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Home » The Event That Turned an Aerospace Engineer Into an AI Founder
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The Event That Turned an Aerospace Engineer Into an AI Founder

EditorBy EditorJuly 25, 2026No Comments5 Mins Read
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This as-told-to essay is based on a conversation with Lily Vittayarukskul, 30, cofounder and CEO of Waterlily. It has been edited for length and clarity.

When I was a kid, I was fascinated by the universe and wanted to understand how the world worked. Science taught me that even the biggest, most intimidating questions could be broken down, understood, and eventually 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 resourcefulness it takes to build something from very little.

At 11, I entered a NASA competition with a homemade water rocket, won the competition, and got the chance to visit Kennedy Space Center. Later, I interned at NASA as a young teenager. 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 learned that there were expenses we hadn’t expected. We also learned that caring for someone with a serious illness extended far beyond medical appointments.

I was 16 when she became sick. What I remember most wasn’t a single diagnosis or conversation. It was the quiet.

Everyone in my family was exhausted, moving from work to doctor’s appointments to caregiving without ever stopping to talk about what was happening. We were all operating on autopilot because there was simply too much to do.

Watching my family unravel changed my definition of impact

Headshot of Lily Vittayarukskul

Courtesy of Waterlily



My mom became my aunt’s primary caregiver. The rest of us worked at the family factory whenever we could. I went to my parents’ factory after school, often staying until 10 p.m. or 11 p.m. before going home.

Only later did I realize the full cost.

Our family relationships had become strained. Financially, we had almost nothing left. There was blame, tension, and isolation that lingered long after my aunt died.

Growing up in a first-generation immigrant family, I’d always understood that money mattered. My parents worked incredibly hard, yet I learned early that hard work alone doesn’t guarantee financial security. You have to create economic value. That lesson shaped almost every decision I’ve made since.

After my aunt died, I started asking a different question: Instead of wondering how I could build better rockets, I wondered why families like mine had to navigate one of life’s hardest moments with so little support.

I realized no one was solving the problem I cared about most

Lily Vittayarukskul in white pants and shirt walking a black dog with San Francisco bridge in background.

Vittayarukskul cofounded her company to help families avoid what hers went through. 

Courtesy of Waterlily



I still loved engineering and building things, but I realized I could apply those skills somewhere that felt much more personal.

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 needed to be solved. That’s why I cofounded 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 could cost, and how to pay for it based on their health, finances, and family situation. The platform provides personalized projections and funding strategies—including insurance, savings, and caregiving plans—to help families prepare for the financial and logistical challenges of aging. Since launching, the company has raised $9.2 million.

The work has been much harder than I imagined.

Healthcare doesn’t exist in one industry. Neither does aging. We work across healthcare, insurance, and financial services simultaneously, each with different incentives and different ways of operating. Every week seems to introduce a new layer of complexity.

There were plenty of moments when I questioned whether we could figure it out. What kept me going, though, was the same question I asked myself after my aunt died. If we’re not solving this problem, who will?

After speaking with thousands of families, one thing surprised me. I’d assumed my family’s experience was unusually devastating. Instead, I found that many families who experience serious long-term care needs face financial strain and relationship breakdowns. The details vary, but the emotional toll often looks remarkably similar.

Building this company changed how I think about my own future

Starting Waterlily has changed me in ways I didn’t expect.

I’ve become much more financially literate than I ever thought I’d need to be. Building Waterlily has required me to develop deep expertise across 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’s also changed how 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 during moments when life feels completely uncertain.

If my aunt were alive today, I don’t think she would care very much about the technical details of the platform. But I also think she’d ask me 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 insights, based on more than half a billion data points, to better understand what aging and long-term care could look like.



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