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3 Things 11-17-25

 Thing One

 

Using AI Tools To Predict Long-Term Care Needs


I recently read an interesting piece on Kiplinger.com about Waterlily, an AI-powered platform that predicts long-term care (LTC) needs and helps you figure out how to pay for them. What struck me most is how fast the whole process works. You answer a short three-minute questionnaire about your health, medications, and family history — and within seconds, Waterlily generates a personalized long-term care report.

 

The example Kiplinger walked through was eye-opening. Waterlily estimated a 70% chance the writer would need long-term care, beginning around age 86, and lasting a little over four years. The projected care path started with home help from family, transitioned to assisted living, and eventually moved into a full-care nursing facility.

 

Then came the real shock: Waterlily projected total lifetime LTC costs of $1.48 million (inflation-adjusted). Most of that came from an estimated 18-month stay in a nursing home — the most expensive stage of the journey. It’s a harsh reminder of just how financially devastating a long-term care event can be.

 

The article also highlighted a common misconception: many Americans still believe Medicare will cover long-term care. It won’t — at least not the kind of long-term, day-to-day support most people ultimately need.

 

Where Waterlily becomes especially useful is in planning how to fund those future costs. The Kiplinger writer first explored “self-funding,” allocating $200,000 of retirement assets. Waterlily’s math showed that would only cover 52% of projected expenses. So the writer tested adding a $100,000 long-term care insurance policy. Waterlily’s AI analyzed hundreds of thousands of policy options and instantly found one with a 494% return on investment, providing $574,000 of total coverage. Combined with self-funding, that approach covered 91% of the projected LTC costs.

 

The platform can also evaluate joint LTC policies for couples, review existing policies, and estimate how likely you are to be approved based on your medical profile. And while the tool handles a lot of sensitive personal information, Waterlily does offer a way to request deletion of your data.

The article mentioned one last statistic that really stood out: only 11% of adults have purchased LTC insurance. Given the rising costs of care, it’s not surprising that a tool like Waterlily — which provides clarity in seconds — could become a valuable resource.

 

Kiplinger’s takeaway was straightforward: planning for long-term care is too important to leave to guesswork. And if AI can help you see your future needs clearly, it’s worth paying attention to - along with a human advisor like us.

  

 

Thing Two  

 

How Capitalism Quietly Makes Everyday Workers Wealthy

 

There’s a lot of talk these days about socialism making a comeback. Critics love to point to rising inequality and low wages as proof that capitalism is broken. The proposed fixes are usually big government moves—steep wealth taxes, sky-high minimum wages, more redistribution.

 

But a recent Wall Street Journal article makes a very different case: the private sector is already solving the inequality problem on its own—not loudly, not politically, but through something much more powerful and sustainable: employee ownership.

 

The article highlights how companies across the country are turning regular employees into millionaires, often without those employees even realizing it’s happening until years later. The engine behind it is simple—401(k) plans, stock-purchase programs, and long-term ownership of company shares.

 

Fidelity just reported a record number of 401(k) millionaires, over half a million people. And for the first time, more than half of private-sector workers now participate in employer retirement plans. That’s millions of Americans quietly building real wealth, paycheck by paycheck.

The WSJ piece uses several big-name companies to make the point. Take AutoZone. The founder and top executives are wealthy, of course—but so are more than 4,000 lower-level employees, the people running stores, stocking shelves, and helping customers. The company offers discounted stock, strong 401(k) matches, and stock options for key roles. With the stock returning an average of 21% annually for two decades, it’s no wonder so many employees have crossed the millionaire mark.

 

The same story shows up at Microsoft. Bill Gates offered broad stock options early on, and by 2005, thousands of rank-and-file employees had already become millionaires. With Microsoft’s stock exploding over the last decade, that number has only grown. Today, it’s estimated that more than 30,000 employees—everyone from engineers to administrative staff—have hit seven figures mostly because they owned shares.

 

Even retailers like Home Depot tell the same story. Co-founder Ken Langone has said they wanted everyone to have “skin in the game,” which led to thousands of associates who started out pushing carts now retiring as millionaires. And then there’s Nvidia, where nearly 80% of employees are reportedly millionaires thanks to generous stock programs and a meteoric rise in the company's value.

 

What’s striking is that none of this comes from government programs, higher taxes, or wage mandates. It comes from companies choosing to share ownership and employees consistently investing in their future.

According to the National Center for Employee Ownership, more than 12,000 companies now share ownership with over 25 million workers—and the number keeps growing.

 

The WSJ article boils the wealth-building formula down to something incredibly simple: buy company stock or broad index funds automatically from every paycheck, hold them for decades, and let the system do its work.

 

And as Mark Skousen, the article's author points out, this isn’t democratic socialism. It’s democratic capitalism—profitable companies sharing their success, and ordinary workers becoming wealthy because of it.

 

Thing Three


Just A Thought  


“Mistakes are a fact of life. It is the response to the error that counts.” — Nikki Giovanni

 

 
 
 

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