The AI The AI Talent War
Signal, Substance, and What You Should Really Pay Attention To
The news cycle is fizzing again. Meta’s Superintelligence Labs has reportedly poached multiple top-tier AI researchers from OpenAI and Google DeepMind, dangling packages that could hit $100 million+. Naturally, the media is framing this as a high-stakes chess match, one where personnel moves are interpreted as existential wins or losses. But beyond the headlines, and a more nuanced picture emerges.
In Liberal Democracies, where people can move between roles freely and without financial ruin, job mobility acts as a form of economic signalling. When a highly visible AI researcher switches employers, it:
Confers credibility on the company they’re joining.
It raises eyebrows at the company they’re leaving.
It influences investor sentiment, recruitment pipelines, and public narrative.
It’s not just about compensation either - it’s a public benchmark of perceived momentum and relevance. For trillion-dollar firms, these movements are splashy but mostly symbolic. For the rest of us, a single departure or hire can be a material event. When someone leaves, the fear is that context (and corporate knowledge) walks out the door, or that delivery timelines will wobble. Maybe morale will take a hit.
The likelihood, however, is that you’re operating without the buffer of deep benches, and without the resources to throw seven-figure “stay packages” at strategic hires. So while the talent war plays out in Silicon Valley headlines, it has real-world consequences elsewhere; in wage inflation, skewed candidate expectations, and a distorted sense of what success looks like.
Not every hire needs to go in a press release. Not every resignation is a reputational blow. In fact, the best firms win by quietly building mission clarity, technical autonomy and cultural stickiness. People want to work on things that matter. They want the freedom to build without bureaucracy, with a shared belief that the team and product matter more than any one individual.
What we’re seeing is that AI talent expectations are up 30–50%. Engineers at startups are benchmarking themselves against FAANG+ labs, irrespective of the fact that their next job might be their first in “true” machine learning and AI, in a different geographical location. Some investors are chasing "celebrity hires" instead of credible execution, as is evident from the recent headlines.
But as with all bubbles, signal decays fast when it isn't backed by substance. People have always moved jobs. They always will. No-one is indispensable. No-one is irreplaceable. Even the most hyped departure eventually fades into the rear-view mirror.The real challenge isn’t preventing movement. It’s building teams, culture and processes strong enough to absorb it without flinching.
And only then you can start worrying about the technology.