There’s an ongoing debate about whether your R&D teams should be cross-functional (composed of full-stack, data engineers, AI specialists, etc.) or uni-functional (grouped by a single profession within a dedicated team). Let’s break down the pros and cons of each structure before drawing conclusions.
Uni-Functional Teams
Uni-functional teams are optimized for leveraging specific technical expertise. This structure helps drive higher code quality, adherence to best practices, and efficient code reuse, as team members naturally align on principles related to their shared profession. Additionally, career paths are clearer—engineers tend to look up to the tech lead as a role model within the same field.
However, one major downside is that uni-functional teams are not self-contained when it comes to delivering product or business outcomes. These teams need to collaborate with others to achieve shared goals, which can lead to inefficiencies and multiple handoffs. Without a clear owner of the full picture, execution can become fragmented.
Cross-Functional Teams
On the flip side, cross-functional teams are self-contained and optimized for end-to-end execution. These teams bring together all the necessary disciplines to deliver an initiative with autonomy, speed, and minimal dependencies. A typical cross-functional team might have a tech lead responsible for system architecture and technical design, while ensuring high standards across the board.
The trade-off here is that cross-functional teams can lead to silos in terms of best practices, libraries, and tools. You may end up with duplicated efforts, multiple repositories, or fragmented processes, as teams optimize for their own immediate needs rather than a unified R&D approach.
Finding the Right Balance
As you can see, there’s no one-size-fits-all approach. In smaller companies, I tend to lean towards uni-functional teams, as it allows me to build strong foundations—shared libraries, tools, and best practices—that will scale as the company grows. It also encourages redundancy and knowledge sharing across the organization. In these cases, forming cross-functional execution pods—by borrowing the necessary professionals from uni-functional teams—works well for executing initiatives without losing alignment with the broader technical strategy.
In larger organizations, I’ve found success with organic cross-functional teams supplemented by technological guilds. These guilds bring representatives from different teams together to agree on best practices and drive the overall technological strategy, including addressing tech debt.
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