$100M base salary

Hello again my friend,

Reading how Meta (Facebook) is offering AI researches a $100M base salary to work with them instead of OpenAI absolutely blew my mind.

What happened to being happy with one million? One hundred-million-dollars is absurd, right?

They’re calling this a “God Father” offer (and offer you can’t refuse). Surprisingly, some people allegedly did refuse it.

$100M is more than executives at Meta make. Since they’re a public company, you can see the details here. It’s unfathomable that someone gets paid $100M per year as an employee. In some cases, the offers went up to $300M over four years. Three-hundred-million-dollars for four years of being an employee. I’m not sure I can ever really wrap my head around this.

The internet in all its glory has started making AI researcher trading cards like they’re hall of fame baseball players.

Now, the news here isn’t just about the money these people are making. It’s a prompt that pushes us to think about the future of work.

In a world where a 10 or so employees at a massive company make $300M in four years, what does that mean for entry level employees? For context, Lebron’s salary is under $50M. Meta, OpenAI, and the major players in this new technology are saying that the key employees are worth more to their company than Lebron is to the Lakers.

Let’s get into it.

How does a company function when the top 10 AI leaders may make three-billion-dollars in 4 years, while the global average a Meta employee makes is ~$350k-$400k?

Call me extreme, but it probably functions well, and slowly but surely, the total number of employees will go down, and the average salary for everyone who’s left will go up.

Meta’s already announced they’re laying off 5% of their staff. That’ll be around 3,500 people, all while giving out these $100M offers.

And it looks like other companies are following their lead. So far this year, 93,000 or so people in tech have been laid off. This is significantly greater than normal, and you can see the full list here.

Fewer people. More money to each. An extreme fight for those few people that will drive up salaries.

Like most people who hear this, you probably asked “So, how do I become an AI researcher?” Look, if I knew how, I’d be doing it now. That’s not the track I’m on.

Before we start looking at how to become an AI researcher, let’s look at the more pressing issue, staying employed for 5+ more years.

First, a little context.

For the last few years, there have been different groups in relation to AI:

You don’t want to be in the last two groups. That’s the danger-zone.

It’s not like there’s one big day where “it happens” and we all lose our jobs. It’s started small, and has been building momentum like dominos about to knock our careers (and lives) over.

The good news for most is that tech will be impacted first. It already is. That’s the industry that always innovates first, whether with new technology, management practices, or ways of doing business.

So, how do we prepare?

This seems counter-intuitive, but hear me out.

If you’re reading this worried about potentially losing your job in the next few years, whether or not that happens depends on the company. It’s a balancing act.

In Vancouver where I live, for example, some companies reach out asking me for “help with AI,” and it’s an uphill battle, so I have a little personal experience here. Most of these companies have never hired a developer. Many of them keep all their servers in a closet and have a third party come and fix them when there’s an issue. Some hire IT support to keep the computers working. Very few companies outside of tech are really using the tech, or AI, to its full potential.

Sure, some are more prepared for AI than others, but for the most part, they’re years away (we’re talking about industries that are not tech).

At smaller companies (less than 100 people) outside of tech, most people won’t actually lose their jobs because AI displaced them for a while. The companies are just not there yet.

But, the bigger issue is whether these smaller or mid-sized companies that shun tech will survive long enough to begin with. You might think you’re safe.

“Oh, my boss doesn’t even know what AI is, it’s not taking my job from a while.”

I get that. But if you’re boss doesn’t even know what AI is, what’s stopping a startup with 3 young people who use AI from competing (and beating) that business in the first place? It’s fun to think of getting ChatGPT to do half your work, cruise, and collect easy pay-cheques. It’ll be fun for another few years. But if this is your plan, you are in for a rude awakening in my opinion.

That’s why it’s company first. And to be clear, it’s not every job, every career, not everyone is at risk. Just everyone behind a desk working at their computer at least.

The same business owners who ask for “help with AI,” are asking specifically because they don’t want to hire and pay salaries. On the other side, I have people asking me to help them find a new job, or side-gig. Do you see the gap here?

The entire premise of “one job” or “one career” is what’s at risk. Day jobs are disappearing, but the gig-economy is growing 3x faster than the traditional workforce (and Gen Z is a big part of this).

Then we have people making money with social media. Content creators, influencers, the whole “creator economy” is on pace to grow 4x in the next 5 years.

This isn’t guru-talk on “7 streams of income” or “generational wealth,” it’s extremely practical, and becoming more real every day. Worth looking into. For example, ChatGPT tells me (irony intended) that someone working Uber for just 10 hours a week in Vancouver can earn $290 to $430 per week. Sure, it fluctuates, but you get the idea.

I keep coming back to those AI researcher trading cards. We're literally treating these people like rare collectibles - because that's exactly what they've become.

The uncomfortable truth is that in any revolution, there are winners and losers. The AI researchers have won the lottery. The rest of us need to stop buying lottery tickets and start building something that can't be easily replaced.

The math is stark: when 10 people command potentially $4 billion while 93,000 get laid off, we're witnessing the most extreme talent concentration in corporate history. This isn't just about AI researchers getting rich - it's about entire industries restructuring around a handful of irreplaceable people.

The question isn't whether this will affect your career. It's whether you'll be ready when it does. The middle ground is disappearing fast.

Something to think about.

Thanks for reading!

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