Durability (Not Growth) Will Define AI Winners
What Jamin Ball, Des Traynor, and Cassie Young are all pointing to.
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There are many independent perspectives shared through content. We read a ton of them, and there’s connective tissue between some that reveal a broader macro and message. This week, we’re highlighting a few pieces from different leaders because, together, they reveal a deeper pattern emerging across AI.
Across the ecosystem, a single truth is coming into focus:
Most AI traction today is experimental, not durable.
And the market is beginning to price that reality in.
Three independent perspectives were written, which are highlighted here:
Jamin Ball’s ERR vs. ARR analysis
Des Traynor’s Four Horsemen
Cassie Young’s customer success renaissance
But together, they describe the same structural shift:
We’re entering an AI cycle defined not by adoption, but by retention.
Not by growth, but by durability.
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Jamin Ball (Clouded Judgement): ERR vs. ARR
In his March 2024 Clouded Judgement, Jamin Ball surfaces one of the most important (and most uncomfortable) truths about AI revenue today: a significant portion of what startups call ARR is really ERR: Experimental Run-Rate Revenue. Many have since added to the narrative, including ourselves in this edition.
Classic SaaS ARR works because retention is predictable:
90–95% gross retention keeps customers for a decade.
120%+ NRR compounds revenue.
Investors can underwrite future cash flows with confidence.
In AI, three structural breaks are happening at once:
1. Annualizing without commitment.
Teams are multiplying monthly usage by 12 and calling it ARR, even when the revenue doesn’t behave like a contract.
2. Buyers are experimenting aggressively.
They’re testing multiple vendors in parallel. In many cases, the first tool used in a prototype is not the one running in production.
3. Early AI categories are commoditizing.
Competition is exploding, prices are falling, and switching happens before companies can even measure churn.
Often, AI companies are reporting growth that is neither predictable nor durable.
Gross retention will be the truth serum of this cycle.
Des Traynor (Intercom): The Four Horsemen of AI
If ERR explains why early traction is unstable, the Four Horsemen explain how to assess what’s actually durable. In a Cheeky Pint podcast episode, Intercom’s co-founder expressed that today’s AI boom has created an illusion of traction. ARR is rising, logos look impressive, and rounds are getting bigger, but a large share of this revenue is experimental, not durable. Much of what’s being counted as ARR is actually ERR (experimental run-rate): pilots, POCs, and opt-out trials funded by innovation budgets and AI FOMO.
He introduces the Four Horsemen of AI - the filters that reveal whether traction is real:
Revenue backed by usage
Usage tied to business impact
Deep, differentiated AI
Positive unit margins
The idea is that startups should have all four of these. But most AI companies meet only the illusion of the first horseman.
The Four Horsemen reveal the gap between reported growth and retained value.
Revenue quality in AI is being redefined by durability, not velocity.
Cassie Young (Primary Venture Partners): Tech is on the brink of a gross retention apocalypse and a customer success renaissance
If ERR exposes instability, and the Four Horsemen define what’s durable, Cassie Young’s writing explains how companies actually earn that durability.
Her argument: The AI era is triggering a customer-success renaissance.
Switching costs are collapsing, time-to-value is compressing, and organizations are buying AI faster than they understand it (and churning faster than anyone expected).
In that environment, the winners aren’t the companies with the best demos, they’re the ones that operationalize value delivery.
Cassie highlights the shifts already underway:
Compressing time to value
Quantifying ROI weekly, not annually
Integrating into critical workflows
Building POC “factories” to accelerate adoption
Engineering for value delivery, not just value capture
Customer success is no longer a post-sale function. Rather, it’s the operating system of durable AI companies.
Durability becomes the moat.
Put these three lenses together – ERR, the Four Horsemen, and the customer-success renaissance – and a unified market story emerges:
AI’s early traction is inflated by experimental revenue. ERR is driving growth numbers that won’t survive the first renewal cycle.
The Four Horsemen are becoming the market’s durability filter. Usage, business impact, differentiation, and margins separate experiments from enterprises.
Customer success is becoming the backbone of AI. Fast adoption is easy, and retained adoption is rare. Durability requires operationalized value delivery.
Across operators, investors, and founders, these signals converge on one conclusion:
The winners of the AI decade won’t be defined by how fast they grow, but by how long they can last.
Always play the long game.
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Durability over flashy growth is spot-on. AI startups that embed measurable value into workflows and prioritize retention will outlast the hype-driven players.
I talk about the latest AI trends and insights. If you’re interested in understanding how to spot durable AI strategies and build long-lasting value in your projects, check out my Substack. I’m sure you’ll find it very relevant and relatable.