GCP – AI will break the stagnation in developer productivity, but only if you do it right

“Continuous improvement” is an upbeat term that we like to throw around in technology circles. Let’s keep getting better! Who can argue with that? But realistically, nothing and no one improves continuously. We grow, we plateau, regress a bit, grow again, and so on. If we’re being honest, that “plateau” stage can sometimes last a long time, and we need a jolt to trigger our next climb to new heights. For many organizations, developer productivity has been “stuck” for a while now. Could AI be the thing to shake it loose? We just published a new paper that makes the case that it will.

The topic of developer productivity came to a head in the second half of 2023, as people debated new ways to measure software delivery performance. How do you actually measure software developers? Do you just look at output and activity? What about outcomes and impact? Should we be looking at individuals or teams? In some respects, it seems like we’ve flatlined on some of the team-based measures of productive activity. For example, adoption of core delivery capabilities like continuous integration and continuous deployment hover at 30% year after year. Developers are asked to do a lot — too much, if I’m being honest — and it feels like we’ve hit a plateau on how much more we can do. Until something changes.

Something did change. I’m talking about the mainstreaming of generative AI. It’s already changed how we work. From brainstorming and prototyping, to coding and infrastructure optimization, we finally have tools that can break the productivity logjam. This new class of tool stands to fundamentally alter significant portions of the software development lifecycle and help us do more, with less effort. 

This new paper is for team and organization leaders. It explores what it means to measure developer productivity and how generative AI will make a difference. We look at frameworks like DORA and SPACE, offer questions for assessing your own organization’s approach to developer productivity, and then explain how AI-assisted developer tooling improves your productivity outcomes. Just throwing powerful tools at your team won’t yield the benefits you’re hoping for. But if you have the right frame of mind on productivity while creating an excellent developer experience, we believe that the introduction of AI assistance to your developers will have a generational impact on their productivity.

To read more, download the paper here.