Why Software Teams Slow Down as They Grow?
And How to Fix It by Design
Headcount goes up, but delivery doesn't get faster
More engineers should mean faster delivery, but the opposite often happens as teams scale.
Meetings multiply, and progress feels slower with every quarter
Coordination overhead grows exponentially, consuming time that should be spent building.
The real bottleneck isn't talent … it's the hidden drag no one is naming
The issue lies deeper than skills or tools - it's in the systems that surround your teams.
The Wrong Diagnosis
Common Misdiagnosis
- Not enough talent
- Wrong tools
- Poor planning
Typical "Solutions"
- Hire more engineers
- Implement stricter processes
- Add better toolchain
The instinctive diagnosis is familiar and the proposed remedies are equally predictable. These prescriptions are comforting. They are also, in many cases, counterproductive.
The real issue lies deeper. It's not about the specific tools, but in how teams are expected to operate. Delivery often doesn't degrade because the people get worse; it degrades because the systems around them become harder to move through.
The "Engineering" becomes easier. The orchestration becomes the bottleneck. Teams spend more time navigating internal systems than solving actual problems, creating a hidden tax on productivity that compounds with every new hire.
A Real-World Case Study
We've seen this up close, including at a global enterprise with a streaming platform serving over 15 million concurrent users. Five delivery teams hit their deadlines while the other 20 teams lagged, despite having similar skill and scope.
The Traditional Approach
The traditional infrastructure track focused on building the perfect toolset: complete, integrated, and hard to adopt. It was technically sound, but slow to land. Teams struggled with complex onboarding processes and rigid tool requirements. Focused on:
- Perfect toolset integration
- Complex adoption process
- Stakeholders add rules and blockers
- Weeks to onboard new applications
The Breakthrough Method
Meanwhile, the five teams we worked with agreed on a minimum viable Path to Production: a shared delivery contract that doesn't require alignment on tools at first. Tool enforcement comes later. The first priority was getting alignment on principles between key stakeholders. Focused on:
- Being firm on principles and flexible on tools
- Optimizing for adoption
- Stakeholder rules baked into platform
- Less than a day to onboard
The difference wasn't talent. It was their priorities.
The Key Difference
Change management stopped being a bottleneck, because the Path to Production itself gave them more clarity through automation than ever before.
This isn't a story about hero teams or better tech. It's about how having a shared agreement on the design of the path from "idea" to "delivered" can quietly shift the trajectory of a organization, especially as complexity scales.
Defining the Path to Production
A common contract between stakeholders that defines how work moves forward and what it must go through before it's released.
Benefits of a Well-Defined Path
Done well, these agreements strip away bureaucracy and replace it with confidence built through engineering, enabling teams to move with greater autonomy, speed, and safety.
The Drag You Can't See (But Feel Every Day)
As organisations grow, they accumulate a kind of invisible weight. It comes in three main forms that collectively create a compound effect on team performance:
Delivery Friction
A thousand small barriers, unclear handoffs, opaque approvals, manual reviews, that collectively slow teams to a crawl. Each individual step seems reasonable, but together they create an obstacle course.
Cognitive Load
Developers spend more time figuring out how to deliver than solving business problems with software. The orchestration required becomes harder to reason about than the code itself.
Coordination Tax
More people means more meetings, more dependencies, more time spent aligning rather than advancing. Communication overhead grows exponentially with team size.
These forces don't show up in sprint reports, but they shape everything. And many of the usual "fixes": more headcount, more layers, more tools; tend to make things worse. This isn't about a lack of intelligence or effort. It's about friction that quietly builds up over time.
Without strategic design of the path to production, it's like a badly signposted motorway: the cars are fine, they just keep missing the turn.
Platform Thinking, Done Properly
The prevailing term for the response to this is "platform engineering." It is often mischaracterised as building internal tools or automating infrastructure. In practice, it's closer to designing a usable system for delivery, a consistent interface between engineers and the capabilities they rely on.
True platform thinking goes beyond tool consolidation. It's about creating coherent, well-designed experiences that reduce cognitive load and enable teams to focus on their core mission: solving business problems through software.
The best platforms feel invisible to their users - they provide powerful capabilities without requiring deep knowledge of the underlying complexity. They abstract away the difficult parts while maintaining flexibility for teams that need it.
Designing for Enablement, Not Control
Good platforms don't impose. They enable. They give delivery teams the ability to self-serve environments, deploy code, meet compliance, all without opening tickets or attending extra stand-ups. They reduce the burden of remembering how everything works, and make the right way the easiest way.
Self-Service Capabilities
Teams can provision environments, deploy code, and access resources without waiting for approvals or manual interventions. Automation replaces bureaucracy.
Engineer-as-Customer Mindset
Platforms treat engineers as customers - literally. People with goals, constraints, and finite tolerance for friction, with better things to do than decipher five different ways to spin up a staging environment.
Right Way = Easy Way
Well-designed platforms make compliance, security, and best practices the path of least resistance. Good behavior becomes automatic rather than enforced.
This approach fundamentally shifts the relationship between platform teams and delivery teams from one of control to one of service. The platform exists to amplify the capabilities of delivery teams, not to constrain them.
Scale That Actually Works
This thinking scales. In one platform we built, over 1,000 engineers work through a common multi-tenant system. More than 500 applications ship daily via a common Path to Production
93%
Time Reduction
Environment provisioning dropped from two weeks to 15 minutes
100%
Coverage
Observability, security and change management embedded by default
6000+
Daily Deployments
Applications shipping through unified interface
Teams move faster, not because they were pushed, but because the road is paved. The platform provides a foundation that scales with the organization, maintaining consistency while preserving team autonomy. This isn't about standardization for its own sake - it's about creating leverage that compounds over time.
When application teams don't think about the platform and focus on their products, you know you've succeeded.
The Path To Production as a Product
Every engineering organisation has a delivery system. Few treat it as something worth designing.
But that Path to Production, from 'idea' to 'delivered', is the main interface engineers use every day. If it's inconsistent, fragile, or overly bespoke, even the best teams will slow down.
Design it well, and you create leverage. Design it poorly, or not at all, and even world-class engineering becomes frustrating to scale.
Good Design
Creates leverage Enables scale
Poor or No Design
Frustrates engineers Limits scalability
You don't need to centralise everything. You don't need to control everything. But you do need to make the path clear, and treat that clarity like a product.
Because in the end, it's not the code that slows teams down. It's the path it has to travel.
Where To Start
You don't need to get everything right at once. But you do need to begin treating delivery friction as a first-class problem and platform design as its most effective long-term fix.
"If we weren't allowed to hire one more engineer next year, how would we go faster?"
Brave asking that question. You might be surprised at what you uncover.
A Simple Starter Toolkit
Embark on a journey to optimize your processes and accelerate progress with these initial baby steps.
1. Map Your Current Reality
- Document every step from code commit to production deployment.
- Include handoffs, approvals, manual processes, and waiting periods.
- Identify friction points like where teams get stuck or require manual intervention.
2. Align on a Path To Production as a contract
Focus not on which tools, but on the steps, what must happen for code to move safely and confidently to production. Talk about stages of testing, and outlaw the mentions of specific tools for that conversation. Just draw the lines, boxes and the purpose of each step.
3. Show, don't Tell
- Make it real. Build a default opinionated Path to Production as a reusable pattern.
- Find an early advocate customer/team to prove it with. Bring them close by serving them.
- Prove it with one team, while keeping others informed and inviting feedback.
- Value their perspective, especially the pain, as they're your litmus test for the rest.
4. Measure time-to-first-deploy
Not just team velocity, but activation. How long until a new app or service is live in a real environment?
5. Treat delivery teams like customers and check in regularly
- Get direct feedback from engineers
- Ask them how easy the path to production feels
- Treat those insights like customer data
- Make adoption support part of your team's job.
The goal isn't just to build capabilities, but to ensure they're trusted, easy, and actively used.
We'd Love to Hear Your Thoughts!