From financial leverage to capability leverage — why owning delivery creates compounding advantage.
When General Catalyst published “The Future of Services: Capability-Led Growth Compounding Through Direct Ownership,” it articulated what many of us in the industry have sensed for years — that the next frontier of transformation will occur not in pure technology or pure services, but in the integration of both.
The thesis is powerful:
Technology builders can capture greater value by directly owning and operating the service businesses that deliver their innovations to end customers.
In other words, the future belongs to those who operationalize technology, not just develop it.
At Stellar, we’ve been preparing for this future for several years. We didn’t set out to “build an AI-enabled roll-up.” We set out to solve the structural inefficiencies in service delivery — to create a model where knowledge, technology, and human expertise reinforce one another.
In hindsight, that’s precisely what General Catalyst is describing.
Anticipating the Convergence of Technology and Services
Traditional service businesses — in accounting, compliance, or corporate administration — have long been constrained by the limits of human throughput and fragmented systems.
Meanwhile, software firms often stopped short of the last mile: their tools enhanced productivity but didn’t fundamentally change service delivery.
The opportunity now lies at the intersection — where service execution becomes a capability that compounds through technology.
At Stellar, we began building the foundations for this model years ago:
- A unified operating platform that brings together formation, compliance, payroll, bookkeeping, and CFO functions across multiple jurisdictions.
- Structured knowledge bases and AI agents trained on proprietary service data, enabling consistency, accuracy, and decision support across teams.
- A modular integration framework designed to absorb new service lines or acquisitions seamlessly, standardizing processes and data from day one.
Each of these elements serves a single objective: to convert what has traditionally been human tacit knowledge into explicit, interoperable systems — so that service excellence can scale.
From Vision to Realization
The vision described by General Catalyst is entirely achievable. But realizing it requires more than conviction; it demands depth, precision, and disciplined execution.
AI doesn’t inherently transform a service business — it amplifies whatever operating model it’s applied to.
In practice, that means success depends on a few non-negotiable foundations:
- Systemic process design.The organization must operate as a coherent system, not a collection of disconnected workflows. Processes need to be observable, measurable, and replicable across teams and regions.
- Data architecture and integrity.Information — from client records to compliance filings — must exist in a structured, machine-readable form. Without this foundation, automation introduces more error than efficiency.
- Organizational alignment.Transformation requires cultural readiness. Teams must understand not just what is changing, but why — and see technology as a multiplier of their capability, not a threat to their role.
At Stellar, much of our early effort went into this groundwork: mapping service flows, codifying operational logic, and creating common taxonomies for data and services.
Because intelligence compounds only when structure exists.
Executing the AI-Enabled Roll-Up
The difference between a financial roll-up and an AI-enabled one is profound.
- A traditional roll-up captures financial arbitrage — buying fragmented service providers, consolidating overhead, and improving margin.
- An AI-enabled roll-up captures capability arbitrage — integrating technology into the operating core, so each acquisition strengthens the platform’s intelligence and throughput.
This distinction changes the growth equation.
Instead of chasing economies of scale, you’re creating economies of learning — where every new business integrated into the platform enhances collective capability.
In practice, this means embedding technology into delivery workflows, centralizing data, and continuously retraining systems to improve quality and speed.
It also requires governance discipline — to ensure each acquisition aligns with a shared operational model and cultural DNA.
Why This Moment Is So Exciting
While the operational demands are real, this is one of the most promising transformations in the modern business landscape.
Three factors make it particularly compelling:
- Rebundling creates defensibility.By integrating technology and service delivery, companies become embedded in the daily operations of their clients. The result is deeper relationships, higher retention, and stronger barriers to entry.
- Capability compounds faster than capital.When knowledge, data, and automation reinforce one another, productivity growth outpaces headcount growth. The platform becomes smarter — not just larger — with each transaction.
- Global expansion becomes viable.Standardized processes and AI-enabled workflows reduce the marginal cost of entering new markets. What once required 200 people per country can now be achieved with 30 — without compromising quality or compliance.
For operators and investors alike, this model redefines what a “services business” can be: intelligent, scalable, and outcome-oriented.
Closing Reflection
The convergence of AI and services is not a speculative future; it’s already unfolding.
But sustainable success will favor those who build for substance, not headlines — who combine vision with operational depth.
At Stellar, we view this as a once-in-a-generation opportunity to rebuild how service industries operate — to turn institutional knowledge into scalable infrastructure and deliver true capability-led growth.
It’s a challenge worth taking on.
And if we execute it well, it won’t just reshape our industry — it will redefine what it means to operate a company in the age of intelligent systems.
