You focus on investing in ‘the future of work’ startups at IOVC. Could you explain how you understand this concept?
At IOVC, we are investing in startups driving 3 key waves of change that are bridging us from the economy of today to the economy of tomorrow: workflow automation, workforce diversification, and workplace hybridization.
When it comes to workflow automation (what work is done and how it’s done), we are already seeing the length of tasks that AI can automate growing exponentially, doubling every 7 months for the past 5 years. At this pace, within 3–5 years, startups building with AI will be automating tasks that take humans days to weeks, which will free people to focus on more meaningful activities like building relationships. For example, we have invested in startups like Imbue (unicorn backed by Nvidia), which helps humans improve AI-generated code, and Convex (acquired by ServiceTitan), which automatically identifies upsell opportunities for commercial contractors.
When it comes to workforce diversification (who does the work and why they do the work), we see startups leveraging technology to enable older and younger employees, as well as people from nontraditional educational backgrounds, to meaningfully contribute to the economy through their skills (rather than be restricted by their age, lack of experience, or lack of relevant degrees). For example, we have invested in startups like TalkIQ (acquired by DialPad), which provides real-time feedback for customer service and sales agents to help them excel in their roles, and Marble (acquired by Caterpillar), which leverages robotics to enable a broader workforce than previously possible to contribute to construction and mining operations.
When it comes to workplace hybridization (when and where work happens), we see the biggest impact coming from the ability to work in mixed reality environments, where we can merge data from the digital world with observations from the real-world to enable 24/7 monitoring of critical business functions. For example, we have invested in startups like UpKeep (series B), which leverages real-time mobile data to help maintenance and reliability teams run factories more efficiently, and Laudable (acquired by Zapier), which automatically generates genuine customer testimonials from customer calls.
These three key waves of change guide our investments and thinking around the future of work.
What mindset shifts must leaders adopt to stay relevant amid automation and rapid change? What challenges do they face in doing so?
One crucial mindset shift is recognizing how quickly jobs evolve. Data shows that 76% of jobs that will be available in 2030 don’t even exist today, impacting not only entry-level jobs but also the C-suite.
In fact, we are seeing an increasing number of “fractional founders” who are rapidly outgrowing their current roles—these are employees who identify painful problems in their full-time jobs, proactively build solutions part-time, and iterate quickly until they identify the best solution that gains traction. Leaders must embrace and empower fractional founders within their own workplaces because these individuals deeply understand the company’s problems, and if supported properly, can turn their part-time projects into the organization’s next biggest opportunities. Fractional founders can even become the organization’s future leaders. However, if unsupported by their companies’ leaders, fractional founders have no choice but to take their part-time projects outside of the organization to build externally as independent startups.
Our quantitative research shows that six out of seven trillion-dollar U.S. companies were started by fractional founders, and 25% of Fortune 500 companies were started fractionally. Leaders who nurture these fractional founders by creating new roles and providing resources will future-proof their organizations. In contrast, companies who see fractional founders as distracted employees risk falling behind. Leaders need a future-focused lens to encourage employees to evolve from being problem solvers (focusing on what to do in the present) to being problem explorers (focusing on where to be in the future).
Challenges include balancing immediate business metrics and shareholder expectations with the need to innovate for the future. Companies often lack the luxury to think many steps ahead. Internally, providing low-commitment and low-stakes opportunities for experimentation—like “10-minute workshops” where employees rapidly prototype ideas—can foster innovation. Externally, partnerships with universities and nonprofits can bring specialized expertise to solve pressing problems, as seen in collaborations like Pinterest’s visual search built with UC Berkeley. On a macro level, companies face complex questions around policies and ethics, especially relating to AI, so leaders must choose focused areas to engage deeply to avoid feeling overwhelmed.
In that respect, do you think we will witness a trend of specialization of many companies?
It depends on seniority. I expect junior roles to become more specialized, focusing on specific problems or functions. On the other hand, I expect senior leadership to require more generalized skills to manage these specialists and increasingly AI agents. As AI increasingly automates tasks, humans will increasingly end up needing to manage AI teammates, leading to managerial skills becoming more important even at the junior levels.
… AI teammates?
Recent research highlights the importance of viewing AI as a teammate, not just a tool. Data already suggests that those who manage AI well—applying the same skills used to manage humans—are already more productive and creative than those who merely rely on humans. Thus, while junior roles will become more specialized, the definition of leadership will expand to include not just the management of people but also the oversight of human-AI collaboration.
This trend is already unfolding before our eyes. Anyone who’s ever asked AI a question (called a “prompt”) is already managing AI without realizing it. “Prompt engineering” is already a highly coveted skill in tech circles. Effective AI management will become mainstream before we know it—at which point we will all wonder how we ever lived without it. I have seen this play out through my role as the Chair of the Board of Directors at Decode, the largest founder community across UC Berkeley and Stanford, where more than half of startups in the community have 95% AI-generated codebases.
Can you share an example of a fractional founder?
A fractional founder is an entrepreneur who is transforming their part-time project into a full-time startup.
One of my former UC Berkeley students, Jay Dang, identified a common pain point while still in school: People weren’t getting the answers they wanted from AI because they didn’t know what to type into the AI chat window (AKA they didn’t know how to “prompt” AI tools). He developed a platform allowing users to share and rate effective AI prompts across categories. This part-time project called FlowGPT grew rapidly, reaching about eight million monthly active users before he left school to focus on building the venture full-time. Over time, FlowGPT evolved to focus on “beyond camera content” (content that’s not filmed by a camera), which AI is particularly well-suited to create. He is now closing his Series A round of venture funding.
Jay is a great example of a fractional founder: he reflected on his personal pain point from his full-time role as a student, built a prototype part-time, iterated quickly, and leveraged technology efficiently. His work has not only helped many users overcome the “blank page” problem with AI, but also illustrated how fractional founders can innovate early and successfully.
Did IOVC coin the term “fractional founders”?
Yes, we developed the term over the past decade of investing in some of the successful startups in Silicon Valley. We noticed that the best founders often began by solving problems part-time before committing themselves full-time. In contrast to the mainstream caricature of the startup founder who wakes up with a spark of inspiration and then starts building 24/7, fractional founders take a more methodical approach: rather than going all-in right away, they come up with hypotheses to test and focus on validating assumptions. Our goal is to avoid the all-too-typical startup pitch that is overconfident and lacking in empirical grounding.
Fractional founders balance thoughtful experimentation with hustle. Because they have good career alternatives, they do not quit jobs cold turkey but instead test ideas extensively before committing themselves full-time. We invest in fractional founders because we have seen time and time again across our portfolio that they are lower risk and have higher odds of success than the average founder.
How does AI impact the rise of fractional founders?
AI enables fractional founders by lowering the barriers to getting started. Jensen Huang, co-founder of NVIDIA, is a classic fractional founder who brainstormed ideas part-time while working full-time. Similarly, Joris Poort, another portfolio founder, was a Boeing engineer who developed an optimization solution part-time before founding Rescale, which now serves Fortune 500 clients across aerospace, automotive, energy, higher education, life sciences, manufacturing and semiconductors.
AI makes it easier to build part-time than ever before, so, the more AI continues to advance, the more fractional founders we will expect to see.
Given all this, what role do you believe will higher education play in the future of work?
I believe higher education will be as crucial as ever. It is not about memorizing facts. It is about learning to learn and learning to build relationships. After all, the value of a strong social network, particularly from a shared alma mater, will not go away anytime soon.
The rising cost of higher education is a concern, though. In response, another portfolio company of ours called Woolf is leveraging AI and technology to increase access to world-class higher education, and to ensure that it is globally recognized and transferable. Woolf offers accreditation software enabling students to piece together accredited degrees from multiple institutions. Woolf’s model not only expands access to quality education, but also enables lifelong learning. Overall, higher education’s future lies in preserving its core value of collaborative learning and social network, while making it more affordable and flexible through technology.
