August 2026 Summaries

The month of July marked significant milestones and updates for the Kotlin programming language, celebrating its 15th anniversary with community engagement activities and the introduction of a public benchmark for AI coding agents, which evaluates performance across various engineering tasks. Kotlin 2.4.10 was released, featuring bug fixes, while the Kotlin 2.4.20-Beta2 introduced enhancements like coroutine stack trace recovery and expanded Swift export. Kotlin's integration into BlueJ 6.0 aims to facilitate its use in educational settings, enhancing students’ learning experiences. The RevenueCat Shipaton 2026 event encourages developers to showcase their Kotlin skills by building new apps, with opportunities to win the Ship Kotlin Everywhere Award. The Kotlin community also celebrated individuals contributing significantly to education and community building through the Golden Kodee Community Awards. Additionally, X has fully rebuilt its Android app using Kotlin, showcasing the language’s growing adoption, while JetBrains IDE users can now link their experiences to LinkedIn profiles via a new plugin. The roundup also highlighted the evolution of Kodee, the Kotlin mascot, alongside the spotlight on KMP libraries Ktor, Koin, and Kermit, which support networking, dependency injection, and logging, respectively.

JetBrains has announced the availability of IntelliJ IDEA's Java and Kotlin intelligence in a preview extension format for third-party editors such as VS Code, Cursor, and others, leveraging the Language Server Protocol (LSP) to enhance development experiences across multiple platforms. This move caters to the growing trend of agentic development, where developers increasingly rely on automated agents for implementation tasks and require only basic features like code navigation and completion from IDEs. The new extension offers features such as smart code completion, navigation, refactorings, and support for build tools like Maven, Gradle, and Bazel, providing fast and reliable performance even for large projects. During the preview phase, the extension is free, but post-preview it will require an IntelliJ IDEA Ultimate subscription, allowing users to access these capabilities in various environments. JetBrains is also working on supporting agentic, terminal-based workflows and invites user feedback to refine the extension towards a stable release.

Over the past six months, JetBrains has experienced a significant increase in AI development expenses, driven by a surge in the adoption of AI tools, leading to a roughly tenfold increase in costs. This rise was attributed to the introduction of new models like Claude Opus, which improved agent performance and were widely adopted by JetBrains developers in various environments. To manage these escalating expenses, JetBrains explored several solutions, ultimately developing the JetBrains Central CLI, a tool that enables developers to use AI tools seamlessly while allowing managers to monitor and control AI usage and costs effectively. This solution, which was rapidly deployed, helps in balancing developer freedom with cost management, offering granular control over AI limits and integrating usage data into a centralized console for easier governance. Despite rapid adoption, JetBrains continues to refine its policies and expand support for more agents while acknowledging the need for further enhancements to accommodate diverse workflows and consumption patterns.

JetBrains Academy offers a course titled "Mastering Python Libraries: pandas," designed to equip learners with practical skills in handling data using the pandas library, a crucial tool for data cleaning and manipulation in Python. The course is structured to provide hands-on experience through real-time feedback and error highlighting within an IDE, focusing on essential tasks such as sorting, filtering, and summarizing data. Participants will complete two portfolio projects, including a recommendation model using the TED Talks dataset and an analysis of compute costs for training large language models. The course is available in two formats: a comprehensive package on Coursera with video lessons and certification, or a free coding-focused option directly from the course catalog, allowing learners to choose based on their preferences for structure or self-driven exploration. It is recommended for individuals with basic Python knowledge, while prior experience with NumPy is beneficial but not mandatory.