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A recent survey conducted by GitHub in association with Wakefield research sheds light on the impact of artificial intelligence (AI) on the developer experience. The survey, which involved 500 US-based developers from companies with more than 1,000 employees, focused on key aspects of their careers, such as developer productivity, team collaboration and the role of AI in enterprise environments.
According to the findings, 92% of developers are already using AI-powered coding tools in their work. But despite investments in DevOps, developers still face challenges. Waiting for builds and tests is their most time-consuming task. They also expressed concern about repetitive tasks, such as writing boilerplate code. They strive to free up more time to collaborate with colleagues, acquire new skills and create innovative solutions.
GitHub stated that these statistics indicate a growing need to improve efficiency in the development process.
“We found that developers spend most of their time writing code and testing, then waiting for the code to be reviewed or builds completed,” Inbal Shani, chief product officer at GitHub, told VentureBeat. “We also found that AI-powered coding tools enable individual developer productivity and better team collaboration. That means generative AI helps developers generate more impact, increase satisfaction and build more innovative solutions.”
The company suggests business leaders should prioritize their developers by identifying areas of friction, removing productivity barriers, and fostering growth and momentum. Developer experience, the research shows, has a major impact on productivity, satisfaction and impact.
Collaboration emerged as an essential aspect of the developer experience. Developers in enterprise environments typically collaborate with an average of 21 engineers on projects, making their collaboration skills important in their performance assessments. More than 80% of developers believe AI-powered coding tools can improve team collaboration, improve code quality, accelerate project completion, and improve incident resolution.
“Collaboration is the power multiplier for larger engineering teams to benefit and drive customer outcomes. Every organization should use this equation to put developers at the center of customer empowerment,” added GitHub’s Shani.
In the survey, developers also expressed the wish for more opportunities to train and increase impact. They ranked learning new skills, receiving feedback from end users and designing solutions to new problems as key elements that positively impact their workday.
What developers need in today’s growing AI ecosystem
The study took a closer look at the impact of AI-powered coding tools on individual performance. An overwhelming majority of developers (92%) reported using AI-powered coding tools, with 70% believing these tools give them an advantage at work.
Developers said they see AI as an opportunity to focus on designing solutions and developing skills, such as learning new programming languages and frameworks. They also claimed that the integration of AI coding tools aligns with the goal of improving the developer experience.
In fact, Github’s Shani expects the 92% figure to have already risen since the study was conducted in March 2023. “We’ve already seen this impact from our customers using GitHub Copilot,” said Shani. “These developers are 75% more satisfied with their work and are already writing code more than 55% faster.”
Shani stated that AI has the potential to significantly improve several aspects of the developer experience. These include speeding up code delivery, facilitating intelligent code reviews, improving codebase collaboration, and resolving development disruptions that typically require more cognitive effort.
As AI models progress and additional functionality is developed, she says, we can anticipate a fundamental redefinition and improvement of the developer experience, developer productivity and team collaboration.
Upskilling, productivity the main benefits of AI tools
The study identified upskilling as the top benefit, followed by productivity gains. Integrating AI-powered coding tools into the developer’s workflow was seen as an opportunity to improve performance and better adhere to existing standards.
Developers said acquiring new skills and creating innovative solutions had the greatest positive impact on their work.
“AI developer tools will soon become the stakes and organizations that fail to make this change will be left behind. Having AI tools becomes an expectation of all developers as a central tool to do their job,” added Shani. “If industries want to hire and retain top talent, they need to be able to provide the best tools to make developers more productive.”
The research also pointed to the misalignment between current performance metrics and developer expectations. Code quality and collaboration were identified as key performance metrics, with developers expecting to be judged against those criteria. But according to Shani, leaders traditionally judge performance based on code quantity and output. Developers find code quality and collaboration equally important factors to evaluate.
“I know this from my own experience as a developer! We developers prefer to be measured by how we solved complex incidents and made an impact, rather than the number of incidents resolved – which the developers echoed in our survey,” she said.
Effective collaboration would improve code quality. Developers pointed out a number of factors that are crucial for a successful collaboration; regular points of contact, uninterrupted work time, access to fully configured development environments and mentor-mentee relationships.
They noted ineffective meetings and excessive communication as distractions that negatively affected their work.
“As developers now work on projects with an average of 21 other engineers, collaboration is more important than ever for efficiency and productivity. Developers in our survey said they want their organizations to make collaboration a top performance metric, suggesting that organizations could do more to encourage more collaboration between their tech teams,” Shani explains. “Organizations need to proactively drive developer collaboration as the true power multiplier of mission-critical outcomes.”
Shani believes the widespread adoption of AI-powered coding tools among developers indicates that most organizations likely have developers using these tools without an enterprise-grade solution or clear policy to effectively govern their use.
She said that while generative AI tools such as ChatGPT and Stable Diffusion have gained popularity, they are experiencing rapid development, raising concerns about the occurrence of false output or hallucinations, as well as data privacy.
That’s why Shani stressed the importance of organizations investing in enterprise-grade AI encryption tools that align with their criteria for effectiveness and data privacy. In addition, she emphasized the need to help developers integrate and optimize their workflows around these approved tools.
“In our experience with customers deploying GitHub Copilot and GitHub Enterprise, such investments in technology require organization-wide culture change and proactive change management,” she explains. “You can’t enable new AI coding tools and expect teams to seamlessly adapt their workflows around them. Technical agility requires operational agility.”
How organizations can improve the developer experience
Shani advises organizations to start at the cultural level to identify workplace programs and policies that promote greater collaboration. She emphasizes the importance of establishing regular check-ins for work teams, scheduling meetings, and providing platforms for asynchronous communication through pull requests, issues, and chat apps.
Tech leaders should also explore methods to standardize developer environments, such as using cloud-based IDEs or alternative solutions, according to Github. These initiatives are designed to minimize the time spent setting up the machine and allow developers to focus more on collaborative problem solving.
The research shows that developers place a high value on mentor-mentee relationships and want more of such relationships in their work environment. GitHub suggests that organizations can take this opportunity to invest in cost-effective measures that facilitate the growth and upskilling of their development teams.
“Programs and processes that encourage effective collaboration and communication, whether through documentation, effective meetings, or team components such as mentor-mentee relationships, can help developers collaborate, achieve a flow state, and even grow their skills Shani said. “Through AI-powered coding tools, teams can start with simple things like code reviews or pair programming to establish effective mentors across their organization to help their more junior developers grow.”
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