Full Title: The State of Developer Experience in 2025
Highlights
This year in particular, we sought to understand more about how development teams use AI. We revisited teams’ feelings towards their own productivity, what’s working well for them, and which roadblocks are continuing to challenge their workflows. (View Highlight)
AI tools are producing more value: 68% of developers reported a sizeable time saving of more than 10 hours a week from using AI. This is a significant jump from last year, where 54% of developers said they were yet to experience significant productivity benefits by using AI. (View Highlight)
A widening gap between leaders and developers: An increasing number of developers are reporting that leaders don’t understand their pain points: A strong majority (63%) feel top leaders at their organization don’t understand the challenges developers face in their roles, up from 44% reported in last year’s survey. (View Highlight)
Developers are still losing valuable time to non-coding tasks: 50% report losing 10+ hours per week, and 90% lose 6+ hours or more, largely due to organizational inefficiencies. (View Highlight)
Generative AI (GenAI) is a workhorse: 68% of developers report a time savings of more than 10 hours a week using GenAI, with significant gains for non-coding tasks.
Managers and developers are closely aligned on AI gains: 70% of managers saved more than a quarter of their time.
AI is reshaping a developer’s workweek: A majority of developers are using their AI time savings to focus on improving code quality. (View Highlight)
In our 2024 State of DevEx report, we saw a disconnect between leadership’s expectations of AI and the everyday reality for developers. While a majority of managers ranked AI as the number one solution to improving developer productivity and satisfaction, surprisingly, only 38% of developers reported any time saving at all. (View Highlight)
This year, we wanted to circle back on the state of developer sentiment around AI, tools being used, and areas where AI is adding value for teams. Things have changed significantly.
A majority of developers are now relying on AI for a lion’s share of their tasks, saving over a quarter of their workweek. Managers have also made improvements in understanding their team’s usage. When asked again this year about how AI is improving team productivity, managers were aligned with their developers, reporting time savings on par with what their teams were sharing. (View Highlight)
Generative AI is a workhorse Most developers shared that they are using Generative AI (GenAI) tools to save time, with 68% reporting saving more than 10 hours a week across all of their workflows. While numerous reports study time savings on coding tasks, this survey focused on the holistic impact of GenAI across the entire working week.* (View Highlight)
This is a sizeable jump from last year’s survey, where 54% of developers reported only slight or moderate improvements to productivity* from leveraging AI tools. (View Highlight)
: Leaders and developers are finding common ground on GenAI 70% of managers reported that their team, as a whole, saves 10+ hours a week with GenAI Interestingly, managers and developers are closely aligned on how much time GenAI is saving their teams.
When asked how much time GenAI tools save their developers on tasks they would otherwise perform manually, 70% of managers said more than a quarter of their time. (View Highlight)
AI is reshaping a developer’s workweek So, how are developers spending that extra time? The top priority: improving code quality. Close behind were building new features, enhancing engineering culture, and developing documentation – all sharing nearly equal attention.
This is great news for companies – developers are completing tasks more quickly and using the time they save to improve quality and develop new features. As companies start leveraging GenAI for more tasks outside code assistance, these gains will compound. (View Highlight)
enAI is versatile beyond the code When asked what tasks they use GenAI for beyond coding, developers shared a closely distributed breakdown between five tasks: search and finding information, testing, writing and improving documentation, automating workflows, and chat, or sparring with AI.
Non-coding tasks developers report using GenAI for 1. Search and finding information 2. Testing 3. Writing and improving documentation 4. Automating workflows 5. Chat, or sparring with AI (View Highlight)
The state of developer productivity: a snapshot Growing empathy gap between leaders and developers: A strong majority of developers (63%) feel top leaders at their organization don’t understand the challenges and pain points developers face in their roles, up by 19% from last year’s survey.
AI adoption is rising, but friction persists across the software development lifecycle: Developers are losing valuable time to non-coding tasks: 50% report losing 10+ hours per week, and 90% lose 6+ hours or more, largely due to organizational inefficiencies Alignment = increased productivity: When managers work to understand developer pain points we see higher levels of productivity. Less time lost to obstacles and inefficiencies correlates directly with higher satisfaction with developer experience investment. (View Highlight)
Organizational inefficiencies continue to disrupt developer workflows Even with the rise in AI adoption and a growing ecosystem of developer tools, developers are still experiencing disruptions that take them out of flow. 50% of developers now report losing more than 10 hours of their working week due to inefficiencies. From fragmented workflows to time lost searching for information, these persistent friction points continue to limit the full potential of AI gains. (View Highlight)
Our survey findings highlight some common challenges worth looking into: Finding information: When teams are able to self-serve information, they are 4.9 times more effective, 4.4 times more productive, and 4.4 times more adaptable.
Cognitive load: The need to constantly search for information is a major contributor to cognitive load. According to the 2024 Stack Overflow Developer Survey, 61% of developers spend more than 30 minutes a day searching for answers to problems.
Tech debt: Technical debt slows down development and increases costs. It can lead to more bugs, limit scalability, and lower team morale. If left unaddressed, tech debt can hurt the user experience and make it harder to adapt or grow the product. (View Highlight)
‘Finding information’: AI’s core advantage still stumping devs ‘Finding information’ emerged at the top of the leading causes of time waste for development teams. What is interesting is that ‘finding information,’ along with the second and third friction points (new technology and switching context between tools) are AI mainstays. With teams reporting increased adoption and higher time savings, you would expect to see a decrease in these pain points that AI is designed to address. (View Highlight)
The report also found that teams with easy access to self-serve information are 4.9 times more effective, 4.4 times more productive, and 4.4 times more adaptable. (View Highlight)
Atlassian’s Rovo CLI is one example of an agentic CLI experience that brings intelligent development assistance directly to the terminal. It enables developers to interact with an AI agent using natural language for tasks like asking for documentation, summarizing code changes, or publishing updates as part of their workflow.
By connecting Rovo CLI to the MCP (Model Context Protocol) server and IDE extensions, developers can generate, update, and retrieve documentation directly from the editor, reducing context switching and manual search. The MCP server becomes a central hub that integrates knowledge management and project management tools like Confluence and Jira. (View Highlight)
Tackling the 84% of the work week spent outside the IDE If you recall from the beginning of the report, 68% of developers are saving 10+ hours a week using AI.
That’s a significant time-saving! And there’s still room for improvement, when we consider that a greater percentage of developers are dealing with 10+ hours a week of friction due to organizational inefficiencies.
When we scan the landscape of developer AI solutions today, most capabilities focus on coding. It’s easier – and more tempting than ever – to automate developers’ favorite part of the job. (View Highlight)
Category Code generation Documentation generation Pull request summaries Unit test generation Capabilities Using AI to write or help write code Using AI to write code or procedural documentation AI creates a summary of the changes contained within a Pull Request AI automatically suggests or creates unit tests for changes in a Pull Request (View Highlight)
While optimizing coding time matters, the bigger opportunity lies in reducing friction across everything else. That’s where AI can make a transformative impact – streamlining non-coding tasks and improving the overall developer experience.
Teams that collaborate with AI see exponential gains in performance and output, giving their organizations a competitive edge. Leaders can accelerate this shift by spotlighting internal success stories – showcasing how developers are using AI to elevate their work provides both inspiration and a blueprint for others to follow. (View Highlight)
