October 2025 Summaries

Laurens Lamberts, a freelance React Native developer and music enthusiast, collaborated with fellow Dutchman Jordy to create the Chase Bliss app, a preset manager for Chase Bliss guitar effects pedals. Developed using React Native and Expo, the app allows musicians to explore and save custom sound configurations, known as presets, that mimic the intricate controls of the physical pedals. It also facilitates preset sharing among users, provides access to pedal manuals, and ensures user privacy by minimizing data collection. The app features animated interactions with pedal controls and uses Expo modules to enhance functionality, including a custom module for "MIDI over Bluetooth" to transmit presets directly to the pedals. The team is working closely with Chase Bliss to refine the app, considering user feedback and potential new features while maintaining an intuitive and clean interface.

Boom is a video-first competition platform where creators submit clips to monthly contests in 11 categories, with users voting for their favorites and a jury selecting winners, who receive cash prizes. Initially, Boom faced challenges with its JavaScript uploader, which struggled with large video uploads due to lack of background execution and network interruptions. To address these issues, the team developed a new upload pipeline using Expo Modules, implementing AWS S3 multipart upload for faster, more reliable uploads. This approach, which combines JavaScript and native code, resulted in a significant improvement in upload speed and reliability, reducing median upload times by about 20% for large clips and eliminating stuck uploads. Expo Modules proved to be an effective solution for integrating native performance with JavaScript, offering easier maintenance and smoother integration with Expo projects, ultimately enhancing user experience and app robustness.

Rosebud's decision to use Expo for developing its native app was pivotal, transforming not only its engineering approach but also its business trajectory. By leveraging Expo, Rosebud's existing React developers could efficiently deliver a cross-platform app, bypassing the need for separate iOS and Android teams, which significantly reduced costs and accelerated time to market. This strategic move allowed Rosebud to launch its app rapidly, capturing $20K in revenue shortly after launch and increasing user engagement, particularly with features like voice journaling. The engineering efficiency gained through Expo was reinvested into understanding user needs, enhancing the app's capability to support personal growth, which aligns with Rosebud's mission. Moreover, the use of Expo fostered a more satisfying developer experience, contributing to high retention rates and avoiding costly recruitment. As a result, Rosebud not only expanded its user base and revenue but also attracted significant investment, all while maintaining a focus on democratizing access to personal development tools.

The Expo MCP Server, currently in preview, offers enhanced integration for AI coding assistants within Expo projects by utilizing the Model Context Protocol (MCP), an open standard that allows AI models to integrate with external data sources and tools. This feature aims to transform generic AI assistants into specialized, Expo-aware development partners that understand the framework's specific patterns and conventions. The server provides two types of capabilities: server capabilities, which include learning Expo patterns, searching documentation, and installing packages, and local capabilities, which enable advanced interactions with the development environment, such as taking screenshots and automating UI interactions. By bridging these capabilities, the Expo MCP Server delivers a hybrid solution that offers immediate access to Expo knowledge and powerful automation tools, enhancing the efficiency of development workflows. During the preview phase, the focus is on refining development processes, with feedback being sought from users to determine future enhancements and integrations for upcoming SDK versions.

React has transitioned from being primarily maintained by Meta to being governed by the newly formed React Foundation, marking a significant milestone for the entire React ecosystem. Initially open-sourced by Meta a decade ago, React has evolved into a crucial open-source project, powering countless websites and applications globally. The creation of the React Foundation, which now serves as the official home for React, React DOM, React Native, and related efforts, aims to coordinate and sustain the ecosystem rather than control it. This shift allows broader and more resilient governance, enabling transparent decision-making processes led by the maintainers and contributors. The transition is supported by major tech players like Meta, Microsoft, and Amazon, under the Linux Foundation's stable framework, ensuring continuous evolution and collaboration. Meta's commitment of five years of funding and engineering support during this transition underscores the importance of community-driven development. For Expo developers, this move reinforces the open and shared future of app development, with improvements to React's infrastructure benefiting Expo's framework. The React Foundation empowers developers to actively participate in shaping the future of React, ensuring the ecosystem remains healthy, mature, and ready for upcoming advancements.

Expo Modules allow developers using the Expo ecosystem to integrate custom native functionality into their applications when the existing libraries do not meet their specific needs. The process involves creating a custom native module, such as one for detecting audio routes, which includes steps like setting up a fresh Expo project, using the expo-dev-client package for development builds, and defining JavaScript APIs that communicate with native code on iOS and Android. Developers are guided on integrating native audio APIs from AVFoundation for iOS and AudioManager for Android, with methods to query and listen for audio route changes. The module setup involves managing events to notify JavaScript of changes in audio routes, ensuring efficient resource usage through lifecycle hooks like OnStartObserving and OnStopObserving. Continuous Native Generation (CNG) allows for the efficient management of native projects without committing them to source control, while custom modules are maintained separately within the project. Building locally or using EAS Build provides flexibility in compiling the app, and the process showcases the potential of Expo Modules for extending app functionality with custom native code.

Integrating new technology into a mature native app can be simplified by using Expo, which allows for incremental adoption without the need for a full app rewrite. Expo and React Native offer speed and flexibility by enabling developers to introduce new features or views one at a time, seamlessly integrated with existing apps. This approach is particularly beneficial for teams needing platform parity, as it allows a feature to be developed once and deployed across both iOS and Android simultaneously. Larger organizations benefit from shared JavaScript components that reduce duplication and enhance consistency, while teams divided by domain can focus on specific development areas, such as mobile platform engineers maintaining infrastructure and product teams building features. Expo supports a migration strategy where aging native codebases can gradually be replaced with React Native, optimizing development cycles without compromising existing investments. Integration involves setting up project structures and making specific configuration changes on both Android and iOS, with detailed guidance available for each step. Despite current limitations, such as certain libraries requiring additional setup or being unsupported, Expo is committed to improving these integrations, as demonstrated by examples in various open-source apps.

The inaugural Expo App Awards are being launched to celebrate the creativity and technical excellence of applications developed using Expo, a platform for building apps with React Native. These awards aim to recognize outstanding apps and their developers, showcasing the potential and innovation achievable with Expo. Submissions are open across five categories: App of the Year, Most Creative, Community’s Choice, Largest Scale, and Most Innovative, with the submission period running from October 6 to October 31, 2025. The evaluation will be conducted by the Expo team based on design, technical excellence, performance, innovation, and overall feel, without the influence of external sponsors. Winners will be announced in November 2025 and will receive custom-built Norbauer mechanical keyboards, exclusive apparel, and recognition across Expo’s platforms. The awards not only celebrate the quality and craftsmanship of Expo apps but also aim to inspire future developers by setting a high standard for what can be achieved with the platform.

AI applications have become increasingly popular, with developers often unaware of the potential for on-device AI, which eliminates the need for data to be sent to APIs and avoids access fees. Initially experimental, on-device AI has gained traction due to advancements in model efficiency and device processing power, exemplified by Apple's Neural Engine introduced in the iPhone X. This advancement allows for sophisticated language models and real-time image generation to run directly on devices, ensuring privacy, reducing costs, and offering reliability and instant response times. However, implementing on-device AI poses challenges such as computational intensity, hardware constraints, and storage issues. Libraries like react-native-executorch simplify these complexities by providing React Native developers with tools to integrate AI features without deep machine learning expertise. This library leverages Meta’s ExecuTorch engine, offering cross-platform versatility and optimized performance for various devices. While there are limitations, such as resource consumption and performance disparity across devices, strategies like model quantization and hybrid architectures can mitigate these issues. Ultimately, on-device AI is ideal for applications prioritizing privacy, offline functionality, and low latency, and serves as a foundation for innovative, privacy-focused AI experiences in mobile development.