This As They Told It essay is based on a conversation with Lily Vittayarukskul, 30, co-founder and CEO of water lily. It has been edited for length and clarity. As a child, I was fascinated by the universe and wanted to understand how the world worked. Science taught me that even the most important and
This As They Told It essay is based on a conversation with Lily Vittayarukskul, 30, co-founder and CEO of water lily. It has been edited for length and clarity.
As a child, I was fascinated by the universe and wanted to understand how the world worked. Science taught me that even the most important and intimidating questions can be broken down, understood, and ultimately solved.
I also grew up with limited resources, and working in my parents’ factory after school taught me how hard families work to create stability and how much discipline and ingenuity it takes to build something from very little.
At age 11 I entered a NASA contest with a homemade water rocket, I won the contest and had the opportunity to visit the Kennedy Space Center. Later, when I was a young teenager, I interned at NASA. For years I thought aerospace engineering was my future.
Then my aunt was diagnosed with cancer and the trajectory of my entire family changed almost overnight.
My aunt didn’t speak much English, so my mom translated at doctor’s appointments. My family quickly realized that there were expenses we were not expecting. We also learned that caring for someone with a serious illness went far beyond doctor’s appointments.
I was 16 years old when she got sick. What I remember most was not a single diagnosis or conversation. It was silence.
Everyone in my family was exhausted, going from work to doctor’s appointments to caring for someone without even stopping to talk about what was happening. We were all operating on autopilot because there was simply too much to do.
Watching my family fall apart changed my definition of impact.
Courtesy of water lily
My mother became my aunt’s primary caregiver. The rest of us worked in the family factory whenever we could. I would go to my parents’ factory after school and often stay until 10 or 11 at night before returning home.
Only later did I realize the full cost.
Our family relationships had become strained. Economically we had almost nothing left. There was guilt, tension, and isolation that lingered long after my aunt died.
Growing up in a first-generation immigrant family, I always understood that money matters. My parents worked incredibly hard, but I learned early that hard work alone does not guarantee financial security. You have to create economic value. That lesson shaped almost every decision I’ve made since.
After my aunt died, I began to ask myself a different question: Instead of wondering how I could build better rockets, I asked myself why families like mine had to face one of life’s most difficult times with so little support.
I realized that no one was solving the problem that mattered most to me.
Vittayarukskul co-founded her company to help families avoid what hers went through. Courtesy of water lily
I still loved engineering and building things, but I realized I could apply those skills somewhere that felt much more personal to me.
I spent nearly a decade leading product and engineering at early-stage companies while learning everything I could about healthcare, financial services, and underserved populations. I wanted to understand why planning for aging and long-term care was so fragmented.
No one seemed to be solving the problem the way I thought it should be solved. That’s why I co-founded Waterlily.
Waterlily is an AI-powered long-term care planning platform that helps people estimate when they may need long-term care, how much it might cost, and how to pay for it based on their health, finances, and family situation. The platform offers personalized projections and financing strategies, including insurance, savings and care plans, to help families prepare for the financial and logistical challenges of aging. Since its launch, the company has raised $9.2 million.
The work has been much harder than I imagined.
Healthcare does not exist in one industry. Neither does aging. We work simultaneously in health, insurance and financial services, each with different incentives and different ways of operating. Every week seems to introduce a new layer of complexity.
There were many moments where I wondered if we could figure it out. However, what kept me going was the same question I asked myself after my aunt died. If we are not solving this problem, who will?
After speaking with thousands of families, one thing surprised me. I assumed my family’s experience was unusually devastating. Instead, I found that many families experiencing serious long-term care needs face financial strain and relationship breakdowns. The details vary, but the emotional toll often seems remarkably similar.
Building this company changed the way I think about my own future.
Starting Waterlily has changed me in ways I didn’t expect.
I have gained far more financial knowledge than I ever thought I would need. Building Waterlily has required me to develop deep expertise in insurance, retirement planning, healthcare, and financial services. Understanding aging means understanding how all of those systems (and the decisions families make within them) fit together.
Understanding aging means understanding insurance, retirement accounts, savings, investing, and how all those pieces fit together.
It has also changed the way I think about responsibility.
When I was younger, I thought success meant solving interesting technical problems. Now, I think success means building something that helps people regain a sense of control in times when life feels completely uncertain.
If my aunt were alive today, I don’t think she would care much about the technical details of the platform. But I also think I would ask myself two questions:
- Are you helping people?
- Is this business sustainable?
I’d like to think she’d be proud of both answers.
Waterlily offers a free tool on its site that provides personalized information, based on more than 500 million data points, to better understand what aging and long-term care could look like.
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