In the never-ending quest for developer productivity gains, a new default setting has been applied to engineering leadership teams: buy an AI coding tool.
It’s an understandable instinct. AI can now produce code in seconds, and vendors promise gains measured in hours saved per engineer, each week. But for most teams, the results are underwhelming. Delivery timelines barely budge, and the sense of “we’re moving faster” fades.
The problem isn’t with the tools, it’s with the target. Most of the friction that slows teams has nothing to do with coding, because the real bottlenecks live in the 84% of a developer’s job that happens outside of coding.
Why coding tools don’t fix the real problem
The writing on the packet says AI coding assistants can save developers significant amounts of time.
Coding only makes up about 16% of a developer’s week, and it’s the part they experience the least amount of friction. The rest of their work week is spent on more cumbersome tasks like searching for information, clarifying requirements, attending meetings, and finding time to pay down tech debt. By focusing on coding efficiency, we miss the glaring friction points that are slowing down the end-to-end software delivery cycle.
One major drain on developer productivity is switching context between tools.
Modern-day developers need to navigate a maze of disconnected tools and scattered information. Jira, GitHub, Slack, email, and documentation hubs hold pieces of the context puzzle but never the whole picture. The constant context switching causes costly mental resets that quietly eat away at momentum.
This isn’t a glamorous problem to solve, and it doesn’t have a nice ring to it like “AI writes your code for you”, but it is a productivity drain. One that erases the very gains AI coding tools promise to give back.
AI beyond coding – tackling the other 84%
The real opportunity for AI is not to write more code but to streamline the work around it.
For example, leveraging AI to keep documentation updated means people can self-serve the information they need, when they need it. Using AI to bridge the gap between Jira tickets, GitHub PRs, and Slack conversations, they’d have a coherent thread of context.
Using AI to solve the points of friction developers face, they’re happier and able to deliver value faster. These gains dwarf any benefit code generation alone can provide.
Leadership’s role – align before you automate
This shift in thinking starts with leaders. Too often, AI investments are made without first understanding where time is truly being lost.
The most effective leaders conduct developer experience audits to uncover bottlenecks and then work with teams to address them. Importantly, developers also need to articulate their challenges in business terms.
If extended Pull Request cycle time is reframed as a missed feature launch or delayed revenue opportunities, it’s easier for leadership to prioritize addressing it. When leaders and developers align on the real sources of friction, AI can be applied in ways that deliver measurable results.
The future is outside the IDE
The next leap in developer productivity won’t come from squeezing faster coding, it will come from eliminating the inefficiencies that surround it.
Leaders who focus on the 84% of time where the bulk of delays occur will see faster delivery cycles, higher AI ROI, and teams that are not just more efficient, but more engaged.
The message is simple – stop buying more speed for the wrong part of the process. Start removing everything that slows developers down before they even start typing.
Andrew Boyagi has led multi-disciplinary technology teams for over 20 years across some of Australia’s largest enterprises. Most recently, Andrew was an Executive Manager at the Commonwealth Bank of Australia where he led the development of an internal development platform, supporting the experience of over 7,000 engineers. Today, Andrew leads the DevOps Evangelism team at Atlassian where he regularly meets with Fortune 500 companies, traveling the world sharing insights and guidance on optimizing for high-performing and engaged software teams and leadership.