For trillion-dollar companies, talent isn't expensive but missed opportunities are!
Estimated Reading Time: 4 minutes
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.
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 billionin 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.
To better understand just how valuable these engineers have become, let’s look at some of the standout examples:
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:$8Bcommitted.
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…
Mira Murati@miramurati
Thinking Machines Lab exists to empower humanity through advancing collaborative general intelligence.
We're building multimodal AI that works with how you naturally interact with the world - through conversation, through sight, through the messy way we collaborate. We're
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.
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.
https://docs.google.com/spreadsheets/d/1kUC1LDJXLUDMuW3IuQ08764ao2pRuoRpuQvCBopwCw8/edit?usp=sharing
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.
When removing the top three companies from the dataset, some clear trends emerge about the labs these founders came from.
Other sources(e.g., Apple, universities, smaller startups): $1.3 billion
This data suggests thatOpenAI alumni are more efficient in generating value per dollar raised, whileDeepMind alumni tend to secure larger funding rounds, especially in foundational model and AI infrastructure projects.
Meta has reportedly offered up to$200 millionto attract elite AI engineers. While this might seem excessive, it's actually a tiny fraction of Meta's overall value—around0.0067%of its $1.5 trillion market cap.
$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.
There are a few key reasons why top-tier AI engineers are commanding such massive compensation packages:
They have a proven track record.These individuals have been behind systems like ChatGPT, AlphaFold, and LLaMA.
They attract capital quickly.Many investors are willing to commit $100 million or more just based on who is on the founding team.
They save time.With their experience, these engineers know how to avoid costly mistakes and move faster to launch.
They define future products.From agents to copilots to next-generation reasoning models, they’re driving what’s coming next.
In most industries, talent scales output. In AI, top talent can scale entire ecosystems. One exceptional founder or engineer can:
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 becomingstandard
$100 million pay packages arestrategic, not excessive
Labs like OpenAI, DeepMind, and Meta are evolving into launchpads for billion-dollar founders
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 engineersarethe 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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