# Android Developers Blog An Open Handset Alliance Project. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Introducing Fast and Reliable Wireless Debugging with Android Debug Bridge (ADB) Wi-Fi 2.0 DevFeed: [Introducing Fast and Reliable Wireless Debugging with Android Debug Bridge (ADB) Wi-Fi 2.0]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-09-09T16:00:00Z Content type: release Language: en Sources: [Android Developers Blog]() Topics: [ADB Wi-Fi 2.0](), [Wireless Debugging](), [Android](), [Android Studio](), [Wi-Fi](), [SDK]() Tags: [adb](), [adb-wi-fi-2-0](), [android](), [android-studio](), [debugging](), [network](), [sdk](), [wi-fi](), [wireless-debugging]() ### AI overview Android introduces ADB Wi-Fi 2.0, a wireless debugging update that reworks the adb server, adbd daemon, and Android Studio integration. It adds a new mDNS-based server stack, smarter handling of untrusted networks, and improved device discoverability. The article reports a 32% improvement in auto-connection success rates and a 66% increase in connection speeds for 90% of connections. ### Source excerpt Posted by Steven Jenkins, Product Manager, Sherif Eid, Senior Software Engineer, and Fabien Sanglard, Staff Software Engineer, Android Studio Wireless debugging on Android is now faster, more reliable, and easier to set up than ever. With ADB Wi-Fi 2.0, we've introduced a new server stack and smarter network handling to directly address developer feedback around usability gaps. How ADB Wi-Fi 2.0 Improves Wireless Debugging To ensure ADB Wi-Fi 2.0 is even more reliable, we reworked all three core components of the stack: the adb server, the adbd daemon, and Android Studio. Here are the new features: A new server stack (adb): Previously, wireless device connections would sever when network configurations changed or devices were turned off. This meant that connections would drop for common occurrences. With our new mDNS stack, we've replaced both Bonjour and legacy mDNS so that your wireless devices more reliably stay connected as you go about your day. Smarter network handling (adbd): Previously, the workstation's mDNS client would sporadically drop services. Now, the daemon automatically turns off ADB Wi-Fi when it detects an untrusted network and re-enables itself once running on a user-allowed network. Improved discoverability in Android Studio: Previously, Wi-Fi pairing was difficult to find. Now, you simply enable wireless debugging on your phone and it will show in Android Studio's Device Manager. With ADB Wi-Fi 2.0, auto-connection success rates improved by 32% and connection speeds increased by 66% for 90% of connections. Getting Started You can use ADB Wi-Fi 2.0 on your phone, tablet, Wear OS, and TV. Here's how to get started: Update to Android 17, Android SDK Platform-Tools 37.0.0, and Android Studio Quail 3 or later. Ensure your workstation and your Android device are connected to the same Wi-Fi network. On your device, navigate to Developer Options and enable Wireless debugging. Open the Android Studio Device Manager and click the pair over Wi-Fi icon. Sc ## Leverage Android skills and Gemma 4 in Android Studio Quail 4 DevFeed: [Leverage Android skills and Gemma 4 in Android Studio Quail 4]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-09-01T15:00:00Z Content type: article Language: en Sources: [Android Developers Blog]() Topics: [Agent Skills](), [Android Studio](), [Artificial Intelligence](), [LLMs](), [Google](), [gemma4]() Tags: [agent-skills](), [ai](), [android-skills](), [android-studio](), [development](), [gemma-4](), [google](), [llms]() ### AI overview Android Studio Quail 4 is stable and includes Android skills bundled directly into the IDE. The curated, preloaded skills help its agent handle complex Android workflows, including API changes, migrations, configuration, profiling, navigation upgrades, and adaptive UI work. ### Source excerpt Posted by Amman Fasil Asfaw, Product Manager, Android Studio Android Studio Quail 4 is now stable and ready for you to use in production. This is the final stable release for Android Studio Quail. The new features in Android Studio enable you to build premium apps with AI efficiently and effectively. Check out the video below to see the most helpful new features from the last 4 releases that can help improve and speed up your development. Here is a deep dive into what's new in Android Studio Quail 4: Android skills bundled into Android Studio While LLMs are incredibly capable at generic coding queries, they frequently write incorrect or outdated code when confronted with rapidly evolving Android APIs, platform-specific migrations, or complex configuration structures.To solve this, we bundle Android skills that have been curated by the team who builds Android, directly into Android Studio. Following the open-standard agent skills specification, these are modular, AI-optimized instructions designed specifically to guide LLMs through complex Android workflows. Android skills are now pre-loaded directly into the IDE, so you can start using them without having to manually download additional files. When you prompt the Android Studio agent, we analyze your prompt and search against the metadata for installed skills, automatically invoking them when they're most relevant. Your agent gains instant domain expertise, applying Google's best practices with less overhead spent on long, manual setup prompts. Android Studio comes preloaded with 23 curated skills, including: Need help upgrading your build? You have the Android Gradle Plugin (AGP) 9 Upgrade skill. Want to profile your app for any performance issues? You have the Android Profiler skill. Ready for a Jetpack Navigation framework upgrade? You have the Navigation3 skill. Adapting your app UI to different Android devices? You have the Adaptive skill. We also encourage you to create your own custom skills to extend Agent M ## Emulator control for adaptive app development DevFeed: [Emulator control for adaptive app development]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-08-31T16:00:00Z Content type: tutorial Language: en Sources: [Android Developers Blog]() Topics: [Android](), [Emulator](), [Command-line interface](), [Large Screen](), [Android Studio](), [Terminal](), [Development]() Tags: [adaptive](), [adb](), [android](), [android-studio](), [app-development](), [command-line](), [commands](), [console](), [development](), [devices](), [emulator](), [layout](), [verify](), [workflow]() ### AI overview A tutorial on using Android Emulator console commands through adb emu to test adaptive app behavior. It covers folding and unfolding devices, rotating them, simulating physical postures, and resizing displays from the terminal. ### Source excerpt Posted by Rob Orgiu, Developer Relations Engineer, Adaptive Apps, Android Adaptive app development is fundamental on Android, but making sure everything looks good and every feature works the way it should require multiple tests on multiple devices. Or does it? Well, yes... and no! While Android Studio is bundled with the Resizable Emulator to let you test layouts manually, there's a faster, more streamlined way to control form factors directly from your terminal. By leveraging fire-and-forget console commands using the adb emu shortcut, you can execute commands that immediately return control to your invoking shell. If you have multiple emulators running at the same time, you can target a specific virtual device by passing in the shortcut's serial: adb -s emu First things first: Fold and unfold To test foldable-specific user journeys and layout configurations, you can fold and unfold your emulated device programmatically. adb emu fold If your foldable emulator is unfolded, you can fold it to display its smaller screen configuration, powering on the (virtual) external display. To unfold the emulator and power on the internal display, simply run: adb emu unfold Now, you can instantly verify that your app preserves its state and that layouts appear exactly as they should on different display sizes. Rotation, rotation, rotation Correctly handling orientation changes is a cornerstone of adaptive app development. You can trigger device rotations programmatically to test how well your app handles configuration changes, including state restoration. The following command rotates the device 90° clockwise: adb emu rotate Simulating postures using sensors What about placing the emulator into a specific physical posture, like tabletop mode? The easiest approach is querying for the number of available positions with . First, list all available sensors and their current status: adb emu posture This returns a list of positions similar to the following: ## How WhatsApp Implemented Passkey Authentication for Faster, Phishing-Resistant Sign-In DevFeed: [How WhatsApp Implemented Passkey Authentication for Faster, Phishing-Resistant Sign-In]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-08-27T17:00:00Z Content type: article Language: en Sources: [Android Developers Blog]() Topics: [Passkeys](), [Authentication](), [Security, Privacy and Abuse Prevention](), [Cryptography](), [Android]() Tags: [api](), [authentication](), [credential-theft](), [cryptography](), [developer](), [google](), [meta](), [sign-in](), [whatsapp]() ### AI overview The article describes how WhatsApp implemented passkey-based authentication to provide faster sign-ins and reduce phishing and credential-theft risks. It explains the use of public-private key cryptography, biometric or screen-lock authentication, and Android's Credential Manager API. ### Source excerpt Posted by Niharika Arora, Senior Developer Relations Engineer, Tracy Agyemang, Product Marketing Manager, Google and Mayank Manuja, Android Engineer, Meta WhatsApp is the world's largest messaging platform, serving billions of users globally. It is the default communication tool for people across diverse regions, connecting users through private, reliable, and secure messaging. "What excites me most is the sheer scale of WhatsApp's impact. Even a small improvement to WhatsApp touches billions of users worldwide," says Mayank Manuja, an Android Engineer on the WhatsApp Registration and Access team who led the design and implementation of passkey-based authentication for WhatsApp. Building for an audience of this magnitude requires navigating a vast range of network conditions, device capabilities, and levels of digital literacy. Recognizing the potential early, WhatsApp committed to adopting passkeys in 2023, becoming one of the first major consumer apps to integrate the technology. By implementing passkeys, WhatsApp aimed to provide a fast, phishing-resistant option that significantly reduces user friction while providing robust protection against account takeovers and credential theft. A user creating a passkey on WhatsApp for faster, more secure sign-ins. The Decision to Adopt Passkeys For WhatsApp, offering multiple access methods is key to making it easier for users to stay connected and regain access when needed. Passkeys offer users a streamlined, one-tap login experience that eliminates phishing risks and functions reliably even in regions where OTP message delivery can be inconsistent. Underneath, passkeys leverage public-private key cryptography to replace manual entry with biometric or screen lock authentication. This workflow drastically improves sign-in speeds by reducing the process to a single tap via a unified, bottom-sheet interface that keeps users engaged within the app's context. The benefits are twofold: passkeys offer users a streamlined login e ## Elevating app quality: Reducing memory usage and improving device migration DevFeed: [Elevating app quality: Reducing memory usage and improving device migration]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-08-26T17:00:00Z Content type: news Language: en Sources: [Android Developers Blog]() Topics: [Android](), [Google Play](), [Optimization](), [Mobile]() Tags: [android](), [google-play](), [memory](), [onboarding](), [optimization]() ### AI overview Google Play is introducing Android app and game quality requirements covering memory footprint, code optimization, and secure device-migration login. The article describes new performance thresholds and Play Console tools intended to help developers identify and address excessive memory use. ### Source excerpt Posted by Raghavendra Hareesh Pottamsetty, GM, Google Play Developer & Monetization Maintaining a healthy Android ecosystem is a shared commitment where every app and game has a role to play. To help you deliver the premium experiences users expect, Google Play is introducing two new quality requirements: one focused on reducing app memory footprint, and another on providing a secure, seamless device migration experience. First, to help developers navigate industry-wide hardware constraints and Android's broader memory limits, Google Play is establishing new performance thresholds. Second, as part of our broader commitment to elevate app quality, we are introducing a new onboarding standard to simplify and secure login during device upgrades. Reducing app memory usage and optimizing code The mobile industry is navigating significant hardware supply constraints that are altering device memory availability that over time can negatively impact the user experience. Android is addressing this challenge head-on with broader memory limits that aim to protect the overall user experience from apps using excess memory and causing system-wide slowdowns. Building on this, today Google Play is establishing performance thresholds to help developers ensure their apps continue to deliver the premium experience users expect. This includes new thresholds across dynamic memory usage, bitmap usage, and code optimization to prevent unexpected on-device performance throttling and app terminations. Dynamic memory usage (anonymous RSS + swap): This tracks the memory used for your app's private data storage, including both active and compressed memory. It excludes files stored on the device, such as code or assets. We will assess this usage across different app states (like when your app is in use or running in the background) and device performance categories. Bitmap memory usage: This evaluates the memory consumed by bitmaps. While bitmaps occupy memory when your app is in the foreground, ## Ensuring Safety in the Generative AI Ecosystem: Protecting Users from Non-Consensual Intimate Content DevFeed: [Ensuring Safety in the Generative AI Ecosystem: Protecting Users from Non-Consensual Intimate Content]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-08-25T17:00:00Z Content type: article Language: en Sources: [Android Developers Blog]() Topics: [ai safety](), [Generative AI](), [Google Play](), [trust & safety](), [LineageOS]() Tags: [ai](), [ai-safety](), [generative-ai](), [google-play](), [policy](), [safety](), [testing](), [trust-safety]() ### AI overview Google Play outlines safety requirements and safeguards for generative AI apps to help prevent non-consensual intimate imagery and other harmful content. The guidance covers app-lifecycle reviews, guardrail visibility, adversarial testing, and Android safety practices. ### Source excerpt Posted by Ron Aquino, Senior Director, Trust & Safety, Chrome, Android, and Play At Google Play, user safety and developer success go hand in hand. We continue to see growth in apps with AI generated features, and indeed, adding generative AI into your apps is a great way to unlock incredible creative possibilities. However, AI features also bring new safety challenges - such as the rise of AI-facilitated generation of non-consensual intimate imagery (NCII). Google Play's policies prohibit the facilitation, creation, or distribution of non-consensual sexual content. Harmful applications designed to target, harass, or exploit individuals have absolutely no place on Google Play, and we are committed to enforcing our policies to keep the store a safe space for developers to thrive. We know that the vast majority of you are dedicated to building positive, ethical tools. To protect both your hard work and our shared user base, we are investing heavily in platform protections, technical defenses, and developer resources to stop abuse. How we're safeguarding our shared ecosystem Protecting the platform is a continuous effort. Bad actors attempt to exploit distribution channels, monetization paths, and model boundaries. To help keep the ecosystem fair and safe, we've put a multi-layered defense strategy in place: Safeguards across the app lifecycle: Generative AI features are dynamic and can be less predictable, so safety isn't just a one-time check when you submit your app. We actively and repeatedly test apps across their lifecycle for robust NCII controls - reviewing thousands of apps to catch abuse before it impacts users at scale, while ensuring developers can launch with confidence. Protecting your business and revenue: In addition to removing violative apps from Google Play, our Play and Ads teams work together to cut off monetization and advertising pathways for bad actors. Apps that are suspended or removed for attempting to generate or monetize harmful content suc ## AAOS SDV - Secure by Design DevFeed: [AAOS SDV - Secure by Design]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-08-24T16:00:31Z Content type: article Language: en Sources: [Android Developers Blog]() Topics: [Android](), [Security](), [virtualization](), [virtual machines](), [SELinux](), [POSIX](), [Processes](), [Google]() Tags: [android](), [android-security](), [article](), [google](), [posix](), [process](), [security](), [selinux](), [virtual-machines](), [virtualization]() ### AI overview This article explains the security design of Android Automotive Operating System for Software Defined Vehicle (AAOS SDV). It describes virtualization for domain isolation, UID-based application and service sandboxing, POSIX capabilities, SELinux deny-by-default enforcement, and Android's vulnerability management and disclosure processes. ### Source excerpt Posted by Markus Vill, Software Engineer, Sean Keys, Security Engineer, and Istvan Nador, Software Engineer, Android Auto At Google, we believe our products should be secure by design, which is why we built the Android Automotive Operating System for Software Defined Vehicle (AAOS SDV) on existing, market-proven platforms, leveraging virtualization technologies like Cuttlefish. While our release announcements focused on the features, this blog post outlines some of the security concepts. Foundation: Domain IsolationVirtualization to isolate co-hosted instances The current trend of consolidating Electronic Control Units (ECUs) into a single chip reduces isolation by running multiple domains side-by-side. While AAOS SDV instances provide internal isolation mechanisms, it is often preferable to run logical domains independently. For instance, a cluster and an infotainment system have distinct requirements. We use virtual machines to run multiple instances in parallel, ensuring that sharing remains explicit and isolation is the default behavior. Inherited Android Security AAOS SDV evolved from Microdroid, a minimalistic Android version optimized for privacy virtual machines (pVM). This lineage provides Android platform engineers with established security features they already know. Process Isolation & Deny by Default AAOS SDV follows Android's User ID (UID)-based isolation model to set up a sandbox for each application. Each service runs in a dedicated process with a unique UID to manage access rights, data directories, and other restrictions. We employ Portable Operating System Interface (POSIX) capabilities to strictly limit operations and pair this with Security-Enhanced Linux (SELinux) to enforce a "deny-by-default" posture. This approach restricts each service to the absolute minimum required, meaning missing configurations block access rather than creating an over-permissive system. We apply this same strategy to our communication permission system, as explained l ## Preparing your app for broader memory limits DevFeed: [Preparing your app for broader memory limits]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-08-19T19:00:00Z Content type: tutorial Language: en Sources: [Android Developers Blog]() Topics: [Android](), [Optimization](), [User Experience](), [Memory Leaks](), [memory price increases]() Tags: [adb](), [android](), [memory-leaks](), [memory-optimization](), [optimization](), [user-experience](), [vitals]() ### AI overview This Android Developers article explains how Android 17 per-app memory limits are expanding beyond Pixel devices across a range of RAM configurations. It describes the effects of exceeding memory budgets, including zRAM swapping, CPU overhead, UI jank, throttling, and possible process termination, and outlines ways to measure and optimize app memory usage. ### Source excerpt Posted by Blair Harmon, Director of Product Management, Android Platform A great user experience is central to Android's mission, and delivering on that promise requires keeping devices fast, responsive, and reliable. This is why memory optimization is more critical than ever. Across the ecosystem, new devices are maintaining or even decreasing their physical memory capacity in response to memory price increases, yet users continue to expect the same seamless, high-performance app experience. In Android 17, we introduced per-app memory limits, starting with Pixel devices, to help protect the overall user experience from applications using excess memory and causing system-wide slowdowns. Over the coming year, an increasing number of manufacturers will leverage the Android per-app memory limits across their portfolio of device RAM configurations from 4GB to 16GB+ devices. If your app exceeds these limits, it will be slowed down and may be terminated. Optimizing your app's memory footprint is essential to preventing OS throttling and maintaining a seamless user experience. In this post, we'll explore how these limits work under the hood, how to measure your memory footprint using new Android vitals metrics, and actionable steps to optimize your app or game. Understanding Memory Limits When your app exceeds its memory budget, Android takes progressive action to protect device responsiveness: zRAM Swapping: If your app reaches its allocated limit, the system forces your app's pages into zRAM (compressed RAM). While zRAM prevents immediate eviction, compressing and decompressing pages adds CPU overhead, which can result in noticeable UI jank and experience slowdowns. Process Termination: If your app continues to increase its memory usage beyond the zRAM threshold, it will be terminated by the system. To determine if your app session was impacted by these constraints in the field, you can call getDescription() within ApplicationExitInfo. If the system applied a limit, the ## Tinder cuts app cold starts by 47% with new R8 Configuration Analyzer DevFeed: [Tinder cuts app cold starts by 47% with new R8 Configuration Analyzer]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-08-18T18:00:00Z Content type: article Language: en Sources: [Android Developers Blog]() Topics: [R8](), [Android](), [Optimization](), [configuration](), [audit]() Tags: [android](), [anr](), [audit](), [configuration](), [metrics](), [obfuscation](), [optimization](), [r8]() ### AI overview This developer case study explains how Tinder used the R8 Configuration Analyzer to identify and remove keep-rule blockers in its Android application. The reported results were a 47% reduction in cold-start time, a 28.98% reduction in download size to 61.5 MB, and a 28% reduction in user-perceived ANRs. The article also describes analyzer metrics for shrinking, optimization, and obfuscation, along with an R8 Analyzer skill for agentic development workflows. ### Source excerpt Posted by Ajesh R Pai, Developer Relations Engineer, Ulises Uriel Verduzco Diaz, Software Engineer, Tinder, and Tracy Agyemang, Product Marketing Manager Tinder is on a mission to power and inspire real connections by making meeting easy and fun for every new generation of singles. However, as their Android application codebase grew in size, so did its complexity. Prior to their latest optimization efforts, approximately 70% of the application was not optimized, carrying 17 dex files,including three dedicated just to startup. Although they had enabled R8, much of its optimization potential was blocked due to keep rules, and the team was unable to identify which specific rules were preventing optimization. To reduce startup time and decrease user-perceived Application Not Responding (ANR) errors, Tinder turned to the new R8 Configuration Analyzer to tackle these challenges. By utilizing the R8 Configuration Analyzer, Tinder successfully identified and removed unintentional optimization blockers. The results were immediate and impactful: Tinder achieved a 47% reduction in app cold starts, shrank their app download size by 28.98% (down to 61.5 MB), and reduced user-perceived ANRs by 28%. Configuration analyzer The R8 Configuration Analyzer shows R8 optimization by tracking shrinking, optimization, and obfuscation scores to show available refinement areas. It shows the broad, redundant, or obsolete keep rules, including those from external libraries so that you can analyse the keep rule impact and refine the keep rules. Key metrics shown in Configuration Analyzer include: Shrinking Score: Code percentage available for R8 shrinking. Optimization Score: Code percentage open to optimization (for example, method inlining, horizontal class merging). Obfuscation Score: Percentage of classes, methods and fields that can be renamed by R8 to decrease size. Use the analyzer to audit keep rules and their impacts: Find broad rules: Narrow the scope of package-wide rules that restri ## Jetpack XR SDK core libraries reach beta: The next milestone for Android XR DevFeed: [Jetpack XR SDK core libraries reach beta: The next milestone for Android XR]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-08-18T17:00:00Z Content type: release Language: en Sources: [Android Developers Blog]() Topics: [Jetpack XR SDK](), [Android XR](), [Jetpack](), [Compose](), [releases]() Tags: [android-xr](), [beta-announcement](), [compose](), [jetpack](), [jetpack-xr-sdk](), [preview](), [releases](), [sdk]() ### AI overview Google announces that Jetpack SceneCore, ARCore for Jetpack XR, and XR Runtime have reached beta as part of the Jetpack XR SDK. The release stabilizes APIs for Android XR development, while Jetpack Compose for XR is expected to reach beta soon. ### Source excerpt Posted by Amy Zeppenfeld, Developer Relations Engineer, Greg Underwood, Software Engineering Manager, Yasmine Evjen, Senior Product Manager, Android XR Since introducing the Android XR SDK, developers have transformed their ideas into innovative, immersive experiences for XR headsets and wired XR glasses. As the ecosystem expands, you can more easily take those experiences from preview to production and reach users wherever they are. Today, we're excited to announce that Jetpack SceneCore, ARCore for Jetpack XR, and XR Runtime have reached beta with Jetpack Compose for XR to follow soon! This means the APIs are stabilizing, making it a great time to start integrating them into your production workflows and creating for Android XR. Why the Jetpack XR SDK? The Jetpack XR SDK includes all the tools and libraries you need to build immersive and augmented experiences for Android XR. Whether you're porting an existing 2D app or creating a new 3D XR app from scratch, you can do so using the familiar Android development tools you already know and love. To support your development, this release focuses on providing the fundamental building blocks across the SDK: Jetpack SceneCore: Build and manipulate the Android XR scene graph with 3D content. You can arrange 3D models, play spatial audio, and use the robust entity-component system to create, control, and manage entities. ARCore for Jetpack XR: Bring digital content into the real world with perception capabilities. This library powers depth estimation, persistent anchors, hit testing, and plane identification. XR Runtime: Provides the essential runtime foundation of the SDK, handling device lifecycles, session creation, and system configurations that enable the API surface. Jetpack Compose for XR: Create spatial UI layouts that take advantage of Android XR's spatial capabilities. This library lets you use familiar Compose concepts to create spatial UIs and will be reaching Beta soon. What's new in Beta? Direct feedback from ## Building adaptive Android apps for foldable and expanded displays DevFeed: [Building adaptive Android apps for foldable and expanded displays]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-08-12T19:00:00Z Content type: article Language: en Sources: [Android Developers Blog]() Topics: [Android](), [Large Screen](), [Jetpack Compose](), [ui](), [Jetpack](), [Canvas]() Tags: [adaptive](), [android](), [jetpack](), [jetpack-compose](), [layout](), [multitasking](), [ui]() ### AI overview This Android developer article explains how to adapt apps for foldable devices and expanded displays. It covers window-based sizing, Jetpack Compose layout APIs, posture-aware interfaces, and preserving UI state across folding, rotation, multitasking, and resizing transitions, with examples from Notability and Flo Health. ### Source excerpt Posted by Fahd Imtiaz, Senior Product Manager, Loryn Hairston, Product Marketing Manager, and Tracy Agyemang, Product Marketing Manager, Android Developer Made by Google expands what's possible across the Android ecosystem. With the introduction of the Pixel 11 Pro Fold, Pixel Watch 5, and the entire Pixel family, users are moving seamlessly across diverse screen sizes, unique postures, and intelligent experiences. For you, the developer, this represents a massive opportunity: foldable users spend about 14x more than standard phone users. To help you elevate your existing experience without starting from scratch, we're sharing our latest platform guidance alongside real-world examples from developers already putting these features into production. Deliver adaptive experiences across foldables and expanded displays The Pixel 11 Pro Fold gives your app a chance to flex its capabilities with an expanded inner display and a standard size outer screen. Building for the foldable form factor requires dropping hardcoded layout rules and designing around available window space. Leveraging Jetpack Compose APIs like Navigation 3 with Scene strategies or our newest layout APIs like Grid and FlexBox allows your layout containers to automatically wrap, span, and reflow. You can also use the experimental MediaQuery API to dynamically adapt your UI to environmental signals like foldable posture, and keyboard states. Building adaptively requires tracking actual app dimensions rather than physical device size, especially during split-screen and multitasking flows. Using Window Size Classes from the WindowManager library allows your layout to respect folds and hinges as natural content separators. For instance, Notability leveraged Material 3 Window Size Classes to create a responsive two-pane layout that transitions smoothly between folded and expanded screens. As Ryan Shea, Android Engineering Manager at Notability, shared, tracking the window itself allows their layout and canvas z ## Bring one-handed gestures to your Wear OS app DevFeed: [Bring one-handed gestures to your Wear OS app]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-08-12T17:00:00Z Content type: tutorial Language: en Sources: [Android Developers Blog]() Topics: [Compose](), [Android](), [API]() Tags: [android](), [api](), [compose](), [framework](), [release]() ### AI overview This article explains how to add Wear OS 7 one-handed gesture support to Wear Compose apps. It covers the Gestures framework, primary and dismiss actions, gesture indicators, design guidance, and the 1.7 beta release of Compose for Wear OS. ### Source excerpt Posted by Chiara Chiappini, Developer Relation Engineer, Android Developer Relations One-handed gestures offer a convenient and touch-free way for users to interact with their watches, enabling them to perform key actions using only the hand on which the device is worn. First introduced on Pixel Watch with Wear OS 6.1, one-handed gestures made quick interactions effortless, such as starting and stopping a timer, accepting calls, and controlling media. Now, with Wear OS 7, we're expanding this functionality with a new Gestures framework that allows OEMs to map gestures to primary actions and dismissals, and an API to bring gesture control to the developer community. Starting with the 1.7 beta release of Compose for Wear OS, you can seamlessly integrate gesture control into your Wear Compose apps. To use this release, upgrade your Wear Compose dependency to: androidx.wear.compose:compose-material3:1.7.0-beta01 Designing for one-handed interaction The one-handed gestures framework is designed around two primary interaction patterns that allow users to take action without touching the screen: Primary action, which on Pixel Watch is mapped to a double-pinch gesture: this action should be mapped to the most important task in a given context. For example, users can perform this gesture to take a photo in a camera app, start/stop a timer, or accept an incoming call. Dismiss action, which on Pixel Watch is mapped to a wrist turn gesture: this action is mapped to system back by default and provides an intuitive way to close interruptive screens or get back to the watch face. It may be overridden for specific use cases, such as silencing an incoming phone call. These gestures are currently available on Pixel Watch 3 and newer, and the Wear OS gesture framework is available to all Wear OS device manufactures to adopt. Check out our new design guidance for integrating one-handed gestures into your Wear app. Integrating gestures with Compose on Wear OS To provide seamless gesture ## What's new in the Jetpack Compose August '26 release DevFeed: [What's new in the Jetpack Compose August '26 release]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-08-12T16:00:00Z Content type: release Language: en Sources: [Android Developers Blog]() Topics: [Compose](), [Jetpack Compose](), [Android](), [API](), [upgrade](), [Documentation]() Tags: [2026](), [android](), [compose](), [graphics](), [jetpack-compose](), [layout](), [performance](), [release](), [sdk](), [shaders](), [update](), [upgrade]() ### AI overview The Jetpack Compose August 2026 release is stable and brings version 1.12 to core Compose modules. It adds Mesh Gradients, Wide Color Gamut and HDR rendering support, named areas in Grid, Credential Manager integration, and testing and performance improvements. The release also includes breaking changes, including a requirement for API 37 and AGP 9.1.1. ### Source excerpt Posted by Nick Butcher, Product Manager, Jetpack Compose Today, the Jetpack Compose August '26 release is stable! This release brings version 1.12 across core Compose modules (see the full BOM mapping), introducing rich visual APIs like Mesh Gradients and Wide Color Gamut (WCG) support, structural layout features like named areas in Grid, seamless integration with Android's Credential Manager, and significant testing and performance improvements. To update your project to today's release, upgrade your Compose BOM version to 2026.08.00: implementation(platform("androidx.compose:compose-bom:2026.08.00")) Breaking Changes AGP & Compile SDK: Compose 1.12 updates compileSdk to API 37, requiring a minimum AGP 9.1.1. As a reminder, Compose will always target the latest compileSdk. Learn more about this change here. Modifier.onFirstVisible() is deprecated: Migrate to Modifier.onVisibilityChanged(), which provides more precise visibility threshold tracking. Graphics Mesh Gradients Compose 1.12 introduces MeshGradientPainter to help you create multi-point, organic color gradients. val rows = 1 val columns = 1 val gradientPainter = remember { MeshGradientPainter(rows, columns) { // Parameters: row, column, position, color setVertex(0, 0, Offset(0f, 0f), Color.Red) // Top-Left setVertex(0, 1, Offset(1f, 0f), Color.Blue) // Top-Right setVertex(1, 0, Offset(0f, 1f), Color.Green) // Bottom-Left setVertex(1, 1, Offset(1f, 1f), Color.Yellow) // Bottom-Right } } Box( modifier = modifier .aspectRatio(16/9f) .fillMaxWidth() .paint(gradientPainter) ) For more information and examples, see the documentation. Wide Color Gamut & HDR Support Modern displays offer extended color fidelity and higher dynamic range. In Compose 1.12, full pipeline support for Wide Color Gamut (P3) and HDR rendering has been enabled across Compose graphics, paint, and shaders. Colors defined in non-sRGB color spaces (such as Display P3) are preserved through to platform rendering without color clamping. Colors wi ## Media3 1.11 adds customizable Compose player controls, gestures, and video preloading DevFeed: [Media3 1.11 adds customizable Compose player controls, gestures, and video preloading]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-08-11T16:00:00Z Content type: release Language: en Sources: [Android Developers Blog]() Topics: [media3](), [Compose](), [Jetpack Compose](), [Playback](), [Android](), [ExoPlayer](), [Ktor]() Tags: [android](), [audio](), [compose](), [compose-ui](), [exoplayer](), [jetpack](), [jetpack-compose](), [ktor](), [media](), [media3](), [playback](), [release](), [releases](), [video]() ### AI overview Android Media3 1.11 introduces customizable Jetpack Compose player layouts, gesture-based playback controls, player recycling and preloading for short-form video feeds, improved Cast integration, a Ktor HTTP client extension, and new Ogg and WAV muxing utilities. ### Source excerpt Posted by Toni Heidenreich, Software Engineer, Android Media3 1.11 is out. Powering the vast majority of top Android media apps, this release brings new features, bug fixes, and improvements across playback, editing, and UI components. We're expanding our Jetpack Compose UI modules with customizable Player slots and easy to use defaults, interactive gestures, state observers, and short-form video preloading using PlayerPool. We also modernized the Media3 Cast integration with SystemUI Output Switcher support, introduced a new Ktor HTTP client network extension, and added new muxing utilities for Ogg and WAV files. Read on for key highlights, and check out the full release notes for a comprehensive list of changes. Playback UI and Compose With Android becoming Compose-first, we are continuing to expand the media3-ui-compose and media3-ui-compose-material3 modules. This update introduces more granular control over your player layout, richer interaction patterns, and deeper integration with Material3. Customizable Player layout The Material 3 Player Composable now supports dedicated content slots for topControls, centerControls, bottomControls, and errorOverlay. You can drop in your own Composables or use the ready-made defaults published in PlayerDefaults: Player( player = player, topControls = { PlayerDefaults.TopControls(player) }, centerControls = { PlayerDefaults.CenterControls(player) }, bottomControls = { PlayerDefaults.BottomControls(player) }, ) The Player Composable also integrates FocusRequester support, enabling seamless D-pad and keyboard navigation on Android TV, foldables, and desktop environments. Example for a Composable Player with customized controls Gestures and playback speed control PlaybackSpeedState now provides a fast-forward/slow-motion API. The demo-compose app showcases this with a long-press gesture to fast-forward playback and seeking with double tap. Combined with the ProgressSlider introduced in 1.10, the Compose player UI now offers ric ## Android Skills: Philosophy, Selection Criteria, and Evaluation Methodology DevFeed: [Android Skills: Philosophy, Selection Criteria, and Evaluation Methodology]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-08-06T16:00:00Z Content type: opinion Language: en Sources: [Android Developers Blog]() Topics: [Android skills](), [Large Language Model](), [Android Studio](), [Command-line interface]() Tags: [agent](), [agents](), [ai-assisted-coding](), [android-skills](), [android-studio](), [antigravity](), [cli](), [docs](), [gemini]() ### AI overview Android Developer Relations explains how official Android Skills are selected, focusing on verifiable knowledge gaps in state-of-the-art models and fast-moving topics. The article also discusses context costs, evaluation requirements, model compatibility, and use of the Android Knowledge Base. ### Source excerpt Posted by Jose Alcérreca, Developer Relations Engineer, Android Developer Relations We released the official Android Skills in April, and the response surpassed all our expectations. In this blog post, I'll address some of the feedback we received, explaining the philosophy and methodology behind the project. Hopefully, this will also help you understand what happens behind the scenes when you install and use skills, allowing you to make better use of tokens and your own time. Why are there so few official skills? Currently, we only consider new skills when there's a verifiable knowledge gap in state-of-the-art (SOTA) models. Put simply: you don't need to teach the model what it already knows. (Though there are a few exceptions--read on!) We've released around 20 official skills so far, and they intentionally target highly specific, fast-moving areas that standard models aren't fully grounded on yet--things like AGP 9, Navigation 3, advanced Camera APIs, and Perfetto SQL. What about core, more general, skills? Every installed skill injects 100-200 tokens into the baseline context of every task you start. If that skill actually activates, that count can quickly jump into the thousands. In most cases, hoarding basic skills is both counterproductive and expensive. Before installing a skill for writing basic Kotlin or Compose, consider if your LLM of choice really needs it, or if it knows those topics well enough already. Evaluating skills Before their release, each skill is tested against a comprehensive set of evals that prove that the skill delivers clear value. These evals should pass when the skill is active, and fail otherwise. Evals are to skills what integration tests are to code. timeout_s: 1200 repository: url: [redacted - internal git repo] working_dir: wear_compose_m3_empty_app category_ids: - wear prompt: |- Add a horizontal pager to MainActivity.kt. Have three pages in the pager. Each page should contain the text "Page 1", "Page 2", and "Page 3" respectively ## Delivering safer, age-appropriate experiences on Google Play DevFeed: [Delivering safer, age-appropriate experiences on Google Play]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-07-29T13:00:00Z Content type: release Language: en Sources: [Android Developers Blog]() Topics: [Google Play](), [API](), [Google](), [App](), [Availability]() Tags: [api](), [app](), [australia](), [availability](), [brazil](), [canada](), [developers](), [features](), [google](), [google-play](), [privacy](), [safety]() ### AI overview Google Play is expanding the privacy-preserving Play Age Signals API to all Play developers globally. After existing availability in Brazil, the rollout will begin in Australia and Canada and later reach users worldwide, allowing parents and adults to share age ranges with apps so developers can tailor safety experiences and content. ### Source excerpt Posted by Paul Feng, VP of Product Management, Google Play Providing a safe online experience and protecting users from harm is a top priority at Google Play. We take this responsibility seriously and have been investing continuously to offer baseline protections on our platform while also empowering parents with the tools they need to make decisions for their families. Importantly, we also want to empower Play developers with the capabilities to deliver age-appropriate experiences based on their app's content. To support this, today, we are taking another big step in our ongoing partnership with parents and developers by announcing the expansion of the Google Play Age Signals API to all Play developers globally. Building on current availability in Brazil, we will expand this experience first to users in Australia and Canada by mid-August, with a full global rollout to all users later this year. Empowering developers to create age-appropriate experiences The Play Age Signals API is a privacy-preserving tool that puts parents in the driver's seat allowing them to share their child's age range (e.g. 16-17) directly with apps. It also enables adults to easily share their age when prompted by the app developer. In turn, developers receive the signals they need to tailor their own in-app safety experiences and content for users in an age-appropriate way. We want to give developers the ability to choose the right protections for the nature of their app. A weather app, for example, shouldn't need the same safety settings as entertainment or media apps. Rather than enforcing one-size-fits-all rules, we give developers the flexibility to choose how they integrate safety signals. With this reliable signal, you retain complete agency to tailor your app's content, features, and settings to match your audience. Users have a choice to share their age range in a privacy-friendly way Simplifying controls for parents Parents shouldn't have to manage complex safety settings across do ## Celebrating 5 years of Jetpack Compose DevFeed: [Celebrating 5 years of Jetpack Compose]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-07-28T16:00:00Z Content type: article Language: en Sources: [Android Developers Blog]() Topics: [Compose](), [Jetpack Compose](), [Android](), [ui](), [Mobile](), [Kotlin](), [Compiler]() Tags: [android](), [compiler](), [compose](), [jetpack](), [jetpack-compose](), [kotlin](), [mobile](), [release](), [ui]() ### AI overview This retrospective marks five years since Jetpack Compose 1.0 was released on July 28, 2021. It describes Compose's evolution into a declarative UI toolkit using Kotlin, a compiler plugin, and a runtime; its expansion to additional form factors; and the community feedback that shaped the 1.0 release. The article also states that more than 68% of the top 1,000 apps use Compose in production and identifies Compose 1.11 as the latest version. ### Source excerpt Posted by Rebecca Franks, Developer Relations Engineer, Nick Butcher, Product Manager, Loryn Hairston, Product Marketing Manager, Android Today, we officially celebrate five years since the release of Jetpack Compose 1.0. From version 1.0, announced on July 28th, 2021, to our latest 1.11 release, we've seen the APIs evolve significantly over the years, and we're taking a moment to celebrate. When we officially announced the 1.0 release, we promised a simpler, faster, and more intuitive way to build native interfaces on Android. Looking back, it's safe to say that Compose didn't just deliver on that promise, but also completely changed the Android ecosystem, with more than 68% of the top 1,000 apps using it in production today. History Over the last five years, Compose has grown steadily. In the early days, we explored showing you how to build layouts with the basic Box, Row, and Column. Today, we've expanded Compose to work not just on mobile devices, but to other form factors such as Compose for TV, WearOS, Glance for Widgets, and even display glasses with Jetpack Compose Glimmer. We recorded an Android Developers Backstage episode with Clara Bayarri, Engineering Lead for Jetpack, and two former leads of the team, Romain Guy and Chet Haase, along with Tor Norbye, Senior Engineering Director. In this episode, they discuss the history of Compose and the early days of development. Compose highlights over the years Looking back The beginnings of Compose were very different from what you know today. Two projects were happening in parallel inside the Android team. At the time, the Views toolkit team was thinking of unbundling the UI Toolkit into a library to help with development speed, and make it easier for developers to adopt and control updates. Meanwhile, a team was working on a novel idea to build declarative layouts by embedding XML inside Kotlin, which looked something like this: Those two efforts merged to produce what you know today - a fully declarative UI Too ## How R8 made Kotlin Coroutines on Android 2x faster DevFeed: [How R8 made Kotlin Coroutines on Android 2x faster]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-07-27T13:00:00Z Content type: article Language: en Sources: [Android Developers Blog]() Topics: [Coroutines](), [Kotlin](), [R8](), [Android](), [Compose](), [Programming]() Tags: [android](), [android-gradle-plugin](), [app-performance](), [atomic](), [compose](), [coroutines](), [jetpack-compose](), [kotlin](), [perfetto](), [performance](), [programming](), [r8]() ### AI overview This article explains how R8 in AGP 9.2.0 optimizes Atomic*FieldUpdater calls into Unsafe variants, improving common operations by 2x to 4x. The optimization particularly benefits kotlinx.atomicfu and can make launching and cancelling Kotlin coroutines up to 2x faster. It also describes how coroutine overhead affected Jetpack Compose performance and how ART method traces helped identify bottlenecks. ### Source excerpt Posted by Andrei Shikov, Senior Software Engineer, Android Toolkit and Jonathan Starup, Software Engineer, R8 Team Starting from AGP 9.2.0, R8 optimizes most Atomic*FieldUpdater calls into Unsafe variants that perform 2x to 4x better on common operations. This has a particularly large impact on the kotlinx.atomicfu library that implements atomics for kotlinx.coroutines, making launching and cancelling coroutines up to 2x faster. In order to get the benefits, update your AGP to 9.2.0 or above. With the majority of Android apps adopting Kotlin as their main language of choice, kotlinx.coroutines has become a de-facto standard for asynchronous programming. The library offers a well-designed and structured way of managing concurrent flows that is native to Kotlin. Jetpack Compose was no exception, adopting coroutines for managing pointer events, animations and other interactions. At the time of writing, most concurrent APIs in Compose call suspend functions under the hood and are launching and/or cancelling coroutines to handle updates. As the Compose team started to investigate performance, coroutines were discovered to be a bottleneck for many operations that happen outside of composition. As an example, 80% of the time spent on creating and updating Modifier.clickable was consumed by launching and cancelling internal coroutines that handled InteractionSource updates. Based on those observations, much of early performance work was focused on removing coroutines from the default path and delaying initialization until necessary. The cost of a coroutine The easiest way to analyze a function's internal behavior on Android is to capture an Android Runtime (ART) method trace. An ART method trace is a tool that records the execution flow of an app, showing exactly which methods are called, their order, and how much time is spent in each, allowing developers to identify performance bottlenecks. For an empty LaunchedEffect { } call, it would look something like this: LaunchedE ## Optimize Android apps for Samsung Galaxy foldables and adaptive screen sizes DevFeed: [Optimize Android apps for Samsung Galaxy foldables and adaptive screen sizes]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-07-22T19:00:00Z Content type: tutorial Language: en Sources: [Android Developers Blog]() Topics: [Large Screen](), [samsung](), [Android](), [ui](), [Tooling]() Tags: [adaptive](), [android](), [devices](), [layout](), [samsung](), [tooling](), [ui]() ### AI overview This developer guidance explains how to adapt Android apps for Samsung's latest foldable and wearable devices, including the Galaxy Z Fold8. It recommends responsive layouts that account for changing orientations, ultra-wide aspect ratios, and dynamic display states. ### Source excerpt Posted by Fahd Imtiaz, Senior Product Manager and Miguel Montemayor, Developer Relations Engineer, Android Developer Experience Today at Galaxy Unpacked, Samsung unveiled its latest lineup of foldable and wearable devices. For developers, this means that the variety of form factors, screen sizes, and device postures your app needs to support is expanding once again. With devices like the Galaxy Z Fold8, the ecosystem is expanding to include hardware with a landscape-first natural orientation and a wider aspect ratio in its main display state. Whether a user is unfolding a large display, flipping open a cover screen, or glancing at their wrist, users expect a flawless experience. To help you meet this moment, we're sharing actionable guidance and new tooling updates to enable you to build adaptively proactively. Rethink layout architecture for dynamic displays, including ultra-wide foldables Building for the latest foldables means dropping assumptions about display orientation and size. This is especially true for the Galaxy Z Fold8, which adopts an ultra-wide display, adding to the variety of aspect ratios to account for. Devices with this landscape-first natural orientation show the limitations of hardcoded layout rules when users unfold the device. That's why we've introduced dedicated guidance for building for landscape foldables and trifolds. To build a responsive UI that handles these physics seamlessly, focus on the following core pillars: Build fluid, adaptive layouts: Wide aspect ratios and compact vertical heights require fluid UIs that scale responsively. Our updated adaptive design guidance advises considering the window class width first to determine layout changes, then adjusting for height. To let individual components fluidly adapt to the grid, structure your layout using flexible containers that allow your content to automatically wrap, span, and reflow. For design inspiration browse our adaptive sample app and dual-screen design galleries. Track act ## Build intelligent Android apps: On-device inference DevFeed: [Build intelligent Android apps: On-device inference]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-07-21T13:00:00Z Content type: article Language: en Sources: [Android Developers Blog]() Topics: [Android](), [On-device AI](), [ML Kit](), [Inference](), [gemma4](), [Google](), [Mobile]() Tags: [android](), [efficiency](), [features](), [gemini](), [gemma](), [gemma-4](), [google](), [inference](), [ml-kit](), [on-device](), [speed]() ### AI overview This Android developer article explains how to use Gemini Nano through ML Kit's Prompt API to build on-device features in the Jetpacker demo app. It covers itinerary summarization, expense management, and voice notes, emphasizing local processing, privacy, offline reliability, and avoiding cloud inference costs. The article reports that prompt iteration reduced response time from 13 seconds to under 2 seconds. ### Source excerpt Posted by Caren Chang, Developer Relations Engineer, Android Developer Relations Welcome back to the blog post series "Build intelligent Android apps" where we take a basic Android app and transform it into a personalized, intelligent, and agentic experience. In our previous post we introduced Jetpacker, the demo app we'll use throughout this series. In this blog post, we will share how you can use Gemini Nano through ML Kit's Prompt API to build intelligent on-device features. Building intelligent on-device features refers to the ability to process prompts and data directly on a device without sending data to a server. This offers a few advantages: User data can be processed locally on the device, preserving user privacy Functionality of the model is reliable even with spotty or no internet connection No additional cloud inference cost, since everything runs on the user's hardware With the benefits of on-device in mind, we identified three features to add in Jetpacker that can improve the user experience: summarizing trip itineraries, managing expenses, and capturing voice notes. On-device features in Jetpacker: Summarizing trip itineraries, managing expenses, and voice notes High quality tailored summarization of short texts The itinerary screen gives users a quick overview of all activities for a given trip. Since this screen contains a lot of information, it can quickly become overwhelming. To help users prepare without feeling overwhelmed, we can add a 'Get ready for your trip' section at the top. The romantic Paris trip is summarized as a classic Parisian adventure blending art, sights, and delicious food. A tip and some useful phrases are also added. By inputting a trip itinerary and asking an LLM to summarize it, we can generate a quick summary of the trip along with packing tips and useful local phrases. This is a great use case for an on-device model for several reasons: Performance and quality: Both the input and output text are relatively short. With tha ## Build intelligent Android apps: Cloud and hybrid inference DevFeed: [Build intelligent Android apps: Cloud and hybrid inference]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-07-21T13:00:00Z Content type: tutorial Language: en Sources: [Android Developers Blog]() Topics: [Android](), [Firebase](), [Artificial Intelligence](), [Inference](), [Cloud](), [ML Kit]() Tags: [ai](), [ai-models](), [android](), [cloud](), [firebase](), [firebase-ai-logic](), [gemini](), [grounding](), [hybrid-inference](), [inference](), [on-device]() ### AI overview This tutorial explains how to build cloud-hosted and hybrid AI features in Android apps with Firebase AI Logic. Using the Jetpacker app as an example, it covers web-grounded museum assistance, hybrid restaurant review drafting with Gemini Nano and cloud fallback, and custom-routed live translation for hotel support. ### Source excerpt Posted by Thomas Ezan, Jolanda Verhoef, Caren Chang, Senior Developer Relations Engineers, Android Developer Relations Welcome back to the blog post series "Build intelligent Android apps" where we take a basic Android app and transform it into a personalized, intelligent, and agentic experience. In our previous post we explored how to build intelligent on-device features using Gemini Nano through ML Kit's Prompt API. In this post, we will look at how you can leverage Firebase AI Logic to build cloud-hosted and hybrid AI features: Grounding answers in real-world context Routing requests dynamically between cloud and local execution using hybrid inference Translating content with custom routing systems Sometimes a use case requires AI models with greater world knowledge, a much larger context window, or the ability to handle complex queries. In those scenarios, we can leverage cloud models. Other times, you want the best of both worlds: using hybrid inference to run on-device when available to lower costs, while falling back to the cloud to ensure compatibility for all devices. Cloud and hybrid features in Jetpacker: Museum assistant with web grounding, hybrid restaurant review drafting, and support chat featuring custom-routed live translation. Let's look at how we implemented three cloud and hybrid features in Jetpacker: a museum assistant with web grounding hybrid restaurant review drafting hotel support chat featuring custom-routed live translation. Use LLM grounding for up-to-date informationMuseum assistant chatbot with LLM grounding The Museum assistant is an interactive chatbot designed to help users plan their museum visits. It provides visitors with up-to-date details regarding specific exhibits, current opening hours, ticket pricing, and more. Museum assistant is a chatbot that answers questions, such as 'How can I get a ticket discount for Le Louvre?' When building AI features, getting the model to answer with fresh, accurate, and specific real-world info ## Build intelligent Android apps: Introduction to Jetpacker DevFeed: [Build intelligent Android apps: Introduction to Jetpacker]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-07-21T13:00:00Z Content type: tutorial Language: en Sources: [Android Developers Blog]() Topics: [android-development](), [Mobile](), [On-device AI](), [Inference](), [genai](), [Open Source](), [App](), [ui](), [Google]() Tags: [android](), [android-development](), [apps](), [genai](), [google](), [inference](), [on-device](), [open-source](), [ui]() ### AI overview This introduction to a technical blog series presents Jetpacker, an open-source Android showcase app built for Google I/O. It outlines choices involving on-device, cloud, and hybrid inference, Android system integration, and agentic flows, with later posts promising implementation guidance and code examples. ### Source excerpt Posted by Jolanda Verhoef, Senior Developer Relations Engineer, Android Developer Relations Building GenAI features in your app usually means navigating through various models, APIs and architecture choices: Execution location: Where does your model run? On device, in the cloud, or both? Complexity: How complex is your setup? Are you doing a single inference call or do you need a more agentic flow? In-app or Android System: Should your feature be built into your Android app or does it fit better as an Android system integration? In this blog post series we'll navigate these choices with you. We will take you along on a journey, starting with a basic mobile app and transforming it into a personalized, intelligent, and agentic experience. Jetpacker: a demo travel app Jetpacker is a technical showcase app that our team built from the ground up for this year's Google I/O (built using Antigravity). At its core, Jetpacker helps users plan, explore, and enjoy their next big adventure. It shows an overview of your trips, the itinerary of each trip, and details of each event on that trip. Of course following all best practices of Android development, including a beautifully expressive Material UI design. And best of all? It's fully open source! Today we are publishing a series of technical blog posts diving deep into each of these features. We'll provide detailed implementation steps, code snippets, and architectural insights to help you build your own intelligent Android applications. On-device intelligence On-device features in Jetpacker: Summarizing trip itineraries, managing expenses, and voice notes Using an on-device model comes with no additional cloud inference costs, means you don't have to worry about internet connectivity, and lets users be confident that private information will be processed locally, on the device, without any of their data being sent to the cloud. In Jetpacker, we chose on-device inference for three of our features: The trip overview feature tra ## Build intelligent Android apps: Integrate into Android's intelligence system using AppFunctions DevFeed: [Build intelligent Android apps: Integrate into Android's intelligence system using AppFunctions]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-07-21T13:00:00Z Content type: tutorial Language: en Sources: [Android Developers Blog]() Topics: [Android](), [App](), [Artificial Intelligence](), [Development](), [Code](), [Mobile](), [User Interfaces](), [Firebase]() Tags: [agent](), [agentic](), [ai](), [android](), [android-apps](), [apps](), [code](), [development](), [how-to](), [mobile](), [user-interfaces]() ### AI overview This tutorial explains how to integrate Android AppFunctions into the JetPacker travel-planning app. It shows how privileged on-device agents can perform tasks such as logging expenses, managing itineraries, and capturing notes through voice or text commands, including background access that can simplify multitasking. ### Source excerpt Posted by Ben Weiss, Senior Developer Relations Engineer, Android Developer Relations Welcome back to the blog post series "Build intelligent Android apps" where we take a basic Android app and transform it into a personalized, intelligent, and agentic experience. In our previous post, we explored how to leverage Firebase AI Logic to build cloud-hosted and hybrid AI features. Traditional mobile UIs excel at focused, hands-on tasks, and the Android intelligence system is introducing complementary features to make complex, multi-step actions even easier. By supplementing traditional user interfaces, AppFunctions provide a powerful new entry point: A privileged agent on the device can access app features in the background. This can be particularly helpful when users are driving, walking or otherwise multitasking. In this article, we'll show you how we designed and integrated these capabilities into our travel planning app, JetPacker, using Android AppFunctions. We'll explore the rationale behind our feature choices, discuss the specialized tooling we used to accelerate development, and dive into the code that makes it all work. Designing AI-ready features: making choices that matter for your users To select which features to provide to the intelligence system, we looked for tasks where a voice or text command is objectively faster than tapping through screens. In this side-by-side screen recording you can see this contrast perfectly: on the left, a user tapping through multiple screens to log an expense; on the right, the same task completed instantly in the background via a privileged agent. Our first choice was expense tracking. Logging a coffee expense during a trip usually takes quite a few taps--unlocking the phone, opening the app, finding the active trip, navigating to the expenses tab, tapping the add button, taking a picture of the receipt, and checking the result. By providing the addExpense and getExpenses features as AppFunctions, the system agent handles th ## Upcoming Changes to the Nearby Connections API DevFeed: [Upcoming Changes to the Nearby Connections API]() Original publisher: [Read original article]() Author: Android Developers (noreply@blogger.com) Published: 2026-07-20T13:00:00Z Content type: release Language: en Sources: [Android Developers Blog]() Topics: [API](), [Bluetooth](), [Wi-Fi](), [Android]() Tags: [2026](), [android](), [api](), [bluetooth](), [developers](), [privacy](), [scheduled](), [wi-fi](), [workflows]() ### AI overview Android is changing the Nearby Connections API so it will no longer automatically enable Wi-Fi or Bluetooth radios for first- and third-party applications. Developers must ensure the radios are enabled and notify users when manual activation is required. The change is scheduled for late 2026. ### Source excerpt Posted by Wei Wang, Engineering Manager, Android BeTo User privacy and transparency are core to the Android experience. To better align with these principles, we are updating the default behavior of the Nearby Connections API regarding how it interacts with device radios. What is changing? Previously, the Nearby Connections API could automatically toggle Wi-Fi and Bluetooth radios ON to facilitate connections without explicit user intervention. Moving forward, the API will no longer automatically enable these radios for 1P and 3P applications. What this means for developers If your app relies on Nearby Connections, you will need to update your implementation to account for these changes: Manual Radio Management: You must ensure that the necessary radios (Wi-Fi or Bluetooth) are enabled before initiating Nearby Connections tasks. User Notification: If the required radios are disabled, your app must now inform the user and request that they enable them manually. The API will no longer programmatically turn them on for you. Timing These changes are scheduled to take effect in late 2026. We recommend reviewing your connection workflows now to ensure a seamless transition for your users. [Next page]()