$1 Billion Per Engineer: Why It’s Rational, Not Radical

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The competition for top AI talent is intensifying, with companies like Meta reportedly offering compensation packages over $100 million to recruit engineers from AI powerhouses like OpenAI, Anthropic, and DeepMind. At first glance, these offers might sound outrageous. How can any company justify spending that much on one person?

In today’s AI landscape, those numbers are not just reasonable—they might even be considered a smart investment.

The Talent Driving Massive Valuations

Over the past three years, former employees of elite AI labs—including OpenAI, DeepMind, Meta AI, and Google Brain—have gone on to launch more than 45 startups. These companies have collectively raised over $26 billion in funding and are now worth a total of around $224 billion.

On average, each of the 81 known founders has been responsible for creating $2.77 billion in enterprise value. Even when excluding the top three companies (xAI, Safe Superintelligence, and Thinking Machines Lab), the average still sits at $1.45 billion per founder. This level of impact has often come before products have shipped or revenue has been generated.

These figures aren’t inflated by large teams either. Many of these companies were started by just two or three technical founders, leveraging their deep expertise and reputations to raise significant capital early.

The Founders Behind the Numbers

To better understand just how valuable these engineers have become, let’s look at some of the standout examples:

🔬 OpenAI Alumni

• Anthropic: Dario and Daniela Amodei (ex-OpenAI) co-founded this frontier AI company. Valuation: $15B+, raised: $8B+.

• Safe Superintelligence: Ilya Sutskever, Daniel Gross, and Daniel Levy (OpenAI and Apple AI alumni). Valuation: $32B, raised: $8B committed.

• Thinking Machines Lab: Mira Murati (ex-CTO, OpenAI). Valuation: $10B, raised: $2B.

• Perplexity AI: Aravind Srinivas (ex-OpenAI). Valuation: $1B+, raised: $100M+.

• Adept AI: David Luan (former VP of Engineering at OpenAI). Valuation: $1B+, raised: $415M.

Mira just announced their $2B seed round…

🧠 DeepMind Alumni

• Inflection AI: Mustafa Suleyman and Karén Simonyan (ex-DeepMind). Valuation: $4B, raised: $1.3B+.

• Mistral AI: Arthur Mensch (ex-DeepMind). Valuation: $6B, raised: $500M+.

• Harvey: Gabriel Pereyra (ex-DeepMind). Valuation: $500M+, raised: $100M+.

• Daedalus: Jonas Schneider (ex-OpenAI Robotics; crossover with DeepMind talent). Valuation: $200M, raised: $34M.

🧬 Meta/FAIR Alumni

• Cohere: Aidan Gomez and Nick Frosst (ex-Google Brain/FAIR). Valuation: $2.2B, raised: $445M.

• EvolutionaryScale: Alexander Rives (ex-Meta AI). Valuation: ~$200M, raised: $142M.

• Nabla: Alexandre LeBrun and Martin Raison (ex-FAIR). Valuation: $800M, raised: $43M.

Check out all 40+ here

While OpenAI and DeepMind are driving the lion’s share of valuation and fundraising, Meta alumni are emerging with promising biotech and foundational model startups.

Which Labs Are Producing the Most Valuable Founders?

When removing the top three companies from the dataset, some clear trends emerge about the labs these founders came from.

Total Valuation (excluding top 3):

• OpenAI alumni: $23.6 billion

• DeepMind alumni: $18.2 billion

• Meta/FAIR alumni: $3.4 billion

• Other sources (e.g., Apple, universities, smaller startups): $1.3 billion

Total Funding Raised (excluding top 3):

• DeepMind alumni: $3.89 billion

• OpenAI alumni: $1.93 billion

• Meta/FAIR alumni: $420 million

• Other: $320 million

This data suggests that OpenAI alumni are more efficient in generating value per dollar raised, while DeepMind alumni tend to secure larger funding rounds, especially in foundational model and AI infrastructure projects.

Why Meta's $100M Offers Actually Make Sense

Meta has reportedly offered up to $200 million to attract elite AI engineers. While this might seem excessive, it's actually a tiny fraction of Meta's overall value—around 0.0067% of its $1.5 trillion market cap.

To offer perspective:

• $100 million = 0.13% of xAI’s valuation

• $100 million = 0.31% of Safe Superintelligence

• $100 million = 1.00% of Thinking Machines Lab

In other words, if an engineer can deliver breakthroughs or leadership that moves the needle even slightly for a trillion-dollar company, the return on investment is massive.

In AI, the value created by a single individual can scale exponentially. These engineers have built and deployed large-scale models, led innovative research teams, and architected the platforms we rely on today.

What Makes These Engineers So Valuable?

There are a few key reasons why top-tier AI engineers are commanding such massive compensation packages:

1. They have a proven track record. These individuals have been behind systems like ChatGPT, AlphaFold, and LLaMA.

2. They attract capital quickly. Many investors are willing to commit $100 million or more just based on who is on the founding team.

3. They save time. With their experience, these engineers know how to avoid costly mistakes and move faster to launch.

4. They define future products. From agents to copilots to next-generation reasoning models, they’re driving what’s coming next.

When Talent Is This Rare, Economics Shift

In most industries, talent scales output. In AI, top talent can scale entire ecosystems. One exceptional founder or engineer can:

• Build an innovative product

• Attract nine-figure capital rounds

• Recruit world-class technical teams

This is why we’re entering a new era where:

• $1 billion in value per engineer is becoming standard

• $100 million pay packages are strategic, not excessive

• Labs like OpenAI, DeepMind, and Meta are evolving into launchpads for billion-dollar founders

Welcome to the New Talent Economy

The AI boom isn’t just about new models and products—it’s about rethinking how we value the people building them. Whether it’s OpenAI alumni behind Perplexity or DeepMind veterans at Inflection and Mistral, the blueprint is clear:

• Elite engineers are the intellectual property

• Their name alone can unlock a $100M+ round

• Their experience leads to the next breakout startup

So if Meta or any other big tech company is willing to spend $100M or more to bring one of these individuals in-house, they’re not overpaying. They’re playing the long game—and it just might pay off big.

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