JetBrains

The Agile methodology recommends that a development team consist of 3–9 people. You might also have heard the magical number 7. But how many teams follow these recommendations? Here’s the data from our annual survey. Almost half of the respondents replied that their team is 2–7 people. Another 20% work in teams of 8–12 (this data is based on a question that garnered almost 24,000 replies). It seems most teams are already within the recommended range ✅. Splitting your growing team into smaller cross-functional teams makes sense. The challenges of scaling development teams are well-known. Here are a few of them:   🗣️Communication overhead: As team size increases, communication complexity does as well, leading to potential bottlenecks and misalignment. 🆕 Onboarding: Integrating new team members in large, distributed teams takes more work. The onboarding process can significantly slow down overall progress. 🎯 Alignment: Ensuring that all team members are aligned with the project’s goals, coding standards, and architectural decisions becomes more difficult with a larger team. How do you manage team size at your organization? Have you faced any challenges when scaling your teams? 

Early evidence suggests that, if not used judiciously, AI-powered coding assistants can erode the quality of codebases 😱 . Why does this happen, and how can it be prevented? AI coding assistants often focus on adding new code, while developers 👩💻 must also bug-fix 🐛 and refactor existing code. Another problem is that most coding assistants are incentivized to make suggestions that will be accepted and not generate code that is easy to maintain. However, improving the quality of suggestions alone is unlikely to solve the problem. The real challenge is how to integrate AI-generated and human-written code in a way that preserves or improves the health of codebases. ☝️ One way to address an AI-driven code quality gap could be to combine traditional code quality best practices like testing, refactoring, static analysis, and code reviews with novel AI-driven solutions. For example, when the JetBrains research team used static analysis to enhance and rank refactoring suggestions generated by LLMs, 81% of surveyed developers found the suggestions useful. Read the full article to explore the problem of the AI-driven code quality gap: https://lnkd.in/defkN_QY

With many companies pushing for a full return to the office, developers may face significant changes. Remote work has provided flexibility, deeper focus, and a more inclusive environment, especially for those with commuting or accessibility challenges.

This summer, our Belgrade office enjoyed a refreshing escape to the beautiful Serbian countryside for our annual JetBrains Summer Event! 🌞 From adventurous activities like zip-lining and mechanical bull riding to relaxing in the chill-out zone, the day was filled with excitement and fun. The team enjoyed getting creative with hands-on workshops like dream catchers, texture painting, and glass engraving. Sports enthusiasts played table tennis, volleyball, and petanque, while others embraced their artistic side with mehendi tattoos and darts painting. 🎨🎯 We wrapped up the day with marshmallows around the fire pit, an open-air cinema, and a disco under the stars. The event was a perfect blend of relaxation, creativity, and team bonding. 😊✨

October 10th is World Mental Health Day 💜. Considering that more than 70% of developers and other tech professionals have experienced burnout, taking care of mental health should be a high priority. Unfortunately, for many, it’s not 😔. 51% of the respondents answered “no” to the question “Do you take care of your mental health?” in our annual Developer Ecosystem survey. A quarter of respondents are vaguely aware of the concept of mental health, and another quarter know about it but are not interested in the topic. There is also some good news: A third of our respondents are into psychological practices like meditation🧘. Team leaders play a crucial role in creating a culture that prioritizes mental health. It’s not just about implementing wellness programs. It’s about fostering an environment where team members feel safe, supported, and encouraged to take care of their mental well-being. Here’s what you can do to help: 🟪 Lead by example: Openly discuss mental health practices and encourage regular check-ins. 🟪 Normalize taking breaks, setting boundaries, and recognizing when someone might need support. 🟪 Provide access to mental health resources and promote their use. 🟪 Share your personal stories – but mindfully, when needed, and with caution. Do you have more tips or stories? Share them in the comments! 

Imagine this: you're deeply focused on an important task – planning the best way to migrate your legacy application. Suddenly, a colleague walks in: "Hey, can I ask you something?" 🙂 It happens all the time. Your focus is shattered 😕, and your mind starts wandering, even if the conversation is brief. Have you ever wondered how much time you and your team waste because of interruptions? ◾ According to recent research, it takes workers 23 minutes, on average, to return to interrupted work. (see Multitasking in the Digital Age). ◾ Another study that investigates software engineering practices in particular states that it takes 8–9 minutes for a developer to get back to coding after being interrupted (see Today was a Good Day: The Daily Life of Software Developers). This metric can be different depending on a person’s cognitive abilities, the nature of a task, and an interruption. And sure, you might accomplish other tasks during these unintended breaks, but your primary work still gets delayed, hindering your progress. What has your experience been like? How long does it take you to regain focus after an interruption? 🔗Multitasking in the Digital Age, Gloria Mark, professor of the Department of Informatics at the University of California, Irvine. https://lnkd.in/dE2EBdA8 🔗 Today was a Good Day: The Daily Life of Software Developers https://lnkd.in/dzXx_CDf

The JetBrains Developer Recognition Program is expanding! Recognized GitHub Stars can now enjoy free access to all JetBrains IDEs. 🌟 Learn more: https://jb.gg/github_stars

Early evidence suggests that, if not used judiciously, AI-powered coding assistants can erode the quality of codebases. Why does this happen, and how can it be prevented? AI coding assistants often focus on adding new code, while developers must also bug-fix and refactor existing code. Another problem is that most coding assistants are incentivized to make suggestions that will be accepted and not generate code that is easy to maintain. However, improving the quality of suggestions alone is unlikely to solve the problem. The real challenge is how to integrate AI-generated and human-written code in a way that preserves or improves the health of codebases. One way to address an AI-driven code quality gap could be to combine traditional code quality best practices like testing, refactoring, static analysis, and code reviews with novel AI-driven solutions. For example, when the JetBrains research team used static analysis to enhance and rank refactoring suggestions generated by LLMs, 81% of surveyed developers found the suggestions useful. Read the full article to explore the problem of the AI-driven code quality gap: https://lnkd.in/defkN_QY

We're going to GITEX 2024! 🎉 Book a time to chat with our team! 👇 https://lnkd.in/dndmmY2s

How can you empower teams to maintain high-quality code? Here are the top issues that leaders need to address. ⏳ Time constraints are the number one reason teams fail to address code quality issues, with 48% of respondents in the Developer Ecosystem Survey conducted by JetBrains selecting them as the biggest obstacle to maintaining high-quality code. As a leader, you can implement better time management techniques or invest in automation and tools to reduce repetitive tasks, freeing time for quality-focused work. 👷 The second-most common reason is high workload, with 38% of responses. Workload can be balanced by hiring additional talent or improving task prioritization. Additionally, leveraging AI to automate low-value tasks can free up your team’s time to focus on more complex and valuable work. 🗒️ Misaligned code quality guidelines come in third, with 34% of responses. Ensure clear, team-wide understanding of code quality standards by holding regular discussions and aligning them with business goals. How are you ensuring your team stays focused on code quality despite these challenges? Let us know in the comments!