Why 10x Joiners are thriving in the Age of AI

This post is based on my new book, The Experimentation Machine: Finding Product-Market Fit in the Age of AI. Buy the book direct from me, or order on Amazon.

It’s graduation season and many students are looking for their first jobs. There are also millions of professionals in the workforce today who are questioning their roles in this rapidly changing Age of AI.

As I say often, AI will not replace your job, but someone using AI will. So how do you become that person who learns to leverage AI to multiply their output and make themselves indispensable?

Let me introduce you to The 10x Joiner:

The 10x Joiner: Supercharged Employees

There used to be a rule at Flybridge that any AI startup we invested in needed to have a co-founder with a PhD in machine learning.

In 2012, I wrote a cheeky blog post with a nod to the classic movie The Graduate titled, “Hey Graduates: Forget Plastics–It’s All About Machine Learning,” encouraging young people to study this important field in the era of Big Data.

We’ve scrapped that requirement today because a PhD is no longer needed to build an AI-forward company. The technical playing field is being leveled for all but the most bleeding-edge companies. There are trillions of dollars up for grabs for fast-moving startups that can “AI-ify” industries with today’s existing technology, no doctorates needed. This generalizing of startup teams will only continue as AI technology matures. 

It has never been more valuable to be a flexible, fast-moving generalist who can quickly learn new tools, adapt to changing circumstances, and connect dots across disciplines. The folks that can do all this and are AI-native are what I’ll call 10x Joiners. 

Like the 10x Founder, the 10x Joiner can get ten times more done than a traditional startup employee, across a wider range of job functions:

• The 10x salesperson can do business development, nurture deals, and systemize the sales process better than a team of ten typical salespeople. 

• The 10x marketer can design a go-to-market strategy while also deftly managing social, SEO, and PR with a team of AI agents.

• The 10x chief of staff can use specialized legal AI to write contracts and handle HR.

• The 10x (or should we say 100x) developer can turn a six-month project into a six-day project.

We already know that AI agents will end up performing 80 percent or more of our day-to-day work. A key skill in tomorrow’s startups will be knowing how to orchestrate hundreds, even thousands of agents to work in collaboration. This skill applies well beyond engineering. Tomorrow’s best marketers, financial analysts, salespeople, and customer support reps will all know how to coordinate with AI agents to get more done. 

So as a founder, how do you screen for a 10x Joiner in the hiring process? Ask candidates to demonstrate how they are using AI copilots, and increasingly agents, in their work and lives today. Has using AI become a habit? Is it their first step in every new project? Has it become an extension of their working selves? 

How to Interview as a 10x Joiner

I recently had an interesting discussion with one of my students on the cusp of graduation. We imagined a job candidate who not just displayed high proficiency with AI, but had built a team of AI agents that she brought to the job. She would be an individual contributor and a manager of AI agents that expanded her capabilities, giving her a better chance of being a $10 million employee. I believe this could be the model for 10x Joiners moving forward. 

Wharton professor Ethan Mollick, author of Co-Intelligence: Living and Working with AI, made a similar point in a recent newsletter:

“Given that AIs perform more like people than software (even though they are software), they are often best managed as additional team members, rather than external IT solutions imposed by management.” 

10x Joiners don’t just use AI—they build and manage hyper-efficient AI teams. Which begs the question, why hire humans at all?  

Simply put, startups still need human judgment. I love the book, Zen and the Art of Motorcycle Maintenance by Robert Pirsig. It’s a novel about the philosophical exploration into the meaning of quality versus commercialism. One of my favorite lines is about the limitations of the scientific method: 

“You need some ideas, some hypotheses. Traditional scientific method, unfortunately, has never quite gotten around to say exactly where to pick up more of these hypotheses . . . Creativity, originality, inventiveness, intuition, imagination . . . are completely outside its domain.”

AI is dramatically expanding our capacity to run experiments and build products, but startups still face time and resource limitations, and thus need to uncover the right answers quickly. We still need humans with creative instincts and good judgment to generate good hypotheses in the first place. Of course, these traits must be balanced with the basic competencies required for the role.

But in a world where AI can increasingly handle specialized tasks, bet on the humans who can do what AI cannot: innovate, create, adapt, and thrive in ambiguity.

Thanks for reading. Want to learn more about using AI to supercharge your company and skills? Pick up my new book: