Services Aren’t the Sin. Linear Scaling Is.
Execution Economics: Part II
Most AI companies look like services businesses early on. That’s not a failure. But it creates a common misconception about what’s actually going wrong.
Services aren’t the problem. Linear scaling is.
Early AI deployments often require embedded engineers, custom integrations, and hands-on execution. That’s rational.
The problem is not that services exist. The problem is when they persist.
For the next customer or existing customer, how hard was it to upsell the existing customer to a new process? Was it just as hard as the first solution? It’s common for consulting companies to be unable to upsell on a bespoke project.
In the beginning, every customer is worth pursuing, but it takes a founder’s serious conviction to turn down revenue, as they know the use case won’t be transversal. There has to be a road map made up.
In a linear model, each new customer requires a proportional amount of effort. More revenue requires more people, more custom work, and more complexity.
In a convergent model, each new customer becomes easier to serve. Early work hardens into reusable systems, and marginal effort declines over time.
Only one of these compounds.
Qualified Health illustrates the transition clearly. Early deployments were deeply embedded and highly customized. Over time, those deployments produced shared ontology models, governance layers, and integration patterns that reduced marginal effort across customers.
The forward-deployed engineers were not the moat. The infrastructure they helped build was.
Ciridae shows the same dynamic from a services-heavy starting point. The company initially relied on human-in-the-loop. Margins expanded only when tooling absorbed the median workflow, and human involvement shifted toward supervision and exception handling.
Automation handles the standard workflows so humans can focus on edge cases.
The signal is not whether services are present. It’s whether they are becoming unnecessary. If delivery headcount scales with revenue, the business is not compounding. It is growing linearly.
If you want to understand whether a company is actually scaling like software, ask:
Is delivery headcount per dollar of revenue declining?
Is deployment time compressing across customers?
Are new customers benefiting from past work?
Is automation replacing labor in the median workflow?
If revenue grows but delivery scales with it, you don’t have a software business yet.
You have a services business with a software layer.
Are you turning services into infrastructure - or repeating the same work every time?
→ Part I: Customer Two Is the Only Metric That Matters
→ Part II: Services Aren’t the Sin. Linear Scaling Is.