Blueprint of a Future Company.
I analyzed the Lean AI Native Leaderboard, but I did some additional calculations and removed the non-AI native Telegram from the dataset. I’ve been in Silicon Valley tech since DotCom and want to provide a broader perspective comparing prior tech waves to this current AI Wave.
This AI wave is very different than the prior waves.
Business Overview:
Small teams, likely in SF bay area or NY.
- Location: Based in SF Bay Area (51% of dataset), distant second is NY 7/35 (or 20%), and a small cluster from Paris, 3/35 (8%).
- Employee Size: 19 (but likely hundreds to thousands of AI Agents).
- Company Age: 4 years (founded in 2021 on average).
Comment: That’s very lean, usually the founding team is 2 people, then they hire 2-3 engineers often after a year, so imagine 5 employees after 12 months. Then on average just hiring 5 people per year for 3 more years to a total 19.
Funding:
Yes, there are VC opportunities, but prob for early-stage investors
- VC Funded: 66% (23 out of 35).
- Average Funding Amount: $32M.
Comment: I’m seeing pre-seed AI startups raise $1-2M, and Seed raising $3-5M, then Series A raising about $15-25M. That generally tracks, despite the data from this leaderboard being the top 1% of startups. For the 66% that took VCs funding, there are strong expectations of industry-and-global growth, not staying as a lifestyle company.
Revenue & Profitability
- Profitable: 74% are profitable (26 out of 35).
Comment: I remember how many DotCom, Web2 and Sharing Economy companies were not profitable for many years, their goal was to get market share adoption vs turning on revenue engines –seeing some changes in this AI market.
Average Annual Revenue:
- $37M Average Annual Revenue (All companies on list).
- $24M Average Annual revenue (removing Midjourney, the $500M ARR outlier).
Average Revenue Per Employee (RPE)
- $1.6M RPE (including Midjourney).
- $1.2M RPE (removing Midjourney, the $500M ARR outlier).
Comment: For comparison: Average TradSaaS company is $200k RPE and top decile TradSaaS are closer to $1M RPE, and many of them took 25 years to get there.
My take: Early-stage VC, former Industry Analyst
AI-first startups are rewriting the rules of company building, by embedding AI agents from day one, they’re achieving 10X results with a fraction of the team.
In prior tech waves, companies scaled by throwing humans at the problem:
- DotCom wave: Hire human employees.
- Social Media wave: Hire human employees.
- Sharing economy wave: Use independent contractors.
- AI wave (today): Use AI agents
Now, they scale with AI intelligence. In this new blueprint, 10 people and 1,000 agents can outperform 10,000 employees. This is the rise of the AI-first, hyper-lean company.
