David George on AI-native companies running 5-10x revenue per employee vs. traditional software benchmarks

Summary

AI-native application companies in the $100M to $1B revenue range are generating $500K to $5M in revenue per employee, compared to the traditional software benchmark of roughly $400K per employee. That 5x to 10x gap, observed across a portfolio of companies reviewed by David George, a16z's growth practice lead, points to a structurally different operating model, not just incremental efficiency gains.

George attributes the divergence to two reinforcing forces. First, AI tooling is compressing headcount needs dramatically. Second, the post-COVID founder cohort is running companies with materially more intensity, a cultural shift he describes as a 'vibe shift' that accelerated over the past five to six years. In his view, that combination of technology and founder psychology is why these companies are scaling faster than prior generations.

On staying private, George frames it as straightforwardly rational. The regulatory and cost burden of being public has risen, the private market is liquid enough to provide meaningful capital, and founders trade a slightly higher cost of capital for relief from daily stock price volatility. a16z's growth fund, raised at a larger size to reflect the current opportunity, is now structured to write checks up to $1 billion directly from the fund into a single company.

The broader strategic thesis remains unchanged over the seven years since the growth practice launched. George's framing is consistent: the best investments are companies that can be larger than consensus expects. The new fund size is calibrated to that conviction, not a change in direction.