A practical perspective on why AI is changing not just how work gets done, but how delivery capacity should be structured.
Toronto, May 7, 2026
At its core, this article tackles a simple but important question:
Do we hire full-time employees — or is there a better way to scale delivery?
Hiring often feels like the default, and in many cases it is the right answer. But as delivery demands increase, roadmaps become more dynamic, and AI begins to reshape how software is built and supported, leadership teams are increasingly discovering that hiring introduces friction precisely when speed and flexibility matter most.
This article explores the practical trade-offs between traditional FTE hiring and a Productized Delivery Organization (PDO) model — based on patterns we see repeatedly across growing technology and product-led organizations.
A Personal Lens
When I was CEO of Tier1, we needed to launch a mobile app to expand our capital markets CRM into investment banking, but our core team was fully committed to existing deliveries. We used a PDO to move fast without disrupting the roadmap — an approach that fundamentally changed how I think about scaling execution.
Today, that same decision is even more relevant — not just because of speed, but because of how AI is changing the shape of delivery teams themselves.
The Traditional Path: Hiring Full-Time Employees
Hiring FTEs makes sense when:
- Demand is stable and predictable
- Roles are well defined and long-lived
- Teams have the bandwidth to recruit, onboard, and manage
In practice, however, many organizations encounter challenges as they try to scale this way:
- Long lead times from approval to productive output
- Recruiting risk — quality varies, and backfilling is inevitable
- Fixed capacity even as priorities shift
- Management overhead added to already stretched leaders
- Delivery outcomes tied closely to individual performance
What looks like capacity on paper often translates into slower execution in reality.
Where Friction Creeps In
The friction usually isn’t visible at first. It shows up gradually:
- Roadmaps move faster than hiring cycles
- Senior leaders spend more time managing people than shipping outcomes
- Teams are sized for last quarter’s priorities, not next quarter’s
- Quality becomes inconsistent as teams scale unevenly
At that point, the organization isn’t short on people — it’s short on execution velocity.
The AI Shift: Rethinking What “Capacity” Means
AI is fundamentally changing how delivery work gets done.
- Developers are becoming multipliers, not just contributors
- QA is increasingly automated and embedded in the development cycle
- Support and operational roles are being streamlined through AI-assisted workflows
As a result, the number of people required to deliver the same output is declining. The skill mix required is also shifting raplidly, and teams built around yesterday’s roles can quickly become misaligned. This creates a new kind of risk with FTE hiring: you’re locking in static capacity in a dynamic, AI-driven environment.
This shift is increasingly visible across the companies Phil Dias and I work with at Silver Peak, from our experience building and scaling Tier1, to advising growth-stage organizations and private equity-backed businesses today. Patterns are emerging around how AI is reshaping both delivery capacity and investment thinking. As Phil, said,
We’re seeing a structural shift — not just in how much work gets done, but in how teams are composed. The question is no longer ‘how many developers do we need,’ but ‘how do we deploy the right capability, augmented by AI, as efficiently as possible.’” -Phil Dias
A Modern Alternative: The PDO Model
A Productized Delivery Organization (PDO) takes a fundamentally different approach.
Instead of scaling delivery role by role, organizations engage ready-to-run delivery pods — cross-functional teams that are assembled, onboarded, and governed as a unit.
A PDO typically includes:
- A balanced mix of engineering, QA, and delivery leadership
- Established delivery processes and tooling
- Built-in quality and automation practices
- Deep integration of AI-assisted development and testing workflows
- Clear accountability for outcomes, not just effort
The focus shifts from staffing to outcomes.
From the vantage point of a delivery organization operating at scale, these changes are already playing out in real-world execution environments. At Silver Peak execution partner Metacube, AI has fundamentally reshaped how work gets done — influencing everything from development workflows and QA automation to team structure and delivery velocity. As Parijat Agarwal, Co-Founder of Metacube, observes:
AI has fundamentally changed how we deliver. It’s embedded across the entire lifecycle — from how code is written and tested, to how teams are structured and how quickly we can move. The organizations that win will be those that operationalize AI across everything they do, not treat it as an add-on.” -Parijat Agarwal
FTE vs. PDO – A Practical Comparison
For many leadership teams, the practical differences between traditional hiring and a PDO model become clearer when viewed side by side:
| DIMENSION | FTE HIRING | PDO MODEL |
|---|---|---|
| Time to start | Months | Weeks (or less) |
| Flexibility | Fixed headcount | Elastic capacity |
| Hiring risk | Client-owned | Provider-owned |
| Management overhead | High | Significantly reduced |
| Delivery accountability | Distributed | Explicit and owned |
| Ability to scale down | Difficult | Built-in |
| AI capability adoption | Fragmented, evolving | Embedded and continuously improving |
This isn’t about cost alone. It’s about reducing friction in how work gets done — especially as AI accelerates delivery expectations.
Where PDO Works Especially Well
We see PDO models deliver the most value when:
- Roadmaps are ambitious and evolving
- Speed matters more than org-chart purity
- Leaders want predictable delivery without permanent overhead
- Teams need to scale now, not after a hiring cycle
- Quality and governance matter as much as velocity
- Organizations want to leverage AI effectively without building that capability from scratch
Importantly, PDO does not replace internal teams. It complements them, absorbing volatility so internal teams can stay focused on strategy, architecture, and long-term ownership.
A RevOps Perspective
From a RevOps standpoint, delivery capacity is a revenue enabler.
If execution lags:
- Launches slip
- Sales confidence erodes
- Customers wait longer for value
The PDO model aligns delivery capacity with business reality — allowing organizations to scale execution without introducing structural drag or misaligned hiring decisions in an AI-driven environment.
Final Thought
The choice between FTEs and PDO isn’t ideological. It’s situational.
The best leaders ask a simpler question:
What’s the lowest-friction way to turn strategy into delivery outcomes right now — given how fast the landscape is changing?“
Increasingly, PDO is part of that answer.
If you’d like to explore whether a PDO model makes sense for your organization, we’re happy to compare scenarios — objectively and without preconceptions.
We welcome a conversation. Contact us.
