. It forces CTOs to reconcile technical roadmaps with business outcomes. The bar has moved from shipping more to achieving more with less.
So where does that leave the CTO?
First, embed autonomy into every workflow so AI feels like just another teammate. Then, connect the stack - one LLM is handy, but one that touches every system is a multiplier. Make safety the default: red-team every release, bake compliance into your pipeline, and design for auditability from day one.
And above all, watch the one metric that tells the whole story.
If your revenue per engineer isn’t climbing double digits year over year, it’s time to revisit your AI strategy. In the race to $100M ARR, the leanest runners will lead - and redefine what a “team” can achieve.
Liad Shnell is the CTO at Viber.
