Excess Returns Podcast

Episode: Finding Compounders in the Age of AI | Joseph Shaposhnik

Date: March 12, 2026
Host(s): Matt Zigler, Bogomil Baranowski
Guest: Joseph Shaposhnik, Portfolio Manager at Rainwater Equity ETF

Episode Overview

In this episode, the Excess Returns team welcomes back Joseph Shaposhnik to discuss the art of finding durable, long-term compounders in the rapidly changing investing landscape, with a special focus on the impact of artificial intelligence (AI). The discussion navigates both macro and micro themes, including geopolitical events, the current AI boom, transformations in software and technology business models, and how investors can identify and allocate capital to the next generation of compounders.

Key Discussion Points and Insights

1. Investing Through Headlines & Geopolitical Shocks

• Shaposhnik stresses that most headlines have little long-term impact on the majority of businesses. He cites historical macro shocks from the late 1990s onward, emphasizing the importance of business durability and recurring revenue.

  • Quote:

    "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. It all comes back to the strength of the businesses, the durability of the franchises and their ability to keep compounding."
    (00:00, 07:55)

• Defense as a structural tailwind: Shaposhnik highlights the ongoing super cycle in defense, reinforced (not weakened) by recent conflicts (e.g., in Iran and the Middle East).

  • NATO defense spending could rise by $1 trillion over the next decade, benefitting companies in that sector. (06:00)

2. Response Process to Market Shocks

• Process-driven approach:
  • Deep knowledge of portfolio companies allows for rapid assessment of headlines.
  • Focus on assessing whether events impact long-term free cash flow and compounding power.
  • Prefers less activity during periods of aggressive headline news, emphasizing discipline over reaction.
  • Quote:

    "Less activity during aggressive headlines...generally has yielded better performance or good performance from my portfolio. So I'm always cognizant of that. Not overreacting to the headlines, just going back to the companies, going back to our investment theses."
    (07:55 – 11:04)

3. Navigating the Age of AI

The AI Investment Spectrum

• Winners:
  • Semiconductors and their suppliers (picks-and-shovels providers) benefit most from AI build-out.
  • Connector markets and diversified suppliers see structural, secular growth.
• Uncertainty for software:
  • The impact of AI is "muddled" — some software firms benefit, others face existential risk.
  • Software previously seen as a fortress business model is now under threat of rapid disruption.
  • Quote:

    "For the longest time, software was thought to be one of the highest quality business models out there in the world. And I think that there's significant uncertainty about whether that will continue to be the case."
    (00:00, 36:37)

• AI disruption cycles:
  • Most businesses previously considered invulnerable are now candidates for disruption.
  • Emphasizes the need to avoid concentrated bets on single AI winners and instead back diversified suppliers.

The Mag 7 vs. The 493

• Market concentration:
  • Recent years marked by outsize returns and valuations for the "Magnificent 7."
  • Shaposhnik believes a rotation to the rest of the S&P 500 ("Magnificent 493") is underway, akin to the post-2000 tech rotation.
  • Quote:

    "We believe that there'd be significant opportunities outside of the Mag 7...there will continue to be a rotation toward regular businesses that have been good businesses that have been left behind by the market."
    (14:32)

Changing Tech Business Models

• From asset-light to asset-heavy:
  • Many former "capital light" tech companies now face massive CapEx cycles.
  • Uses Microsoft as a primary example: cloud/AI investments tie them to significant infrastructure outlays; creates new risks and reduces appeal.
  • Quote:

    "...it's unlikely that Microsoft will get back to being a capital light business for about as far as the eye can see. So these businesses which had been capital light are unlikely to become capital light in the near future. And so in some ways that makes them less attractive."
    (17:42)

  • Raises concern about single-customer (LLM) risk for hyperscalers.

The Investment Edge in AI – Suppliers Not Single Platforms

• Prefers investing in diversified suppliers to LLMs and hyperscalers over betting on platform winners.
• Quote:

  "I wouldn't want to make a significant investment today on predicting exactly who will be the number one player ten years from now. Which is why I think investing behind the suppliers who supply multiple LLMs today and multiple, multiple hyperscalers today is the better route."
  (00:00, 25:00)

CapEx Cycles, Return Risks, and Market Misses

• CapEx for cloud/AI is likely to normalize but risks from massive historical investments remain if "wrong horse" is backed.
• Semi suppliers enjoy stronger economics and lower customer concentration risk.

4. Software in Turmoil: Investment Lessons

• Buffett quote (1987):

  "Experience indicates that the best business returns are usually achieved by companies that are doing something quite similar today to what they were doing five or 10 years ago. ... A business that constantly encounters major change also encounters many chances for major error. ... Economic terrain that is forever shifting violently is ground on which it is difficult to build a fortress like business franchise."
  (27:21, attributed by Joseph Shaposhnik)

• Shaposhnik’s portfolio actions:

  • Trimmed software exposure mid-2025 amid rising AI disruption and leadership change at Constellation Software.
  • Believes software is now a more competitive and dynamic (and risky) sector.

What Makes a Software Business “Antifragile” in AI?

• High regulatory/compliance integration, core operational necessity, proprietary data, and customer-centric learning cultures provide defensibility.

• Decentralized, learning organizations with strong customer relationships and active AI adoption are more resilient.

  • Quote:

    "There's no substitute for organizations that are decentralized, have appropriate incentives put in place...and are a learning culture..."
    (32:19)

• Companies merely repackaging public data face rapid commoditization.

5. Broader Impact: Labor Markets and the Economy

• Debates the conventional fear of white-collar job loss due to AI – recent data suggests robust growth in programming and engineering jobs.
  • Some automation creates new and different job needs (e.g., fixing AI mistakes).
• Stresses the difficulty of forecasting macroeconomic effects; prefers businesses agnostic to cyclical economic swings.

6. Philosophical Frameworks: Fragile vs. Antifragile

• Businesses that are sticky, highly integrated, and with proprietary advantages are more "antifragile".
• Service businesses or software firms that merely aggregate public data are "fragile" and ripe for disruption.
• Even in leading firms (e.g., Microsoft), most engineers use the same off-the-shelf AI tools as everyone else — reinforcing the importance of agile, innovative cultures over proprietary tech alone.

7. Where Are the Clear AI Winners?

• Early, but with signals:
  • Semiconductors and critical suppliers come up as the clearest beneficiaries.
  • Potential for improved efficiency and new business models in industrial distribution (e.g., Grainger, Fastenal) via AI and robotics.
• Management quality as a differentiator:
  • Great managers have already been investing in AI and will successfully adapt/build "bridges" to the future.

8. The Coming Wave: Startups, Innovation, and Fragmentation

• A new ecosystem:

  • The infrastructure giants (“the rails”) will enable thousands of smaller, nimble, niche software providers and businesses (paralleling railroads facilitating the rise of new cities/industries).
  • Lower barriers to entry; faster iteration; richer, more dynamic entrepreneurial landscape.

• But fundamentals still matter:

  • Reminds that sustainable cash flows and durable business models trump excitement over innovation alone.
    • Quote:

      "...at the end of the day we're trying to find cash flows, right? ... We are so excited about this innovation. But then are there profits? Are they sustainable?"
      (58:44)

9. Shaposhnik’s Investment Mandate

• Bottom-up focus:
  • Recurring revenue, strong franchises, and exceptional management are more important than top-down AI exposure.
  • Winners will be companies that use the best tools available to enhance long-term value, regardless of how “sexy” they are as businesses.
  • Still keenly evaluating how AI impacts each industry, but remains diversified and skeptical of hype cycles.

Notable Quotes & Memorable Moments

• On not chasing headlines:

  "Not overreacting to the headlines, just going back to the companies, going back to our investment theses on these businesses and trying to understand whether anything has meaningfully changed."
  (07:55)

• On software’s shifting investability:

  "...software will be a more competitive industry than it has been. It'll be a more dynamic industry than it has been. And the Buffett quote ... is something that we certainly bear in mind as we make these decisions."
  (36:46)

• On the role of management:

  "Great managers have been investing behind AI for the last several years, not just starting and starting their investment today."
  (49:17)

Timestamps of Important Segments

| Timestamp | Segment | |---------------|-----------------------------------------------------------------------| | 00:00 | Shaposhnik on headlines vs. durable compounders | | 06:37 | Process for reacting to sudden headlines and evaluating companies | | 11:04 | Discussion shifts to the impact and cycle of AI in investing | | 14:32 | "The 493" vs. "The Mag 7" and market breadth | | 17:42 | CapEx cycle, asset-light vs. asset-heavy models (incl. Microsoft) | | 25:00 | AI winners: platform concentration vs. picks-and-shovels suppliers | | 27:21 | Software sector risk and the Buffett moat quote | | 32:19 | What makes a software business resilient (antifragile) | | 36:37 | Uncertainty and disruption potential in software | | 46:55 | Where clear AI winners may emerge & sector-specific thoughts | | 58:44 | Caution: Not all innovation leads to durable profits | | 62:22 | Practical takeaways: focus on the best users of the best tools | | 65:00 | Where to find Shaposhnik and Rainwater Equity ETF |

Summary Takeaway

Shaposhnik’s core message is one of disciplined, bottom-up investing focused on recurring revenue, franchise durability, and exceptional management — especially important in an age of relentless change powered by AI. While certain sectors (semiconductors, infrastructure suppliers) are early and clear beneficiaries of AI, others (notably software) will face increasing competition, lower moats, and rapid disruption. The future may be marked by a proliferation of niche, high-velocity businesses built atop the infrastructure laid by today’s giants, but the fundamental investor’s challenge remains: identify those who will generate real, sustainable cash flows over the long term, regardless of hype or headline.