Join top executives in San Francisco July 11-12 to hear how leaders are integrating and optimizing AI investments for success. Learn more
A recent survey conducted by GitHubin’s partnership 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 business environments .
According to the findings, 92% of developers already use AI-powered coding tools in their work. However, despite the investment in DevOps, developers still face challenges. They report that their most time-consuming task is waiting for builds and tests. They also expressed concern about repetitive tasks like writing boilerplate code. They aspire to spend more time collaborating with colleagues, acquire new skills, and create innovative solutions.
GitHub said these statistics indicate a growing need to improve efficiency in the development process.
>>Don’t miss our special issue: Building the Foundation for Customer Data Quality.<
Join us in San Francisco July 11-12, where top executives will share how they integrated and optimized AI investments for success and avoided common pitfalls.
We’ve found that developers spend most of their time writing code and testing, then waiting for code to be reviewed or for builds to finish, Inbal Shani, chief product officer at GitHub, told VentureBeat. We’ve also found that AI-powered coding tools enable individual developer productivity and increased team collaboration. This means that Generative AI helps developers generate greater impact, increase satisfaction, and create more innovative solutions.
The firm suggests that business leaders should prioritize their developers by identifying areas of friction, eliminating productivity barriers, and driving growth and momentum. Developer experience, according to the study, has a major influence on productivity, satisfaction, and impact.
Collaboration has emerged as a vital 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 evaluations. Over 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 force multiplier that enables larger engineering teams to benefit and drive customer outcomes. Every organization should use this equation to put developers at the center of customer empowerment, GitHubs Shani added.
In the study, the developers also expressed a desire for more opportunities for upskilling and 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 survey investigated the impact of AI-powered coding tools on individual performance. The vast majority of developers (92%) reported using AI-powered coding tools, with 70% believing these tools give them an edge 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 said that the integration of AI coding tools is in line with the goal of improving the developer experience.
In fact, Githubs Shani expects the 92% figure to have already increased since the study was conducted in March 2023. We’ve already seen this impact from our customers using GitHub Copilot, Shani said. These developers feel 75% happier with their work and are already coding more than 55% faster.
Shani said AI has the potential to significantly improve various aspects of the developer experience. These include speeding up code delivery, facilitating intelligent code reviews, improving collaboration within the code base, and overcoming disruptions in the development process that typically require more cognitive effort.
According to her, as AI models advance and additional features are developed, we can anticipate a fundamental redefinition and improvement of the developer experience, developer productivity, and team collaboration.
Improved skills, productivity the main benefits of artificial intelligence tools
The study identified improved skills as the top benefit, followed by productivity gains. Integrating AI-powered coding tools into the developer workflow was seen as an opportunity to improve performance and better meet existing standards.
The developers said that acquiring new skills and creating innovative solutions had the greatest positive impact on their work.
AI developer tools will quickly become the stakes, and organizations that don’t adopt this change will be left behind. Having AI tools will become an expectation of all developers as a central tool to get their jobs done, Shani added. If industries are to hire and retain the best talent, they need to be able to provide the best tools to make developers more productive.
The survey also highlighted the misalignment between current performance metrics and developer expectations. Code quality and collaboration have been identified as the most important performance metrics, with developers expecting to be evaluated against these criteria. However, according to Shani, leaders have traditionally evaluated performance based on the amount of code and output. Developers argue that code quality and collaboration are at least important factors to evaluate.
I know this from my developer experience! We developers prefer to be measured on how well we resolved complex incidents and produced impact, rather than the number of resolved incidents that developers echoed in our survey, she said.
Effective collaboration is said to improve code quality. The developers have indicated a number of critical factors for a successful collaboration; regular touchpoints, uninterrupted work time, access to fully configured development environments and mentor-mentee relationships.
They noted ineffective meetings and excessive communication as distractions that negatively impacted their work.
With developers now working with an average of 21 other engineers on projects, collaboration is more important than ever to efficiency and productivity. The developers in our survey said they want their organizations to make collaboration a metric of peak performance, which suggests organizations can do a better job of incentivizing greater collaboration among their engineering teams, Shani explained. Organizations should proactively incentivize developer collaboration as a true force multiplier on mission-critical outcomes.
Shani believes that the widespread adoption of AI-powered coding tools among developers means that most organizations likely have developers using these tools without an enterprise-grade solution or clear policies to effectively govern their use .
He said that while AI tools like ChatGPT and Stable Diffusion have gained popularity, they continue to undergo rapid development, with concerns remaining about the occurrence of false output or hallucinations, as well as data privacy.
Therefore, Shani emphasized the importance for organizations to invest in enterprise-grade AI coding tools that align with their data privacy and effectiveness criteria. Additionally, you highlighted the need to assist developers in integrating and optimizing their workflows around these approved tools.
In our experience with customers implementing GitHub Copilot and GitHub Enterprise, such technology investments require organization-wide culture change and proactive change management, he explained. You can’t roll out new AI coding tools and expect teams to seamlessly tailor their workflows around them. Technical agility requires operational agility.
How organizations can improve the developer experience
Shani advises organizations to start at a cultural level to identify workplace programs and policies that promote greater collaboration. She highlights the importance of establishing regular check-ins for work teams, scheduling meetings, and providing platforms for asynchronous communication via pull requests, issues, and chat apps.
Engineering leaders should also explore ways to standardize developer environments, such as using cloud-based IDEs or workarounds, according to Github. These initiatives aim to minimize the time spent on machine setup and allow developers to focus more on collaborative problem solving.
The study reveals that developers highly value mentor-mentee relationships and want more of these 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 foster effective collaboration and communication, whether through documentation, effective meetings, or team building blocks such as mentor-mentee relationships, can help developers work together, enter a state of flow, and even grow their skills. said Shani. Through AI-powered coding tools, teams can start with simple things like code review or pair coding to create effective mentors in their organizations to help their younger developers thrive.
VentureBeat’s mission it is to be a digital city square for technical decision makers to gain insights into transformative business technology and transactions. Discover our Briefings.
#USbased #developers #AIpowered #coding #tools #work #GitHub #report