Durability Over Headlines: Five Lessons from Joseph Shaposhnik
How to navigate macro noise, AI disruption, and capital cycles by focusing on what actually compounds
Some conversations leave you with a handful of ideas. Others reshape how you filter everything you see in markets. Our discussion with Joseph Shaposhnik, manager of the Rainwater Equity ETF, leaned firmly toward the latter.
What kept coming up was a consistent way of weighing what matters and what doesn’t. Macro shocks, narratives, and technological shifts all run through the same filter: how do they change the long-term earning power of a business?
That sounds straightforward. In practice, it is where most investors get pulled off course.
Here are five lessons that stayed with us.
Lesson 1: Most Headlines Don’t Matter, But Your Process Still Does
Early in the conversation, we asked Joseph how he thinks about the constant stream of macro and geopolitical news that seems to move markets every day. His answer was direct.
“Most headlines don’t have meaningful long-term impacts on companies because most headlines, by their very definition, are relatively short term in nature, and they go away.”
That framing showed up again and again. Markets react quickly, but businesses move more slowly. The gap between those two speeds is where mistakes happen.
What we found most useful is how much of this comes down to preparation. Joseph emphasized that their team spends most of its time building deep familiarity with the businesses they own. That way, when something does happen, they are not starting from scratch.
“We try to know our businesses so well that when a piece of news comes across the wire, we already have a sense for who could be impacted.”
That changes the nature of the decision. Instead of asking what the market will do next, the question becomes whether anything has shifted in the long-term economics of the business.
In many cases, it hasn’t. And when that’s clear, activity tends to drop, not increase.
“In my experience, less activity during aggressive headlines has yielded better performance.”
We’ve seen that pattern across multiple guests. The investors who stay quiet when everything feels urgent are usually the ones with the clearest sense of what actually matters.
Lesson 2: Resilience Shows Up in the Downside Scenarios
Joseph talks about durable franchises throughout the conversation, but one moment grounded that idea in a very practical way. When we asked about geopolitical risk, he focused less on predicting outcomes and more on how long a situation could persist.
“You have to build in a large buffer for how long it could go.”
That line reframes the problem. Most investors still anchor on whether something will happen. Joseph is asking whether the business can live through it if it drags on.
When we pushed on what that looks like in practice, the answer came back to the same core traits. Recurring revenue, strong customer relationships, and products that remain necessary even in weaker environments.
“It all comes back to the strength of the businesses, the durability, the franchises, and their ability to keep compounding.”
What we took from that is a shift in emphasis. The work is not just identifying good businesses, but understanding how their cash flows behave under stress. How long do they hold up if demand weakens? How dependent are they on easy financing or favorable conditions?
Those questions matter more than whether the initial catalyst plays out exactly as expected.
Lesson 3: AI Is a Spectrum, and Some Parts Are More Fragile Than They Look
When the conversation moved to AI, Joseph avoided the usual framing around winners and losers. Instead, he described a wide range of outcomes across different types of businesses.
“There are massive beneficiaries of AI, companies in the middle, and companies that will be clearly negatively impacted.”
He broke that spectrum down in a way that felt concrete. At one end are highly embedded, mission-critical systems with switching costs and regulatory complexity. Those tend to have real staying power. At the other end are businesses that rely on repackaging widely available data or offering tools that can be easily replicated.
One example he highlighted was financial data services that largely aggregate public information. Those models can look stable, but their edge is thinner than it appears.
The point became even clearer when we discussed developer workflows. Joseph noted that even at companies like Microsoft, engineers are often using the same off-the-shelf tools that are available to everyone else. If the largest and most sophisticated players are building with the same inputs, it becomes harder to argue that the tools themselves create a lasting advantage.
That pushes the question one level deeper. If the tools are commoditized, where does the moat actually sit?
For us, that was the most useful lens on AI. The impact is real, but it does not show up evenly. In some areas it strengthens existing advantages. In others, it erodes them quietly, before it is visible in reported results.
“It became clear that a large segment of data analytics and software was likely to be significantly disrupted.”
Recognizing that shift early is uncomfortable, but waiting for the numbers to confirm it usually means reacting after the economics have already changed.
Lesson 4: Capital Intensity Is Rewriting the Economics of Great Businesses
One of the more striking parts of the conversation came when Joseph walked us through how AI is changing the financial profile of companies that have historically been viewed as capital light.
“These businesses, which had been capital light, are unlikely to become capital light in the near future.”
That change flows directly through both margins and free cash flow. Many of these businesses built their appeal on converting a high percentage of revenue into cash with minimal reinvestment. Large-scale infrastructure spending challenges that model.
We talked through what that means in practice. Returns are no longer just a function of growth and pricing power. They depend on whether massive upfront investments translate into durable cash flows over time.
“Time will tell which of these businesses will be able to generate the returns necessary to justify hundreds of billions of dollars of CapEx.”
There is also a concentration element that is easy to miss. Some of these investments are tied to specific technologies or platforms.
“If that doesn’t prove out to be the winner, they will have a very hard time justifying the massive investment.”
The underlying economics of even the best businesses can shift. The label may stay the same. The cash flow profile may not.
That is where the work changes, moving from identifying great businesses to continually reassessing them as their capital allocation evolves.
Lesson 5: You Don’t Have to Pick the Winner to Participate
As we worked through how to position around AI, Joseph kept coming back to a practical constraint. The more complex and uncertain the system, the harder it is to identify the single long-term winner with confidence.
“I wouldn’t want to make a significant investment today on predicting exactly who will be the number one player ten years from now.”
That naturally shifts the focus toward parts of the ecosystem with broader exposure.
“The suppliers of the picks and shovels are likely to continue to do very well because their customer bases are more diversified.”
We have heard versions of this across other conversations, but Joseph tied it directly to the current environment. When multiple large players are all investing heavily, the suppliers benefit from that collective demand without relying on any single outcome.
It reflects a different approach to risk, widening the range of ways you can be right instead of narrowing the bet.
He also framed this in terms of exposure more generally. He is comfortable taking risk, but prefers situations where that risk is spread across many customers, use cases, or outcomes rather than concentrated in one specific path.
That becomes especially important when the range of outcomes is wide and still evolving.
The Bottom Line: Patience Anchored in Analysis
What stayed with us from this conversation was a consistent filter. Big macro moves, shifting narratives, and technological change only really matter when they alter a company’s ability to earn over time.
Joseph keeps returning to that idea, whether he is talking about geopolitical shocks, software disruption, or AI-driven capital spending. The work is in understanding the business well enough to recognize when the underlying economics have actually changed.
That leads to a style that looks quiet from the outside. It often means less activity during volatile periods and more time spent on the drivers of long-term cash flow, along with a willingness to adjust when those drivers shift even if the story still sounds compelling.
The goal is to stay grounded while everything around you is trying to drag your attention toward the next move in the tape.
Watch the full episode here: