Operating model·5 min read
Conway's Law, turned into something you can actually staff
Four team types and three ways they are allowed to interact. The constraint it optimises for is cognitive load, which is the one nobody budgets for.
Source
Team Topologies: Organizing Business and Technology Teams for Fast Flow
Matthew Skelton & Manuel Pais · IT Revolution · 2019
Read the originalAslanWay is not the author of this work. The summary below describes the source; the commentary that follows is ours and is not endorsed by the author.
What it argues
Skelton and Pais take Conway's observation and make it operational. Rather than describing why organisations produce the architectures they do, they propose a small vocabulary for designing the organisation deliberately.
Four team types: stream-aligned teams that own a flow of work end to end; platform teams that provide internal services; enabling teams that help others acquire capability and then leave; and complicated-subsystem teams for parts that genuinely need deep specialists.
Three interaction modes: collaboration, X-as-a-service, and facilitating. The discipline is that a given pair of teams should be in one mode at a time, and collaboration is expensive and temporary rather than a permanent state.
Cognitive load as the binding constraint
The book's central argument is that a team can only hold so much in its head. Spread a team across too many domains and delivery degrades regardless of headcount. The purpose of a platform team is precisely to absorb load so stream-aligned teams can go faster.
What we do with it
- The most common misuse is renaming existing silos to the four types without changing what anyone owns. If the platform team still needs a ticket raised for every request, it is not a platform team.
- "Platform as a product" is the useful test. If stream-aligned teams would not choose your platform when given an alternative, the platform is a tax and it will be routed around.
- DORA's 2025 research found 90% of organisations have adopted at least one internal platform, and that platform quality — not adoption — is what correlates with outcomes. This book is largely about that quality.