Thanks for joining us, Jennifer, and congratulations on becoming a unicorn! Tell us what Scribe does.
We’re building the context layer for how work is done in an enterprise.
We capture workflow data on what people are actually doing and use it to help companies understand how work happens, deliver that context where it’s needed, and improve it through optimization, automation, or AI.
What was the moment when you saw the problem that Scribe would eventually aim to solve?
I did a lot of operations center work. You go into some of these op centers, and some are quite well documented, but what's written down does not match what people are doing, particularly what the best people are doing.
Most of corporate America isn’t even as documented and regimented as an operations center. Companies run on institutional know-how: the knowledge of how they create value lives in people's heads.
I think of the fundamental equation of a company as capital, people, and processes. There are systems of record for capital and for people, but nothing that truly captures workflows.
That’s a big problem. It became even more obvious when companies went remote, and now with AI and digital workers, it’s an even bigger issue. We rely on low-bandwidth ways of transferring knowledge, and that no longer works.
What part of your training helped you most in building and leading Scribe?
Being a rapid learning machine. I joined the Firm at 20, and it shaped how I think about problem-solving and teamwork.
You take big, ambiguous problems and break them into small, testable units. You use a hypothesis-driven approach and validate with data. That’s exactly how we run Scribe. It’s one of our core values.
We’re also very first-principles driven. Since we’re solving something new, we can’t rely only on past heuristics. We have to deeply understand the problem, break it down, iterate quickly, and adapt.
What convinced you that this was a company-scale opportunity?
When I interviewed 1,200 executives, a clear pattern emerged: no one really understood how their company runs at a detailed level.
They could see inputs like salaries and tools, and outputs (results), but not the workflows in between. Teams doing the same work had very different outcomes, and leaders couldn’t explain why.
They were trying to solve this manually by shadowing employees, writing documentation, and running workshops. I realized software could solve this by automatically capturing “digital exhaust”: observing how work happens and using that data to improve it.
Why did this problem matter enough for you to pursue it?
I’m deeply bothered by inefficiency. I love thinking about the efficient allocation of resources.
The most valuable resource is human potential. Yet, in corporate environments, people spend their time inefficiently.
I want people working on their highest-value contributions, using their unique strengths. Technology can remove distractions and reallocate effort toward meaningful work.
Why did you focus on winning with end users first?
I believe people want to do a good job and improve. I wanted to build something they choose to use, not something forced on them.
Much enterprise software succeeds because people are required to use it. That’s a low bar. I wanted Scribe to deliver real value to individuals, which then naturally scales to organizational value.
How has your ambition evolved as Scribe has grown?
Our ambition hasn’t changed. We want to make knowledge work actually work.
Now, with AI agents, workflow context is even more critical. Without context, AI is just guessing.
We’re helping companies build the structured understanding of workflows that AI needs to operate effectively, both to identify where AI should be used and to guide it.
What advice would you give people figuring out what to build?
Ask yourself: What do I want?
I used to ask normative questions: what I should do, what do others expect? But the real question is what you genuinely care about.
Building a company is hard. It has to come from a deeper purpose, not external expectations.
Has anything you’ve read or experienced recently stayed with you?
I rarely consume fiction, but I recently read The Invisible Life of Addie LaRue.
It’s about a woman who is forgotten by everyone she meets, but her ideas endure. It highlights the power of ideas to shape the world, even when the individual isn’t remembered.
That resonates with building a company: an idea that mobilizes people around a shared belief.
What is your favorite place to get lost?
It used to be New York City because of its endless novelty. Now, it’s nature, walking in the woods near my home. It’s quieter and more inspiring.
What do you never leave home without?
I actually do leave home without my phone sometimes. If I don’t need to be reachable, I prefer being fully present.
What is your next bold, brilliant move?
Making AI agents actually work in enterprises.
There’s a big gap between what individuals can do with AI personally and what companies can do. That gap is largely due to missing workflow context, and that’s what we’re solving.
Finally, what did it feel like to become a unicorn?
It doesn’t feel different. It’s just a milestone, a means to an end. What changes more is how others treat you, not how you see your mission.
