Clouded Judgement 5.30.25 - Moats in the Age of AI

Every week I’ll provide updates on the latest trends in cloud software companies. Follow along to stay up to date!

Moats in the Age of AI

A lot has been written about moats in software. Network effects. Switching costs. Proprietary data. Everyone wants to believe they’re building one. But I’ve come to believe the idea of a “long term moat” is mostly a myth, especially in this market. Moats aren’t permanent. They’re time-bound. At best, they function as a bridge. And companies either use that bridge to reach the next defensible position, or watch their moat get breached.

The real “long-term moat” is just a sequence of smaller moats stacked together. Each one buys time. And what you do with that time, how fast you execute, how quickly you evolve, determines whether you stay ahead. In the Age of AI, this is more true than ever. If the moat time window used to be 6–12 months, today it’s 2–3 weeks. Models change. Infrastructure shifts. Customer needs rewrite themselves in real time. What was a 12-month product head start in 2022 is now 3 prompts and a wrapper in 2024. It’s easier than ever to both build and distribute software.

And it’s happening all around us! The first LLM-based CRMs? Swarmed. The first AI note-taking tools? Cloned endlessly. Even infra plays like vector DBs or agent frameworks are seeing differentiation collapse overnight.

Speed isn’t just important, it is the moat. The ability to build, ship, learn, and adapt faster than everyone else is the only sustainable edge right now. In a world where everything is open source, everything is demo-able, and everything is one blog post away from being copied, speed is the only thing that compounds.

Execution speed. Hiring speed. Firing speed. Distribution speed. Even decision-making speed. You don’t win because you’re defensible, you win because you’re faster. Killing bad ideas is just as important as the speed of executing against good ones. The opportunity cost of time has never been greater. So if you’re trying to build a moat today, maybe don’t think of it as a castle wall. Think of it as a race. Whoever stacks the most advantages the fastest: products, distribution, talent, infra, wins.

Quarterly Reports Summary

Top 10 EV / NTM Revenue Multiples

Top 10 Weekly Share Price Movement

Update on Multiples

SaaS businesses are generally valued on a multiple of their revenue - in most cases the projected revenue for the next 12 months. Revenue multiples are a shorthand valuation framework. Given most software companies are not profitable, or not generating meaningful FCF, it’s the only metric to compare the entire industry against. Even a DCF is riddled with long term assumptions. The promise of SaaS is that growth in the early years leads to profits in the mature years. Multiples shown below are calculated by taking the Enterprise Value (market cap + debt - cash) / NTM revenue.

Overall Stats:

• Overall Median: 5.6x

• Top 5 Median: 23.2x

• 10Y: 4.4%

Bucketed by Growth. In the buckets below I consider high growth >25% projected NTM growth, mid growth 15%-25% and low growth <15%

• High Growth Median: 20.6x

• Mid Growth Median: 9.2x

• Low Growth Median: 4.1x

EV / NTM Rev / NTM Growth

The below chart shows the EV / NTM revenue multiple divided by NTM consensus growth expectations. So a company trading at 20x NTM revenue that is projected to grow 100% would be trading at 0.2x. The goal of this graph is to show how relatively cheap / expensive each stock is relative to their growth expectations

EV / NTM FCF

The line chart shows the median of all companies with a FCF multiple >0x and <100x. I created this subset to show companies where FCF is a relevant valuation metric.

Companies with negative NTM FCF are not listed on the chart

Scatter Plot of EV / NTM Rev Multiple vs NTM Rev Growth

How correlated is growth to valuation multiple?

Operating Metrics

• Median NTM growth rate: 11%

• Median LTM growth rate: 14%

• Median Gross Margin: 76%

• Median Operating Margin (4%)

• Median FCF Margin: 18%

• Median Net Retention: 108%

• Median CAC Payback: 45 months

• Median S&M % Revenue: 38%

• Median R&D % Revenue: 24%

• Median G&A % Revenue: 16%

Comps Output

Rule of 40 shows rev growth + FCF margin (both LTM and NTM for growth + margins). FCF calculated as Cash Flow from Operations - Capital Expenditures

GM Adjusted Payback is calculated as: (Previous Q S&M) / (Net New ARR in Q x Gross Margin) x 12 . It shows the number of months it takes for a SaaS business to payback their fully burdened CAC on a gross profit basis. Most public companies don’t report net new ARR, so I’m taking an implied ARR metric (quarterly subscription revenue x 4). Net new ARR is simply the ARR of the current quarter, minus the ARR of the previous quarter. Companies that do not disclose subscription rev have been left out of the analysis and are listed as NA.

Sources used in this post include Bloomberg, Pitchbook and company filings

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