I’ve always been fascinated by the idea of collective intelligence—what becomes possible when we can truly harness the wisdom and context held by many individuals, and make it usable at scale. Years ago, I thought the most exciting application of this idea was in self-driving cars. If autonomous vehicles could share their “representations” of the world with each other, we could sidestep the need for costly LiDAR and instead rely on distributed learning through communication.
That bet didn’t pan out. The startup I was part of couldn’t raise funding, and the founders went their separate ways. But the deeper insight stayed with me.
Fast forward to now, I see a parallel in a completely different domain: employee performance management. At its core, it’s still a problem of collective intelligence and representation. Managers want visibility. Employees want privacy. How can we collect reflections about the work experience in a way that keeps personal data private, yet still allows organizations to learn from the patterns and act on them?
That’s the tension Libra was built to solve. And this is Earl’s story.
A Nonlinear Path, A Unique Perspective
My career’s always been… non-traditional. I’ve crossed industries, moved across geographies, and held roles that don’t fit neatly into one function. That tends to confuse recruiters—but I see it as a strength.
There’s no “structured” path to becoming a founder. You just have to stay open to new experiences. Working across tech, product, operations, data, and strategy, I’ve learned how different parts of an organization think, what they value, and how they frame problems. Finance people solve problems with financial levers. Marketers use storytelling and positioning. Engineers build and automate. I speak all those languages—and I use that to help teams collaborate more effectively.
Through it all, tech has been my constant. I wrote my first lines of code in QBasic when I was nine, trying to recreate a “Give Yourself Goosebumps” book. I was building websites on Microsoft FrontPage back when Amazon was still a bookstore. From Physics undergrad work in image and signal processing, to writing production code in Python, Java, Go, and Dart… to hands-on experience with TensorFlow, CUDA, Kubernetes, and cloud architecture—I’ve always found myself in the thick of where technology meets the messy complexity of real-world problems.
Making Work Work
I believe that work is a fundamental human need. Not just for income, but for identity and meaning. If you’re doing work you love, it shouldn’t feel like something you need to escape from.
But how do you know if you’re in the right job? And how do teams catch early signals that someone is thriving—or not?
I’ve been on both sides: as an employee seeking meaning, and as someone making hiring decisions, aware of the cost—not just financial, but cultural—of getting it wrong. I think of Libra as a way to build better feedback loops, both for individuals and organizations, without compromising trust.
The Hardest Decision
Choosing a co-founder was probably the hardest and most consequential decision I made in this journey. It’s not marriage, but it’s not far off—you’re committing to navigating ambiguity and risk together, often for 7+ years. That’s a serious bet.
While it’s tempting to go solo, I’ve come to believe that the right co-founder doesn’t just help—they fundamentally shift your odds of success.
For Libra, that person was Yiting. Her depth in people analytics and her passion for rethinking performance management brought a perspective I didn’t have. Beyond complementary skills, she brought clarity, focus, and academic rigor. With her, we’re not just building a product—we’re shaping a lens through which organizations can see and understand emotional labor and collaboration.
What We’re Building (And How)
I don’t just want to build a company—I want to build a community. A place where people can be their true selves, but are encouraged to grow into their best selves. A lean, self-organizing team where process never gets in the way of real work. A culture where it’s safe to speak up, and where the best ideas—not the loudest voices—win.
Libra is both a product of this vision and a tool to enable others to build similar organizations—where merit, contribution, and context matter more than posturing.
Why I’m Excited
This is the first time a project brings together all my passions: AI, systems thinking, behavioral science, and the messy beauty of how people work together. I get to play with the frontier of what’s technically possible and wrestle with questions about ethics, culture, and fairness.
Sure, I’ve had my fair share of failed startup attempts. But this time feels different. I’m building this with the right person, in the right city, with the support of both academic and industry communities. If there’s ever been a shot at hitting that home run—I think this is it.
In case you missed it, this is the link to the story of my partner in crime, Yiting:
https://makegreatworkvisible.com/why-we-built-libra-yitings-story/
If you want to learn more about Libra, you can find our introduction post here:
https://makegreatworkvisible.com/introducing-libra/