Designing Platform Teams Around Cognitive Load, Not Org Charts

As "platform engineering" has become a trend, many organisations have done the same thing: draw a box on the org chart called "Platform Team" and move a few infrastructure-minded engineers into it.

Sometimes this works. Often, it does not.

Teams still struggle to ship. Cognitive load stays high. Everyone is less sure who owns what. The diagram changed, but the delivery experience did not.

A more useful way to design platform teams is to start from cognitive load, not organisational lines.

In this article, we look at what that means in practice.

What We Actually Want Platform Teams to Do

If we strip away the buzzwords, platform teams are meant to:

• reduce the amount of infrastructure and tooling detail product teams must hold in their heads,
• provide safer, faster paved roads for common behaviors (deploy, observe, secure),
• and make it easier for teams to do the right thing by default.

That is fundamentally a cognitive load problem:

• How many systems does a team have to understand to ship a change?
• How many different concepts and workflows do they need to remember?
• How often do they have to stop and ask, "how do we do this here?"

If a platform team is not measurably lowering that load, it is just moving boxes on a chart.

Why Org Charts Are a Bad Starting Point

Org charts are optimised for reporting and management, not for cognitive load.

Common patterns we see:

• A platform team formed by collecting people who "own" certain tools (Kubernetes, CI, observability), regardless of how those tools show up in product teams' daily lives.
• Teams mirrored after existing reporting lines ("backend platform", "data platform", "security platform") without thinking about where work actually flows.
• Platform scope defined by who happens to be available, not by what most increases or reduces load.

The result is often:

• fuzzy boundaries – no one is sure whether a request belongs to the platform or product teams,
• duplicated complexity – the platform exposes many of the same concepts, just behind a new interface,
• and platforms that are hard to evolve because they are tied to internal politics rather than system needs.

Thinking in Cognitive Load First

Designing platform teams around cognitive load starts from a different set of questions:

• Which repeated tasks cause the most friction across multiple product teams?
• Where do teams frequently say, "we know what we need to build, but the plumbing is slowing us down"?
• Which areas generate the most "how do I…" questions on internal channels?

These are signals of excess load.

From there, we can ask:

• What would it look like if this concern was encapsulated behind a simpler interface?
• Which responsibilities truly belong to a shared platform, and which should stay with teams?
• How many new concepts would we introduce if we created a platform for this problem?

The goal is not to centralise everything. The goal is to centralise the right things in a way that makes everyday work simpler for most teams.

Shaping Platform Teams by Flow, Not Hierarchy

Once we know where cognitive load is too high, we can shape platform teams around flows instead of reporting lines.

Examples:

• A delivery platform that owns build, test, and deploy workflows across services, with a clear contract: "given a service that meets these criteria, we can take it to production reliably."
• An observability platform that standardises how metrics, logs, and traces are collected and explored, so teams spend less time wiring tools and more time interpreting signals.
• A data access platform that provides safe, audited ways for teams to consume and publish data, without each team re-inventing governance.

Each of these:

• is aligned with a stream of work teams already care about,
• has a clear definition of "done" for its responsibilities,
• and has obvious measures for whether it is reducing cognitive load.

Avoiding the "Everything Platform" Trap

A common failure mode is the "everything platform":

• Every new cross-cutting concern is thrown at the same team.
• The backlog fills with unrelated requests.
• The platform team becomes a bottleneck and a source of frustration.

Designing around cognitive load means being opinionated about scope:

• Which cognitive burdens are we committing to own?
• Which will we explicitly not own – and how will we communicate that?
• When a new concern appears, do we extend an existing platform capability or is this a separate stream?

Sometimes the right answer is to say no – or at least, "not yet" – so that existing platform capabilities stay healthy.

Measuring Whether Platform Teams Are Shaped Well

If we design platform teams around cognitive load, we should also measure them that way.

Useful signals include:

• Lead time changes for teams using the platform vs those not using it.
• Onboarding time for new engineers to become productive.
• The volume and nature of support questions about infrastructure and tooling.
• Whether incident reviews show the platform clarifying or obscuring what happened.

We also listen for qualitative indicators:

• Do product teams describe the platform as "helpful" or "in the way"?
• Do platform engineers have a clear story about which problems they own?

These are not vanity metrics; they tell us whether the team shapes match the cognitive load they were meant to relieve.

How We Approach Platform Team Design at Fentrex

When we think about platform teams, we treat them as a tool to reshape where thinking happens, not just where code runs.

We ask:

• Which kinds of thinking should be shared across teams (e.g., security controls, observability patterns, deployment mechanics)?
• Which should stay close to the product domain (e.g., feature trade-offs, domain models, user journeys)?
• How can we encode the shared thinking into platforms that are boring to use, but powerful in their impact?

The resulting teams may or may not line up cleanly with the existing org chart. That is fine. The point is for the system of teams to have a healthier distribution of cognitive load.

Questions to Ask About Your Current Platform Teams

If you look at your current organisation and wonder whether platform teams are shaped the right way, a few questions can help:

• If we removed the platform team tomorrow, what cognitive load would return to product teams?
• Are we seeing fewer "how do I…" questions, or just different ones?
• When incidents happen, do platform responsibilities make cause and ownership clearer or fuzzier?
• Do our platform roadmaps follow org charts, or do they follow the real pain teams feel in day-to-day delivery?

Answering honestly will tell you whether your platform teams are designed around cognitive load, or whether they are still shadows of the org chart.