In large organizations, engineering systems refer to the tooling and infrastructure that make software delivery possible. This includes build systems, CI pipelines, deployment workflows, test automation, templates, and the internal platforms that support them. These systems are often owned by platform teams whose job is to provide a stable and scalable foundation for all products.
Product teams, on the other hand, own the features that customers use. They work inside real codebases, run builds every day, triage failures, and ship continuously. Their priorities move quickly because their work directly affects users and business outcomes.
Both groups are important, but the distance between them has a major effect on how fast software is delivered.
Over the years I have seen several organizational models for engineering systems across different products and teams. The difference in outcomes always comes down to one factor. How close the owners of the system are to the act of shipping software.
Model 1. Central platform ownership
A central group builds and maintains shared engineering systems for every product. They own CI, pipelines, build infrastructure, templates, and compliance. The idea is scale through consistency.
In practice, this model rarely keeps pace with real product needs. I have never seen a fully centralized system move at the speed required. Even the teams I have led could not close that gap. The limitation is structural. Once a team operates outside daily product development, priorities drift, alignment cycles grow, and the distance from active work slows everything down. The platform may look polished, but the iteration experience usually feels slow for engineers building features.
This is not a talent issue. Platform teams have strong engineers. The problem is the unavoidable distance from the delivery loop.
Many attempts are made to reduce this distance. One common strategy is embedding platform engineers into product teams so they can experience real workflows. This helps, but it does not solve the root problem. Embedded engineers gain context, but ownership and decision making remain external. Improvements still lag behind real needs.
Model 2. Fully local product ownership
Each product team owns its repo, build, test, and deployment flow. They feel every slowdown directly. When a build begins to drag, they fix it. When the pipeline flakes, they know exactly where. The system evolves from real issues rather than abstractions.
There is a challenge here. Product leadership often pushes for more features and faster customer outcomes, so investment in tooling or build systems can feel secondary. This pressure is usually how Model 1 grows. When product teams deprioritize engineering system work, responsibilities shift upward and eventually form a centralized platform group.
Even with this tension, product owned systems tend to produce healthier iteration because the people closest to the workflow understand its impact. Improvements may start small, but they are relevant, fast, and grounded in reality.
Model 3. Virtual cross team engineering task force
In this model, a small group of engineers from each product team forms a virtual task force. They collaborate to fix shared engineering system problems, align standards, and build solutions intended to work across all products. Members stay embedded in their product teams, which keeps them connected to daily development workflows.
This model has strong intent and more context than a central platform team.
The real challenge is sustaining it. A virtual group depends on engineers who still report to their product leads, and each product team has its own roadmap pressures. Keeping contributors engaged becomes a political negotiation. Every improvement requires agreement across multiple teams that may not share priorities or timing. Even when everyone believes the work is important, no team wants to sacrifice feature velocity to fund shared foundation work.
The work slows not because of technical difficulty, but because participation, capacity, and prioritization are spread across many teams.
It is a meaningful improvement over a central platform model, but it still carries friction that local ownership avoids.
The pattern across all models
The more distance between the engineering system and the people shipping the product, the slower the system evolves. The closer the ownership is to the delivery loop, the more accurate and timely the improvements become.
Engineering system work is not a tax on product teams. It is a multiplier. A strong build pipeline, fast feedback loop, reliable deployment flow, and stable tools amplify every engineer on the team. This matters even more in the age of AI where developers can write, delete, and rewrite code faster than ever. None of that speed matters if the build takes minutes or the pipeline flakes. AI increases the rate at which developers generate change. Engineering systems determine how quickly that change becomes working software.
Why product owned systems win
Product engineers:
- feel failures immediately
- know exactly where friction lives
- test improvements inside real workflows
- move without alignment cycles
- fix problems that matter today
- design systems around real delivery work
When improvements grow inside the product loop, they are relevant and easy to adopt. Improvements created outside that loop often arrive late or miss the real issues.
Scaling this model without chaos
Local ownership does not mean fragmentation. The healthiest structure looks like this:
- product teams own their pipelines and build flow
- solutions spread because they work
- a small central group curates shared components
- adoption is earned, not mandated
- guidance grows from working code rather than policy documents
This keeps iteration fast while maintaining consistency.
Final thought
Engineering systems perform best when they evolve from the people who ship the product. Distance slows everything. Proximity creates momentum. If the goal is faster cycles, smoother builds, and reliable releases, the path is simple. Put ownership where the real work happens and support it with shared guidance instead of centralized control.
If you are working on similar challenges, I would be happy to connect.