Platform engineering can improve developer experience, provide reusable platform services across an organization, and help teams deliver software more quickly without compromising trust and security. In practice, however, many platform teams struggle to achieve the level of adoption they expect. Some teams find themselves pulled into project-specific support work. Others build tools and standards that are technically sound, but rarely used, and as a result, the platform does not deliver the reusability or scale it was intended to provide.As a Red Hat consultant, I have worked on platform engineering initiatives directly and have also engaged with customer platform teams while working on modernization projects. Across these engagements, I have noticed recurring differences between platform teams that scale and those that remain stuck. These differences are not simply about technical maturity—they’re not only about whether the infrastructure is modern, or which internal developer portal (IDP) technology the team uses. What I’ve seen is that organizations that successfully scale platform engineering intentionally design the platform as a product: defining what value it provides, who it serves, how it is adopted, and where the platform team’s responsibility begins and ends.What happens when platform engineering does not scaleWhat does it mean for platform engineering to scale?A commonly referenced platform engineering maturity model from the Cloud Native Computing Foundation (CNCF) captures this well. It defines several areas of maturity and describes the progression from early, provisional practices toward more scalable and optimizing operating models.The platform teams I see struggling most often are unable to move beyond the first level of maturity. They are pulled in many directions by users and stakeholders. Some spend much of their time building one-off tools or providing project-specific support. Others push standards too aggressively and are eventually ignored.Why does this happen?One reason is that platform engineering does not always have clear boundaries with adjacent practices such as DevOps or site reliability engineering (SRE). Because those boundaries are poorly defined, stream-aligned team members do not always find it obvious which of those teams to ask for what.The same ambiguity also attracts a wide range of business expectations. Over time, every problem can start to flow toward the platform team, which becomes what I call a “bucket for every problem.” The team must spend its own cognitive capacity deciding how to respond to all these requests, which reduces the capacity available for designing, building, and operating reusable platform services.To avoid this, platform teams need to move away from handling expectations one by one. They need to clearly define what value they provide, how far their responsibilities extend, and how that definition will be accepted across the organization. Expectations management is a crucial part of platform strategy.Product strategy: Platform as a productA common approach to this challenge is to treat the platform as a product. That’s the right attitude in theory, but it is often easier to say than to execute.A practical product strategy for platform engineering needs to answer several specific questions:What problem is this platform initiative trying to solve?Who is the platform user?What journey is that user on, and what problem do they face in that journey?Where are the boundaries of the platform team’s responsibility?How will the platform be discovered by potential users, evaluated, and adopted?How will customer (developer) satisfaction be measured and taken into account in future product iterations?Let’s take a closer look at the steps needed to ensure success as you turn your platform into a product.Start with the problem statementProduct strategy always starts with a clear definition of the problem. Platform engineering is often pitched as a way to reduce cognitive load, but cognitive load by itself is not the primary problem an organization needs to address—it's usually a cause or symptom. The real question is: What business or organizational problem is important enough to justify investment?Different problem statements lead to different platform services. For example, consider 3 organizations:One organization’s top priority is reducing developer turnover.Another wants to reduce cost through more effective use of modern platforms.A third wants to reduce security and compliance variation across application teams and better safeguard the software supply chain.All 3 might say they are doing platform engineering. But the platform services they should design to meet their goals will be different.In the first case, the platform may need to focus on developer experience, onboarding, and reducing friction. For the second organization, standardization, reusable migration patterns, and operational efficiency may matter more. And the third organization’s platform may need to provide secure-by-default delivery paths, trusted templates, approved base images, automated checks, and policy-driven deployment workflows. Accurately defining the problem statement early in the process is paramount for successful implementation.Identify the real platform userThe next question is: Who actually chooses the platform?In some organizations, developers research and select the platform directly. In others, the developer is not the primary decision maker.In one organization I observed, most software development was outsourced to external development partners. The platform team improved the developer experience of its platform services, but adoption still did not increase.When Red Hat Consulting investigated the situation, we found that internal teams were primarily organized around project managers. The external development partner often recommended which platform would be appropriate for a given project. However, the project manager was responsible for communicating internal constraints, rules, and standards to the partner.The problem was that project managers were not providing information about the organization’s development platform. In many cases, they did not even realize that they were expected to do so, or that the relevant resources existed. In that context, developers were not the only platform users. The platform service needed to be designed taking into consideration the project manager as a key persona, because the project manager controlled the information flow that enabled adoption.In another organization, the need was a platform service for citizen developers—that is, developers within the organization who work in departments outside of IT, like sales or finance—using an AI development environment. In that case, the users were citizen developers, but the organization’s AI Center of Excellence also needed to be considered as a user group because it was responsible for enabling AI adoption across the organization.The point is simple: the platform may provide development tools, but the platform user is not always the person writing code.Understand the journey and the problemOnce the user is clear, the next question is: What journey is that user on?