The 10X Founder

Everyone loves the concept of the 10x developer. A 10x developer is a software engineer who is so wildly talented and productive that they produce the output of ten average engineers.

When I heard a provocative statement by Sam Altman of OpenAI at a recent JP Morgan conference, I thought of a new breed we will be talking about in the coming years: the 10x founder.

The 10x Founder vs. the Solo Founder

Sam stated that someday soon, a solo founder will reach a billion-dollar valuation without hiring a single employee. This one-person company would instead be powered by AI and “employ” dozens of AI agents to do the work.

I am not sure about the idea of the solo founder as a superhero who can achieve something of that scale. I have been a founder and worked with founders for three decades and there is something too special about the way a team comes together to build off each other, create a winning culture, and build a high-performing organization. Maybe I'm just old-fashioned, but I like working with humans and I believe humans working with other aligned and talented humans to accomplish a shared mission is pretty magical.

But I am sure that we are seeing the emergence of a new type of founder that I will call the 10x founder. 10x founders are today employing AI to do the work of 10 average founders. And they are instrumenting their organization to do the same. One engineer is using code development tools to become a 10x engineer. One sales rep is using some of the dozens of available AI tools for sales and marketing to become a 10x sales rep. One customer success person is doing the same.

Scaling Without Growing

When I was a founder, I was obsessed with hiring. As soon as we secured more capital, we hired more people. If we closed another partner, we hired. IF we had a new product idea, we hired. I've been an executive at successful B2B and B2C startups that scaled. I've been an investor in board member in hundreds of startups. In all cases, when things started to work and we hit product-market fit, we scaled rapidly because we hired rapidly. And we hired rapidly because we scaled rapidly.

That era is over.

Going forward, founders are going to be less obsessed with hiring and more obsessed with deploying AI to enhance their organization's ability to scale without growing.

Adobe executive Scott Belsky coined that phrase and I like it. He recently wrote, "We are entering an era of scaling without growing...Every function of an organization will be refactored in ways that allow small teams to scale their reach and ambition without growing headcount proportionately."

As I invest in AI-forward startups and teach my Harvard Business School students how to use AI in their startups, I am more convinced that these modern tools allow faster and more effective achievement of product-market fit and scaling. The 10x founders I work with use timeless techniques to achieve this outcome while deploying timely tools.

AI-Forward Organizations

Designing and building an organization to operate optimally during this emerging Age of AI isn't easy. It takes intentionality and a persistent commitment to re-invent communication and organizational processes. It requires an experimentation mindset to bring in new tools, rapidly adopt those that truly make an impact, discard those that don't, and change how startups execute.

In my upcoming book, The Experimentation Machine: Finding Product-Market Fit in the Age of AI, I walk through five core building blocks that align with critical phases of the startup journey. Each of these five is in the midst of radical transformation through AI: Ideation, Customer Discovery, Customer Value Prop Validation, Go To Market Expansion, and Profit Formula Construction. Look at any one of them closely and you see dozens of tiny startups (as well as several big companies) building AI tools to help these founding teams become more efficient and effective. A friend who is a founder of a public software company in the sales and marketing space tells me he's tracking 44 companies alone that are building AI-powered sales development reps (SDRs).

Not all these tools are going to survive, naturally. But when the dust settles, some combination of big companies and small companies are going to be providing an extraordinary suite of AI tools to enhance productivity in every nook and cranny of an organization. Lower R&D costs, Sales & Marketing costs, and G&A costs will eventually translate into higher profits.

Financial Implications

The implications of the 10x founder are vast. As a venture capitalist, I can't help but think of the financial implications. Software companies will become more profitable. And require less capital. Some will argue that the headwinds regarding competition and lack of competitive moat in an AI age outweigh the tailwinds of operational efficiency. Those headwinds are real, but I'm not sure they're strong enough to slow down this productivity boom.

For a glimpse into the future, we can examine the most AI-forward organizations on the planet. The companies are providers of the leading AI tools and thus experts in incorporating these tools to make their organizations more efficient (i.e., "eating their own dog food").

If we look at the revenue per employee of three of these AI leaders-- Alphabet, Microsoft, and Nvidia -- we see dramatic gains in the last four years.

I would be shocked if we didn't see this positive effect on productivity ripple through other large organizations (finally defying the confounding Productivity Paradox of IT). Klarna recently reported tremendous efficiency gains in using AI for customer service, with an AI assistant handling two-thirds of their chats. ServiceNow has mandated that every department provide an AI roadmap and reports massive gains. The company's CEO is obsessed with using AI for process automation. He recently declared, "Any process that exists in the enterprise today will be reengineered, or engineered, depending on how messy the process is with generative AI. So every workflow in every enterprise will be rethought."

No matter how innovative and determined, big companies are slower to adopt new processes than small companies. Culture and organizations are too entrenched and large groups of humans adapt slowly. Startups, on the other hand, get to begin with a blank sheet of paper. 10x founders are going to take that blank sheet of paper and make magic.

How are you using AI to build your startup? 🤖 I write about building startups in the age of AI. Subscribe to my newsletter for more: https://buff.ly/3viAAGH

Jeff Bussgang

Jeffrey J. Bussgang is a Senior Lecturer in the Entrepreneurial Management Unit at the Harvard Business School as well as Co-Founder and General Partner at Flybridge Capital Partners, an early-stage venture capital firm with offices in Boston and New York City and over $1 billion under management across six seed funds and nine network funds. “Unicorn” portfolio companies include BitSight, Bowery, Chief, FalconX, Habi, MadeiraMadeira, and MongoDB. He studies lean startups as well as strategy and management challenges for founders.

Jeff has authored two books: one for startup joiners, Entering StartUpLand, and one on venture capital and entrepreneurship, Mastering the VC Game, to provide entrepreneurs an insider’s guide to financing and company-building. Both books have been hailed by the Wall Street Journal, BusinessWeek, TechCrunch and The Financial Times as essential guides for entrepreneurs.

Jeff is an active community member, serving as board chair and co-founder of Hack.Diversity, a talent development program for Black and LatinX technologists, as well as a board member at educational non-profit Facing History and Ourselves and co-founder and board chair of LEADS, an economic and leadership development program for diverse Gateway City leaders.

Jeff holds a BA in Computer Science from Harvard University where he graduated magna cum laude and an MBA from Harvard Business School where he was a Baker Scholar and a Ford Scholar.

https://bussgang.medium.com/
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