Android Developers Blog

17 Things to know for Android developers at Google I/O

2026-05-19T06:00:00.000-07:00

Posted by Matthew McCullough, VP, Product Management, Android Developer

Today at Google I/O, we announced the many ways we’re powering agentic workflows to increase your productivity and ensure your apps shine across the expanding Android ecosystem. Here’s a recap of 17 of our favorite announcements for Android developers; you can also see what was announced last week in The Android Show: I/O Edition. Stay tuned over the next two days as we dive into all of the topics in more detail!

Build High Quality Android Apps Using Agents

1: Android CLI: helping you build with any agent, LLM, and tool

Android CLI is now stable. It offers programmatic tools that allow any AI agent, including Claude Code, Codex, or Antigravity, to perform core Android tasks much more easily and efficiently. With today’s release, it also provides a bridge to tap directly into the "heavy-lifting" power of Android Studio to give you the production-ready polish needed for professional Android development. By leveraging the new android studio commands, developers can now grant their preferred agents the ability to perform semantic symbol resolution, analyze files for warnings, and even render Jetpack Compose previews. This release also enables official support for "Journeys" through new Android skills, which enables agents to execute end-to-end UI tests under your direction. Watch the developer keynote, and tune into the What’s New in Android tools talk for more information.

You can now easily install Android CLI for use with Google Antigravity 2.0.

2: Build production-ready apps with ease in Google AI Studio

Developers and creators can now build native Android apps, simply with a prompt in Google AI Studio. The apps are built with development best practices like Jetpack Compose, Kotlin, and APIs that leverage our recommended developer patterns. Google AI Studio enables developers to prototype, iterate via an embedded emulator, and deploy to physical devices without heavy local installations. Developers are then able to take those apps and share them to Android devices, as well as share them with others for testing through Google Play Console’s internal testing track. If a developer wants to prepare their app for a wider release, they’re able to take it to Android Studio for advanced debugging, testing, and UI polish. Watch the developer keynote, and tune into the What’s New in Android tools talk for more information.

Use the embedded Android Emulator to create Android apps in Google AI Studio

3: Accelerating AI coding assistance with Android Bench

Android Bench is our LLM leaderboard for Android development challenges. The goal is to accelerate model improvements, so you have more useful options for AI assistance. Many of you have been using open-weight models for AI assistance, so we’re now adding commonly used ones, such as Gemma 4, to the leaderboard, so you can see how LLMs that offer offline access and additional flexibility for power-users measure up. We're continuously working on increasing the difficulty of challenges we’re giving LLMs, to continue encouraging more useful improvements.

4: Convert iOS apps to Android with the Migration Assistant in Android Studio

The Migration Assistant in Android Studio is designed to port apps from platforms like iOS, React Native, or web frameworks to native Android. By simply selecting an existing project, developers can have the agent intelligently map features, convert assets like storyboards and SVGs, and implement Android best practices using Jetpack Compose and our recommended Jetpack libraries. This effectively transforms what used to be weeks of manual porting into a streamlined agentic workflow that only takes hours. We shared a preview of the incoming feature in the developer keynote.

A sneak peek of the Migration Assistant converting an iOS app into a native Android app

Building AI Into Your Apps

5: Building Intelligent Apps with generative AI

Generative AI enables you to create apps that are more intelligent, personalized, and agentic than ever before. This year, we introduced the latest advancements in on-device intelligence with a preview of Gemini Nano 4 for tasks like data extraction and summarization. We also expanded cloud capabilities via Firebase AI Logic, allowing developers to leverage Gemini models with robust grounding (including URL, Maps, and web search) to build smarter, more capable assistants. Furthermore, we unveiled our hybrid inference approach and the new Agent Development Kit (ADK) for Android, alongside communication protocols like AG-UI and A2UI that simplify the creation of autonomous, agentic experiences. To start integrating these powerful features, explore the developer documentation, and watch the technical deep dive session where we showcase all these technologies.

6: Experiment with AppFunctions today

AppFunctions is an Android platform API with an accompanying Jetpack library to simplify building Android MCP integrations. It empowers your apps to behave like on device MCP servers, contributing functions that act as tools for use by agents and assistants. AppFunctions integration with Gemini is currently in a private preview with trusted testers, and you can begin preparing your apps already. You can sign up for the Early Access Program and start experimenting using the API guidance, sample, and skill today.

The Future is Adaptive

7: Android is now Compose First; Views are now in maintenance mode.

Compose is our standard for UI development, and we are moving to a Compose-first approach for all future guidance and libraries. Building on five years of evolution, the latest releases deliver a more mature toolkit, from the highly customizable Styles API to refined shared element transitions and enhanced input support. These updates allow you to build beautiful, adaptive apps with less code and better performance. Learn more about what Compose-first means for Android Development in our blog post.

Build Android UI with Compose

8: Building seamless Android experiences across devices with Jetpack Compose

The Android ecosystem is now Adaptive by Default, moving fluidly across phones, foldables, tablets, cars, XR, and expanding usages with Googlebook and connected displays. With over 580 million large-screen devices, and users on multiple devices spending up to 14x more on apps, the investment in adaptive design presents a massive opportunity. Jetpack Compose is the definitive engine for this transition, offering core tools like our latest Jetpack Navigation 3 release, new experimental Grid and FlexBox layouts, enhanced non-touch input support, and CameraX for correct camera previews across any window size. Furthermore, new skills in Android Studio make updating your existing app to adopt these adaptive patterns easier than ever. Notability’s Android debut sets a new standard for premium productivity apps. Built with Jetpack Compose, Navigation 3, and Kotlin Multiplatform, it delivers an intuitive, adaptive experience across devices.

9: Create seamless experiences for Googlebook

Last week we announced Googlebook, a high-performance laptop that provides a large-screen canvas for your existing apps. Building with adaptive principles today helps ensure your app will work on Googlebook. Get started by reviewing relevant design guidance and developer guidelines for desktop experiences. Try out the new Desktop Emulator available in the Android Studio Canary to to test your apps for this form factor today.

New Desktop Android Emulator

10: Unified widget development experience with Jetpack Glance

Android 17 marks a shift toward a single, Compose-based development model for all widgets. By unifying the experience across mobile, Wear OS, and cars through Jetpack Glance, you can soon scale UI components across the ecosystem with a familiar workflow.

The breakthrough this year is the integration of RemoteCompose. On mobile and cars, it powers high-fidelity animations, while on Wear OS, it allows Wear Widgets (formerly Tiles) to render complex UI logic natively on remote surfaces. This ensures peak performance on low-power hardware while allowing a cohesive user journey—like checking a flight status on your car dashboard and seeing gate change updates on your wrist.

Four widgets are shown cycling through in the Android Auto interface. A clock, a contact card, Google Home favorites and a photo.

11: Expand your reach on the road with Android for Cars
To help you expand your reach when you build in-car experiences, we're making it easier to build once and deliver your apps to Android Auto and Android Automotive OS. With the latest releases of the Car App Library, you can build customized, distraction-optimized templated media apps for both platforms. We're introducing new components and template capabilities to give you increased flexibility and more options for laying out content. Parked experiences are expanding too, with immersive video playback coming to Android Auto for phones running Android 17. You can easily adapt your video apps for these parked experiences; apply now to the early access program to publish in these beta categories and learn more about the latest updates in our blog.

12: Accelerate your development with Android XR Developer Preview 4

Inspired by the innovative experiences you’ve built for the platform, we’re continuing to mature our tools with Developer Preview 4 of the Android XR SDK. A key milestone in this journey is the transition of our core libraries, XR Runtime, Jetpack SceneCore, and ARCore for Jetpack XR, moving to Beta soon to provide a more stable and performant foundation. We are also accelerating hardware access through the Android XR Developer Catalyst Program, where you can apply for XREAL’s Project Aura, audio glasses, or display glasses developer kits. Watch The latest in Android XR session or read our blog to see how these updates help you build experiences across the ecosystem.

Early preview of the Geospatial API in ARCore for Jetpack XR, enabling high-precision anchoring of digital content to real-world locations.

13: Android is your new home for professional-grade media experiences

Android 17 streamlines the entire media lifecycle with a production-ready toolkit. High-fidelity capture is now simplified with the CameraXViewfinder Composable, which handles complex scaling and responsiveness on foldables and tablets. For post-production, the new Media3 AI Effects library provides a single interface for premium features like Magic Eraser and Studio Sound, automatically optimizing for the device's hardware.

The pipeline is completed by CodecDB, offering chipset-specific encoding recommendations to eliminate export noise, and a new Scrubbing Mode in ExoPlayer for ultra-smooth seeking. Whether you’re compositing multi-asset edits with Media3 Transformer or using the streamlined CastPlayer API, these updates ensure a professional-grade experience with significantly less development overhead.

Low Light Boost and Magic Eraser in action

14: Increase app discovery and engagement on Google TV

Pointer remotes, which enable motion-controlled input, will be a future way for users to interact with Google TV as it unlocks faster user navigation. App developers can start declaring support for pointing input to ensure their apps are discoverable on future TVs with pointer remotes. Additionally, the Engage SDK, formerly known as the Video Discovery API, optimizes Resumption, Entitlements, and Recommendations across all Google TV form factors to boost app discovery and engagement. It’s a great time to start onboarding the Engage SDK now, since the legacy Watch Next API, which has been powering your continue watching 1.0 experience, will lose support in the 2nd half of 2027. Get all the details in our blog.

15: Performance: the foundation of a great app experience

To help developers navigate memory limits in Android 17, we've launched a suite of optimization tools. The R8 Configuration Analyzer identifies keep rules that are bloating your binary, while ProfilingManager and the integrated LeakCanary in Android Studio streamline memory leak detection. Furthermore, the new Android Performance Analyzer offers advanced AI integration for complex trace analysis and automated SQL query generation to pinpoint performance bottlenecks.

And The Latest on Driving Business Growth

16: What’s new in Google Play

Today's updates from Google Play help expand your reach and scale your business with less complexity. We’re redefining Play Store discovery with an immersive, short-form video format called Play Shorts, while expanding your audience beyond the store with app discovery in the Gemini app on Android and web. Plus, we’re introducing powerful new capabilities like agentic catalog management for seamless bulk price and SKU updates, and using Gemini models to enable Play Console to pre-populate store listings from imported documents—making global localization effortless.

Gemini will provide users with app suggestions during a search

17: And of course, Android 17

Android 17 includes new performance & system architecture improvements (in addition to app memory limits) like a lock-free MessageQueue and a GC with more frequent, less intensive young-generation collections to ensure system-wide stability and smoother UIs. The new contact picker and eyedropper API help minimize the use of sensitive permissions and unnecessary access to user data.

Review the behavior changes to make sure your app is ready for Android 17, including background audio hardening and SMS OTP protection. Get ready to target Android 17 (API 37) with changes such as mandatory large-screen resizability, certificate transparency by default, and restricted local network access. You can start testing today by enrolling your device in the Beta or using the latest 17.0 emulator images.

One more thing. the third beta of our Android 17 quarterly platform release (QPR1) just came out, and it contains a minor SDK release to support a few features that just couldn't wait for QPR2.

Check out all of the Android & Play Content at Google I/O

This was just a preview of some of the updates for Android developers at Google I/O. Tune into What’s New in Android for the latest news and announcements and follow Google I/O for much more over the following week!

Build native Android apps in Google AI Studio

2026-05-19T05:45:00.000-07:00

Posted by Emma-Louise Leavey, Group Product Manager and Mike Taylor-Cai, Product Manager

Starting today Google AI Studio can build entire Android apps for you in minutes from just a prompt. You don't need to install any software or configure any libraries, which significantly lowers the barrier to development. Whether you’re a seasoned developer looking to prototype at lightning speed or a creator building your first-ever mobile experience, you can now go from a single prompt to a high-quality, Kotlin-based Android app in AI Studio. You can easily install the app on your device, share it with others for testing, or send it to Android Studio for any further development.

The power of native Android

While AI has made it easy to generate web-based apps, people want more on their mobile devices. They expect the beautiful and usable modern app design and capabilities that come with native Android user experiences, built with the Kotlin programming language using Jetpack Compose, the official and recommended toolkit for Android development. Native Android apps bring the reliability of offline support, continuous background services, and the deep integration of hardware sensors like GPS, Bluetooth, and NFC. We've brought the technology that enables you to quickly create new projects with Gemini in Android Studio directly into the web-based AI Studio. Now, you get the best of both worlds: the ease of a prompt-based interface paired with the power of the Android SDK, all in your browser, no installation required.

A seamless, end-to-end workflow

We have streamlined the entire development lifecycle so you can focus on your idea:

1. Create your app and iterate in the cloud: Use the embedded Android Emulator directly in your browser to preview and interact with your app as it’s being built. No heavy SDKs to download, no local setup required.

Use the embedded Android Emulator to create and edit Android Apps right in the web browser

2. Install instantly: Connect your Android phone using a USB cable and install your app directly from AI Studio using the integrated Android Debug Bridge (adb).

Install the app on your Android device

3. Streamlined Publish to Google Play: Using your Google Play developer account, you can now publish your app directly from AI Studio for testing. AI Studio will automatically create your app record, package the bundle, and upload it to an internal testing track in Google Play Developer Console. Your app is available for you to install within minutes, and you can automatically update your app on your device as you develop it further in AI Studio.

Publish the app to an internal test track in Google Play

Seamless app development handoff

As you iterate on your app in AI Studio, you may find you need more advanced Android tools or support for a wider variety of Android device types. To move beyond the browser, you can seamlessly hand off your project to Android Studio by downloading a ZIP file or exporting it directly to GitHub.

Download zip file of Android app project files

When transitioning to a team environment or local development, you can leverage any IDE or agent you prefer. For a specialized experience, we recommend Gemini in Android Studio, which features models designed with Android in mind, or Antigravity, which integrates Android CLI commands into Google’s agentic development platform. This workflow makes building high-quality apps more accessible while giving you total flexibility in how you use AI to scale your project.

Start building today

To ensure a safe, high-quality ecosystem from day one, we have focused our initial release on specific capabilities including:

Personal utilities and simple social apps: You can rapidly prototype single or multi-screen apps, such as habit trackers, study quizzes, or event itineraries.
Hardware-enabled experiences: Because you are building native apps, you can leverage device features like the Camera, GPS/Location, Accelerometer and Bluetooth using the native Android APIs, letting you optimize hardware-level performance.
AI-powered experiences: You can create apps that feature Gemini API integrations, seamlessly embedding powerful AI capabilities directly into your mobile experience.

What’s Next?

We are moving fast to expand what’s possible for creators in AI Studio. Here is a sneak peek at what is coming soon:

Managing Google Play Test Tracks: Coming soon, we will be adding the ability to invite testers to try your app directly from AI Studio.
Firebase integrations: Out-of-the-box support for Firestore, Firebase Auth, Firebase App Check and other tooling critical for Android developers is coming soon.

Head over to Google AI Studio right now to start building. Here is some inspiration to get you started…

Turn your Google Pixel Watch into an aviation assistant

Prompt:

Build a small airplane "6-pack" instrument app for Google Pixel Watch. The 6 instruments should include attitude indicator, airspeed indicator, altimeter, turn coordinator, vertical speed indicator, and heading indicator. Use the Google Pixel Watch's sensors to power the instruments and display them clearly. Display one instrument at a time on the display. Swiping to the left or right should cycle through the instruments.

Interactive Harmonium app on Google Pixel Fold
Prompt: Build a Harmonium app for Pixel Fold devices, which plays like the instrument based on the hinge angle and touch gestures. The app should simulate the bellows and reeds accurately.

An Android app for guitarists to become better musicians by jamming to backing tracks

Prompt:

Build an Android guitar practice companion app that features a two-tab navigation system: 'Fretboard' and 'Library'.

The 'Fretboard' primary screen must contain an interactive guitar neck UI that visually maps out user-selected root notes, musical scales, and chords. Above the fretboard, implement a WebView-based YouTube player configured to play embedded videos inline. Additionally, include an AI generation feature that uses Retrofit to call Gemini Lyria 3 to create custom, 30-second backing tracks based on the user's currently selected key and scale. The generated audio files and their metadata must be saved locally using a database and displayed as a list in the 'Library' tab, where users can delete or play them.

Finally, implement a persistent, globally visible mini audio player at the bottom of the screen, complete with play/pause toggles, a progress slider for seeking, and timestamp text, allowing the user to seamlessly practice on the fretboard tab while listening to their tracks.

We are looking forward to seeing what you build next!

Explore this announcement and all Google I/O 2026 updates on io.google.

Increasing app discovery and engagement on Google TV

2026-05-19T05:00:00.000-07:00

Posted by Paul Lammertsma, Developer Relations Engineer

With over 300 million monthly active devices across Google TV and Android TV, it’s clear that the living room is a massive, distinct platform for apps to accelerate growth. Today, we’re excited to share Google TV features and developer tools designed to increase the discoverability of your content and prepare your app for future TV experiences.

Drive discovery and engagement with Gemini

Last year, we brought our AI voice assistant, Gemini, to our platform, so that people can easily find what to watch, learn something new on the big screen, and get everyday tasks done with just their voice.

Since launch, we’ve made improvements to how Gemini provides tailored responses to questions. Gemini shares a mix of visuals, videos, and text to help users find what they need, when they need it. For our streaming partners, Gemini is a helpful discovery engine—pulling from your app's metadata to surface your relevant content to viewers.

Declare support for pointing modality

The TV experience that we once knew is changing. Gemini is changing the way we discover and stream content with voice, but how we use the remote is evolving, too.

Pointer remotes bring motion-controlled input to the big screen, unlocking faster user navigation across the Google TV Home page and within content-heavy apps. To ensure your app is ready for this shift and provides a great experience for all users, now is the time to start thinking about pointing input. Here’s how to get started:

1. Adapt your TV app UI Library

You’ll need support for hover states, scrollable containers, and cursor clicks to enable pointer remote interactions for your app on Google TV. While implementation varies by UI stack, Jetpack Compose streamlines this transition, as most core components handle these multi-modal interactions natively out of the box.

Hover state: Every focusable element on your screen (buttons, movie posters, setting toggles) needs a clear visual feedback mechanism for a hover state. This is often subtler than a focus state but critical for feedback.
Scrollable containers: Pointer remotes will also have a small circular touchpad for scrolling. Users can use this touchpad to scroll up or down, or left or right in your app. Your app will need to respond to touch events to scroll.
Cursor clicks: Many TV apps today expect a simple D-pad OKAY button “click.” With a pointer remote, a user may “click” on an element that’s not the D-pad focus state, but is instead from a hovered state (similar to a mouse click).

2. Test pointing interactions with a mouse today

To see how your app handles hover, scroll, and clicks, simply connect a bluetooth mouse or wired mouse to your Google TV. Keep in mind that a mouse has more precise control, since users are closer to the screen and typically rest the mouse in a stable position. Pointer remotes can often be less precise, since users are sometimes 10 feet away from the screen, making rough gestures with the remote from their couch. As a TV designer or developer, you can mitigate this lack of input precision by having larger hover targets for elements.

3. Declare TV app support for pointer remotes on Google Play

Finally, tell Google Play that your TV app is designed to work with a pointer. This ensures that users with pointer remotes will be able to easily find, install, and interact with your app.

Within your AndroidManifest.xml, declare the meta-data tag, android.software.leanback.supports_touch. This tag informs the platform that your TV app “spatially supports touch,” since pointer remotes simulate touch events from a distance.

AndroidManifest.xml

<manifest ...>
    <!-- Signal whether the app is adaptive or built just for TV -->
    <uses-feature android:name="android.software.leanback" android:required="true|false" />

    <!-- Ensure the app can be installed on conventional TVs -->
    <uses-feature android:name="android.hardware.touchscreen" android:required="false" />

    <!-- Signal whether the app supports pointer remotes -->
    <meta-data android:name="android.software.leanback.supports_touch" android:value="true|false"/>

    <application ...>
        ...
    </application>
</manifest>

Tips:

The android.software.leanback feature declaration indicates that your app supports D-pad navigation and is intended for distribution only on TV devices via Google Play.
The new software attribute of android.software.leanback.supports_touch declares that in addition to D-pad, you have ensured that your TV app works well for pointer/cursor experiences via mouse (of today) and pointer remotes (of future).
If you haven't already, now is the time to adopt Jetpack Compose. Hover, scroll, and clicks are common input modalities that are supported on various form factors, and building your app with an adaptive UI framework enables code reusability and reduced maintenance.

Onboard the Engage SDK

The Engage SDK, formerly known as the Video Discovery API, optimizes Resumption, Entitlements, and Recommendations across all Google TV form factors to boost app discovery and engagement.

Resumption: Partners can easily display a user's paused video within the 'Continue Watching' row from the Home page.
Entitlements: The Engage SDK streamlines entitlement management, which matches app content to user eligibility. Users appreciate this because they can enjoy personalized recommendations without needing to manually update all their subscription details. This allows partners to connect with users across multiple discovery points on Google TV.
Recommendations: The Engage SDK even highlights personalized recommendations based on content that users watched inside apps.

It’s a great time to start onboarding the Engage SDK now, since the legacy Watch Next API, which has been powering your continue watching 1.0 experience, will lose support in the 2nd half of 2027. To get started, head to goo.gle/engage-tv to learn more.

We're excited to see how our latest Gemini experience and developer tools will optimize your discovery and drive user engagement on our platform.

Explore this announcement and all Google I/O 2026 updates on io.google.

Android CLI Now Stable 1.0: Accelerate developing for Android using any agent

2026-05-19T04:45:00.000-07:00

Posted by Simona Milanovic and Ben Trengrove, Developer Relations Engineers

As Android developers, you have many choices when it comes to the agents, tools, command-line interfaces (CLI), and LLMs you use for app development. Whether you use Gemini in Android Studio, Antigravity 2.0, Antigravity CLI, or third-party agents like Anthropic's Claude Code or OpenAI'sCodex, our mission remains the same: to ensure that high-quality Android development is possible everywhere.

At Google I/O ‘26, we shared the latest leaps forward in agentic development, and showcased some of the newest capabilities of Android CLI—now stable at version 1.0 and ready for all Android developers to use. From new skills to enabling agent access to powerful Android Studio capabilities, we’re giving your agents the right tools to build alongside you.

If you’re already using Android CLI and want to jump into using all the new features, just run android update. Otherwise, read further to learn more about how we’re making the agents you choose be better at building for Android.

Android development unlocked for Antigravity

Google Antigravity now includes an optional bundle of Android resources—including the Android CLI and skills—that you can install. You can either install the bundle during onboarding after installation, or later from the Settings > Customizations > Build With Google Plugins menu.

This provides Antigravity with all the powerful tools and knowledge of Android CLI, enabling it to perform the core tasks necessary for Android app development more easily and efficiently—from creating projects to deploying your app on a new Android virtual device.

You can now easily install Android CLI for use with Google Antigravity 2.0.

Unlocking Android Studio capabilities for any agent

Android CLI provides a lightweight interface for AI Agents to perform tasks and retrieve knowledge about Android development. However, there's benefits to specialization — Android Studio contains over a decade of Android expertise, built to handle even the most complex Android projects. This includes Android Studio's powerful static analysis engine, refactoring tools, dependency management, UI design and rendering libraries, and more. AI Agents can now tap into Android Studio's tools to gain many of these same capabilities.

Your agents can now use Android CLI to access powerful capabilities of Android Studio.

The latest version of Android CLI introduces the new android studio command. This enables the agent of your choice to leverage the deep, contextual capabilities of Android Studio to better understand and perform actions on an open Android project. By running Android Studio alongside your preferred agent with Android CLI, your agent’s tasks can more efficiently navigate the codebase to produce more precise code changes. And, when you use Android CLI to create and iterate on your project, transitioning to Android Studio is much easier, so that you can use the purpose built tools—such as, performance profilers, Compose Previews, and Android Device Streaming—to get that production-grade polish.

When you have a project open in the latest preview version of Android Studio Quail, you (or your agent) can run the following command to check whether Android CLI has a connection established with your open project:

$ android studio check
pid: 32942
version: Android Studio
Projects:
    READY     JetSet /Users/adarshf/AndroidStudioProjects/jetset-main

From there, the agents can use the android studio command to access powerful IDE tools to interact with projects more efficiently. Key commands include:

analyze-file: Analyzes a file for errors and warnings using the editor's built-in inspections.
find-declaration: Finds the exact definition site of a symbol (class, method, variable, field, constant, or Android resource/color) across the project using semantic resolution.
find-usages: Finds all references and declarations of a symbol (class, method, variable, or Android resource) across the entire project using semantic analysis.
render-compose-preview: Renders a Jetpack Compose UI Preview and returns a path to the image and UI hierarchy if successful.
version-lookup: Get the latest information about which versions for specified app dependencies are available in common repositories, such as the Google Maven repository. By providing a programmatic solution, dependency management is less tedious and much less prone to flakiness.
open-file: Opens a file directly in Android Studio. This is useful if the agent wants to direct your attention to view Compose Previews, performance traces, or other specific files in the IDE.

For example, agents can now run the following commands to render a Compose preview for a new layout for your Android app, and then open the previews in Android Studio for you to take advantage of seeing multiple Compose Previews side by side and make AI-assisted edits right from the IDE.

$ android studio find-declaration HotelDetailScreen
$ android studio analyze-file .../JetPacker/feature/detail/src/main/java/com/example/jetset/feature/detail/HotelDetailScreen.kt
$ android studio open-file feature/detail/src/main/java/com/example/jetset/feature/detail/HotelDetailScreen.kt

To learn more about how to use these commands, run android help. And, to make sure your agents understand how to work with this tool, make sure to update the Android CLI skill by running android init.

More ways to get started

To make integrating Android CLI into your environments as seamless as possible, we’re making it available in more ways. You can now download and install Android CLI using more package managers: apt-get, winget, and homebrew. For example, you can run the following to install Android CLI using winget:

winget install -e --id Google.AndroidCLI

We’ve also updated the installation to a user-local directory, by default. You can find the commands for all supported operating systems plus additional download options on the Android CLI page.

Support for Journeys

Journeys are natural language descriptions of core user experiences.

(sped up) An agent running a Journey it generated for an app.

Agents can run these journeys using the Android CLI to navigate your app exactly like a user would. This unlocks entirely new ways to test, validate, or collect data across the critical experiences of your app, all driven by natural language and executed by your agent.

Expanding Android skills

To help models better understand and execute specific patterns that follow our best practices, we are continuing to expand our library of Android skills. We’re shipping new skills that make Android development everywhere more capable, efficient, and productive:

Display Glasses and Jetpack Compose Glimmer for XR: Provides guidelines for developing projected applications for Android Display Glasses using the Jetpack Compose Glimmer UI toolkit.
Migration to CameraX: Helps you migrate legacy Android camera implementations (Camera1 or raw Camera2 APIs) to CameraX.
Perfetto SQL: Translates natural language data prompts into Perfetto SQL queries and executes them against a local trace file.
Adaptive UI: Instructions to make or update an app's UI so that it adapts to different Android devices
Testing setup: Creates a basic testing strategy.
Styles: Helps with adoption of the new Jetpack Compose Style API for new components, and supports migration to Styles API.
AppFunctions: Analyzes Android codebases to recommend and implement new AppFunctions, and refines KDoc documentation for Model Context Protocol optimization.

You can add these new skills to your workflow directly from the command line. To help your agents understand and use Android CLI right away, you can initialize your environment and install the base android-cli skill by running:

android init

From there, you can browse and set up your agent workflow by searching for the exact capabilities your agent needs:

android skills list

Once you've found the right skill, install it to your environment by running:

android skills add –skill=<skill-name>

Get started today

To download the stable 1.0 release of the Android CLI, explore the new tools, and browse the complete documentation, head over to d.android.com/tools/agents today! Also, make sure you update to the latest preview version of Android Studio to unlock the latest features that Android CLI offers. We can't wait to see what you build with Android CLI 1.0 and how these new features supercharge your daily workflows. Join our vibrant community on LinkedIn, Medium, YouTube, or X and share your feedback.

Explore this announcement and all Google I/O 2026 updates on io.google.

Build for the future with the Android XR Developer Catalyst Program — Apply now!

2026-05-19T04:15:00.000-07:00

Posted by Android XR Team

The Android XR ecosystem is expanding, and we’re committed to supporting developers who will build its next great experiences. Today, we’re opening applications for the Android XR Developer Catalyst Program, a dedicated initiative to accelerate the development of Android XR apps ready to launch within the next year.

This program is designed to provide the resources, hardware, and grants to help you build and scale innovative experiences across wired XR glasses, like XREAL’s Project Aura, and intelligent eyewear (audio and display glasses). We are especially interested in seeing innovative experiences across media, gaming, productivity, and health, but we welcome any unique use case that helps users expand what's possible.

Why join the catalyst program?

We want to help developers navigate common barriers to entry for XR development by providing:

Development Kits: Get early access to hardware development kits for wired XR glasses (XREAL’s Project Aura) and / or intelligent eyewear (audio and display glasses).
Technical support: Gain access to specialized technical resources and support forums specifically designed to help you prepare your app for Google Play.
Grant Opportunities: Submit a request and you may be eligible to receive a non-recoupable grant to accelerate your development.

Ready to start building?

Applications are open to developers looking to publish apps for the Android XR ecosystem in the next 6-12 months. You can build with Kotlin and the Jetpack XR SDK, or with Unity, Unreal Engine or Godot. If you need a spark of inspiration, you can check out existing XR Experiments and Samples to see how you can use the SDK for everything from spatial music to navigation.

Once you have your concept ready, be sure to submit your application by June 30th by 11:59PM PDT. We can’t wait to see what you build.

Start Your Application

Explore this announcement and all Google I/O 2026 updates on io.google.

Adaptive development for the expanding Android ecosystem

2026-05-19T04:00:00.000-07:00

Posted Fahd Imtiaz, Senior Product Manager, Adaptive Apps

With the release of Android 17, we are transitioning into an adaptive first development standard. Your users no longer rely on a single form factor; they transition between phones, foldables, tablets, laptops, automotive displays, and immersive XR environments throughout their day.

Now, with over 580 million large screen devices in the hands of users, adaptive is no longer just a technical goal. It’s a massive opportunity to reach highly engaged users. To thrive in this multi-device ecosystem, your app must be resilient, responsive, and ready for virtually any surface.

The multi-device opportunity

The Android device universe is now a multi device reality. Users are buying into entire ecosystems, moving from handhelds to foldables, tablets, and cars. And the data is clear: users with multiple devices often spend more than users with only a phone.

Drive higher revenue: Multi-device users spend 9x more on average than phone only users. On foldables, that engagement multiplier can reach 14x. (Source: Google Internal Data, 2026)
Capture high-value segments: Large-screen users (tablets, foldables, and Chromebooks) typically spend roughly 5x more than phone-only users.

To help amplify your reach with these users, we've rolled out a new badge in Google Play. Apps meeting adaptive quality standards now earn an "Optimized for large screens" badge, making it easier for users to discover high quality experiences.

Latest in adaptive Android development from Google I/O

Android 17, new Jetpack updates and advanced tools help you build apps that feel native across diverse surfaces, from pocket-sized foldables to Googlebooks.

Adaptive by default: Android 17 updates

In Android 16, we introduced significant changes to orientation and resizability APIs to facilitate adaptive behavior, while providing a temporary opt-out to help you make the transition. Android 17 (API level 37) sets a new quality baseline by removing that developer opt-out for orientation and resizability restrictions on large screen devices (sw > 600 dp). When you target API level 37, your app must be capable of adapting to a variety of display sizes. This helps your app deliver an experience that matches the users’ expectations.

Tip: You can start testing these behaviors by enabling the UNIVERSAL_RESIZABLE_BY_DEFAULT flag in App Compatibility Changes under Developer Options under SDK 36.

Your app on even more surfaces

In addition to your mobile app running on large screens devices including foldables, tablets, Chromebooks and XR, we are also expanding the Android surface area for your mobile apps:

Connected Displays: Now in stable as of Android 16 QPR3, Connected Displays support enables supported Pixel and Samsung mobile devices to transform into a desktop environment via external display support.
Automotive & TV: With the Car Ready Mobile Apps program and enhanced pointer support for Android TV, your adaptive app can now benefit from engagement on the infotainment system and the living room with ease.

Googlebook: Evolving desktop computing

Talking about more surfaces, we’re evolving our work in the desktop space with Googlebook, the next generation of ChromeOS. Built with parts of the Android stack, we are enabling your apps to achieve a "laptop-class" feel with native level performance.

Building with adaptive principles today helps ensure your app is ready for this new generation of high performance hardware.

To help you prepare for this new generation of devices, we’ve released comprehensive new documentation including comprehensive design guidance and developer guidelines. Built on the principles of adaptive, these guidelines offer a playbook for transitioning your mobile apps to offer a premium desktop class experience.

Try out the new Desktop Emulator, available now in the Android Studio Canary to get started today.

Building adaptive layouts with Jetpack Compose

We are now Compose first and Jetpack Compose is our recommended way to build modern, adaptive UIs to help you manage layout complexity efficiently.

New layout primitives: We’re introducing Grid and FlexBox layouts, bringing powerful, CSS-inspired capabilities to Compose for both 1D and 2D layouts.
Navigation 3: The 1.1 release for compose-navigation3 introduces Scene Decorators, allowing you to wrap your screens with other content, such as bars, rails and dialogs.
MediaQuery API: The new experimental MediaQuery API provides observable device UI capabilities, such as window size and pointer precision, that allow you to adapt and optimize your app's UI for the current device configuration.
Styles API: Dynamically evolve the visual properties of your app using the new state-based experimental Styles API.

Beyond layouts: non-touch input

Adaptive app quality goes beyond window dimensions, including handling non-touch input paradigms e.g. keyboard, trackpad, mouse, stylus that are primary input methods on large screens.

Trackpad support: Compose 1.11 now brings trackpad support on par with mouse, and provides new APIs to automate non-touch input testing including TrackpadInjectionScope and performTrackpadInput.
Focus indicators: Enhance accessibility with built-in support for standard focus rings in Compose.

AI-Powered developer tools

Android Studio and Android CLI are evolving to help you architect adaptive apps faster than ever.

Android Skills: These modular AI instructions are designed to assist any LLM through complex architectural tasks, including helping you with View-to-Compose migrations, implementing adaptive layouts, Navigation 2 to Navigation 3 transformation, and migrating off of legacy camera libraries to CameraX. Get started with these latest skills on the Android Skills Github repo and via Android CLI.
New Project Agent: Available in Android Studio Panda 2, this agent initializes new projects with adaptive best practices by default.

For developers working with cross-platform frameworks, we continue to provide full support for Web, Qt, and Unity. Whether you are building from scratch or modernizing a legacy codebase, these tools are designed to meet your users exactly where they are.

We’re excited to see how you bring these new adaptive capabilities to your apps. By moving to an adaptive first approach, you’re not just reaching more users but you’re delivering the seamless, high quality experiences they expect across the entire Android device landscape.

Get started with adaptive development and start shaping the future of your apps.

Explore this announcement and all Google I/O 2026 updates on io.google.

Updates to the Android XR SDK: Introducing Developer Preview 4

2026-05-19T03:45:00.000-07:00

Posted by Stevan Silva, Group Product Manager and Amy Zeppenfeld, Developer Relations Engineer

Today we're excited to launch Developer Preview 4 of the Android XR SDK, continuing our focus on unifying cross-device development for headsets, wired XR glasses, and intelligent eyewear. To keep our platform intuitive, we are adopting more descriptive naming for our form factors, where AI glasses are now audio glasses and display AI glasses are now display glasses, with these changes appearing in our documentation starting today.

This release is packed with updates that help you build incredible experiences for XR devices, enable deeper immersive experiences on XR headsets, and streamline the path for creating augmented experiences on audio and display glasses. Also, our core libraries—including XR Runtime, Jetpack SceneCore, and ARCore for Jetpack XR— will be officially moving to Beta soon!

To give you early access to hardware and resources for building immersive and augmented experiences on upcoming devices—like display and audio glasses and XREAL’s Project Aura — we’re announcing the Android XR Developer Catalyst Program. Learn more and start your application today.

Building Augmented Experiences for Audio and Display Glasses

Starting out with our libraries for augmented experiences, Developer Preview 4 introduces new APIs that help you create and test your apps.

Jetpack Projected: Device Availability and ProjectedTestRule APIs

The Jetpack Projected library helps bridge app experiences from the phone to the user's field of view. We've added the Device Availability API, which consolidates wear state and connectivity signals into standard Android Lifecycle.State values. This lets you adjust your applications behavior based on whether the device is worn.

val xrDevice = XrDevice.getCurrentDevice(projectedContext)

// Observe the device lifecycle flow
xrDevice.getLifecycle().currentStateFlow
    .collect { state ->
        when (state) {
            Lifecycle.State.STARTED -> { /* Device is available (worn) */ }
            Lifecycle.State.CREATED -> { /* Device is unavailable (not worn) */ }
            Lifecycle.State.DESTROYED -> { /* Device is DISCONNECTED */ }
        }
    }

To simplify testing, the new ProjectedTestRule API in the projected-testing artifact automates the setup of projected test environments. This helps you write clean, reliable unit tests without the boilerplate code.

// from the 'androidx.xr.projected:projected-testing:1.0.0-alpha07' artifact
@get:Rule
val projectedTestRule = ProjectedTestRule()

@Test
fun testProjectedContextInitialization() {
    // by default, ProjectedTestRule automatically creates and connects
    // a projected device before each test
    val projectedContext = ProjectedContext.createProjectedDeviceContext(context)

    // assert the projected context is successfully initialized
    assertThat(projectedContext).isNotNull()
}

Jetpack Compose Glimmer: Google Sans Flex and new components

Our UI library for display glasses, Jetpack Compose Glimmer, now includes Google Sans Flex for improved legibility on optical see-through displays. We’ve also added several interactive components:

Stacks: Designed for touchpad-optimized groups, showing one item at a time.
Title Chips: Provides categorization and context for content cards.

Building Immersive Experiences for XR Headsets and Wired XR Glasses

If you're looking to build fully immersive experiences for XR Headsets and wired XR Glasses, we have several big updates.

Beta Transition & Modern Architecture

XR Runtime, Jetpack SceneCore, and the ARCore for Jetpack XR perception features (Depth Maps, Eye/Hand Tracking, Hit Testing, and Spatial Anchors) will soon move to Beta, so we’ve streamlined the Jetpack XR APIs. We've removed legacy Guava and RxJava3 packages in favor of a modern, Kotlin-first architecture.

Jetpack SceneCore: glTF and Custom Meshes

We're expanding 3D model capabilities by adding the ability to fine tune 3D models and access specific nodes with a 3D model. Using GltfModelNode, you can modify properties like pose, materials, and textures, and even run animations for specific nodes.

// Create a new PBR material
pbrMaterial = KhronosPbrMaterial.create(
    session = xrSession,
    alphaMode = AlphaMode.OPAQUE
)

// Load a texture.
val texture = Texture.create(
    session = xrSession,
    path = Path("textures/texture_name.png")
)

// Apply the texture and configure occlusion
pbrMaterial.setOcclusionTexture(
    texture = texture,
    strength = 0.5f
)

// Access the hierarchy of nodes
val entityNodes = entity.nodes

// Find the specific node
val myEntityNode = entityNodes.find { it.name == "node_name" }

// Apply the PBR material override
myEntityNode?.setMaterialOverride(
   material = newMaterial
)

We're also bringing Custom Meshes to SceneCore. Custom meshes let you build geometry on the fly programmatically, which is ideal for creating custom 3D models. This feature will launch as experimental, so try it out and let us know what you think!

// Create the meshval roadMesh =
    CustomMesh.BuilderFromMeshData(session, roadVertexLayout)
        .addVertexData(ByteBufferRegion(roadDataBuffer, 0, vertexDataSize))
        .setIndexData(ByteBufferRegion(roadDataBuffer, vertexDataSize, indexDataSize))
        .setTopology(MeshSubsetTopology.TRIANGLES)
        .build()

// Define the material
val roadMaterial = KhronosPbrMaterial.create(session, AlphaMode.OPAQUE)

// Instantiate the entity using the custom mesh and material
val roadEntity =
    MeshEntity.create(
        session,
        roadMesh,
        listOf(roadMaterial),
        pose = roadPose,)

Compose for XR: Native glTF Support

We now have native glTF support directly in Compose for XR with SpatialGltfModel. Use this along with SpatialGltfModelState to access nodes and animations in the glTF model, or use them to add textures and materials to your 3D models.

   val myGltfModelState = rememberSpatialGltfModelState(
        source = SpatialGltfModelSource.fromPath(
            Paths.get("models/my_animated_model.glb")
        )
    )

    val myGltfAnimation =
        myGltfModelState.animations.find { it.name == "animation_name" }

    DisposableEffect(myGltfAnimation) {
        myGltfAnimation?.loop()

        onDispose {
            myGltfAnimation?.stop()
        }
    }

    SpatialGltfModel(state = myGltfModelState, modifier = modifier)

ARCore for Jetpack XR: Geospatial API Preview for Wired XR Glasses

We’re also providing an early preview of the Geospatial API for wired XR Glasses in ARCore for Jetpack XR. This update enables high-precision anchoring of digital content tied to real-world locations in over 87 countries.

By combining ARCore’s Visual Positioning System (VPS) with the reasoning and audio capabilities of the Gemini Live API, you can create contextually aware experiences that understand both the location and position of your user. Imagine building an immersive, AI-guided walking tour that provides real-time audio descriptions of nearby places, seamlessly blending digital information with the physical environment.

Start Building the Future Today

It's an amazing time to develop for Android XR. With the Jetpack XR SDK moving to Beta soon and a robust set of new tools at your fingertips, explore each of the following areas to get your app's experiences ready for XR!

Read the documentation, explore the samples, and check out the XR experiments

Head to the official Android Developer site for full technical guides, API reference, and instructions on setting up the new emulator. Get inspired with our samples and experiments. See how we've used these APIs to build immersive spatial layouts, load 3D models, explore spatial audio, and more!

Check out what's new for game engines

We've added official support for Unreal Engine and Godot, and we've launched two new tools to accelerate development for Android XR with Unity and the Android XR Interaction Framework. And, based on your feedback, we are introducing the Android XR Engine Hub to allow you to run your experiences directly from your preferred engine,

Read the blog post about what's new for game engines

Apply for the Android XR Developer Catalyst Program

Don’t miss your chance to build for the latest Android XR hardware. Apply today for the opportunity to gain access to pre-release hardware, including our audio and display glasses prototype and XREAL’s Project Aura.

Learn more and apply today.

We look forward to seeing the amazing XR experiences you build as we move toward the launch of more Android XR devices later this year!

Explore this announcement and all Google I/O 2026 updates on io.google.

Android XR Updates for Unity, Unreal, and Godot

2026-05-19T03:30:00.000-07:00

Posted by Luke Hopkins, Android Developer Relations Engineer for OpenXR & Ryan Bartley, Android XR Product Manager

Today, we are excited to announce that official support for Unreal Engine and Godot has arrived for Android XR. Alongside these engine expansions, we are also launching new tools designed to boost your productivity and enable new XR capabilities: the Android XR Engine Hub and the Android XR Interaction Framework.

Android XR Engine Hub

The Android XR Engine Hub is currently available for Windows and is your mission control for development. It unifies your workflow across Unity, Unreal Engine, and Godot by serving as a high-speed bridge that streams device-created perception data straight from your device into the engine of your choice.

Real-Time Streaming via OpenXR

The Hub bridges the gap between desktop power and mobile sensor data. Instead of requiring a full build to see how your app reacts to the world, the Hub streams OpenXR extensions from the physical Android XR device directly to your Windows machine.

This means you can iterate on complex interactions in "Play Mode" while receiving live, high-fidelity data from the headset’s sensors. Without this streaming capability, testing even a minor change to eye-tracking or spatial mapping would require a full APK export and installation.

The Hub enables low-latency testing for the following streamed extensions:

Core & Interaction Support

XR_EXT_hand_tracking & hand_interaction: Streams 26-point hand meshes and joint data for immediate interaction testing.
XR_EXT_eye_gaze_interaction: Virtualizes eye-gaze data to test UI and foveated logic on your PC.
XR_EXT_palm_pose & XR_EXT_uuid: Real-time precision tracking and persistent object ID streaming.

Android XR Vendor Extensions

Eye & Face Tracking (XR_ANDROID): Stream expressive avatar data to your editor to refine social presence without building.
Passthrough & Trackables: Access live environmental understanding—like plane detection and hit testing—directly within the engine's viewport.

By virtualizing the device's hardware capabilities and streaming them over a low-latency desktop bridge, the Android XR Engine Hub allows for game engine developers to quickly iterate.

Download the Hub:
Get the Android XR Engine Hub for Windows
Learn more about Direct Preview

Expanding Game Engine Support

Through our commitments to OpenXR standards, we are ensuring that whether you are a veteran studio or an indie developer, you have best-in-class tools to help bring your creative vision to life.

Unreal Engine

Unreal Engine support is now available in developer preview, targeting version 5.6.1. This integration is built directly on using OpenXR with the support for AndroidXR vendor specific API using the Android XR vendor plugin for Unreal, you can access platform-specific extensions for advanced hand tracking, face tracking, and scene understanding (like plane detection and depth) whilst making use of Unreal blueprints or C++ support.

Get Started with Unreal:

Godot

In partnership with the Godot Foundation and W4 Games, we are bringing official Godot support to Android XR for Godot 4.6.2 and higher.

We are already seeing incredible momentum from W4 as they have ported experiences like MoAT and Expedition to Blobotopia that are already live on Google Play, proving that Godot is ready for production-grade spatial experiences today.

To unlock the full potential of the platform, use the Godot OpenXR Vendors plugin 5.1, which provides the necessary Android XR vendor extensions for features like scene meshing, dynamic resolution, light estimation and much more. We're collaborating with Godot to optimize the OpenXR implementation for the Android XR power profile and input standards.

Get Started with Godot:

Unity

The Unity OpenXR: Android XR 1.13 package is now available for Unity 6.5 Beta. Unity has expanded Application SpaceWarp support to include both uGUI and TextMeshPro. Keep an eye out for the general release of Unity 6.5 and more platform enhancements arriving this summer.

Android XR Extensions v1.3.1 for Unity

Everything else you need for comprehensive platform integration is available in our latest Android XR Extensions release:

Spatial API Support: You can now manage the android.software.xr.api.SPATIAL manifest tag directly through XRSessionFeature settings, making it easier than ever to define your app's Spatial API requirements and target levels.
Fine Eye Face Tracking: A new Fine Eye Poses feature provides high-precision eye poses using the TryGetFineEyePoses extension method.
Direct Preview Support: The Android XR Streaming feature enables Direct Preview support within Unity Editor's PlayMode (Windows only).

Note: Android XR (Extensions): Hand Mesh has been removed; you should now use the unified Hand Mesh Data within the extensions package.

Android XR Interaction Framework for Unity

The Android XR Interaction Framework (AXRIF) is now available in developer preview. AXRIF is an unstyled, opinionated input toolkit that abstracts the complex logic required to build interfaces that are consistent with Android XR system interactions.

Instead of focusing on UI visuals, AXRIF prioritizes the underlying mechanics of the Android XR user experience. At its core is the same Transition Manager that powers the system's rich multimodal inputs, enabling state switching between 6DoF controllers, 3D mouse, hand tracking, and eye gaze. By leveraging this framework, developers can significantly reduce the implementation burden required to bring Android XR's full complement of robust interactions to their apps.

At launch, the framework provides three core capabilities:

Automated Multimodal Input Transitions: The framework manages the state machine for switching between input modalities. For example, it handles the transition logic when a user moves from gaze-targeting an object to directly touching it, simplifying simultaneous support for hands, controllers, and mice.
Gaze-Assisted Gesture Interaction: AXRIF combines gaze vector targeting with hand gesture recognition (such as pinch-to-select) for precise distant interaction, matching the system's default behavior.
Physics-Based 2D UI Interaction: The framework maps high-fidelity hand tracking to 2D plane interactions, enabling intuitive poke and swipe gestures on floating panels while respecting physical boundary constraints.

By adopting AXRIF, your app inherits the platform's native interaction model, ensuring your app feels consistent with the rest of the OS.

Explore the Toolkit:
Interaction Framework Documentation
Download the Unity Package

Get Started Today:

There has never been a better time to dive into Android XR development. With support across Unity, Unreal, and Godot, the platform is ready for your creative vision, no matter which engine you call home. Explore our official engine partners to get started:

Explore this announcement and all Google I/O 2026 updates on io.google.

Introducing Android Performance Analyzer : The Next Evolution in Profiling for Android

2026-05-19T03:00:00.000-07:00

By Simon Cooke, Developer Relations Engineer (X) and Mayank Jain, Product Manager (X)

What is Android Performance Analyzer?

Android Performance Analyzer (APA) is Android’s new profiler and performance analysis tool for the Android mobile ecosystem.

APA is intended as a profiling tool for any developer building for Android who needs to make their app or game run better and faster. It is helpful for all performance-minded engineers, especially those using Vulkan in their game engines who want to squeeze every bit of performance out of their code.

APA aims to be the tool that helps you optimize apps and games for all modern Android devices and simplifies your most common workflows, with a simple interface that anyone on your team can quickly learn and be productive.

Available today in open beta is APA’s new System Profiler that you can use to analyze the CPU, GPU, Memory, and power usage of your app or game - and see how it interacts with system behavior.

Developed in collaboration with Samsung Austin Research Center (SARC) and LunarG, APA relies on Perfetto for system tracing and its upcoming frame profiling/debugging features (stay tuned!) are powered by LunarG’s GFXReconstruct technology for graphics capture and replay.

Devices running Android 12+ will provide the best experience for capturing system-wide performance and GPU counters and render stages.

We’re also working across the Android ecosystem with our esteemed industry partners to bring more profiling & optimization related data into APA.

Android Performance Analyzer

How to get Android Performance Analyzer

APA ships in two different forms, and you can download whichever one suits your needs best

As a lightweight standalone desktop app.
And also integrated directly into Android Studio as the updated System Trace viewer (available in Panda 4 canary builds and later).

The standalone desktop app is intended to be used without an Android Studio project or Gradle build - and provides deep customization of recording configuration, built-in Vulkan layers for graphics analysis, deep inspection of GPU counters and much more.

APA is also cross-platform: works natively on Windows, MacOS, and Linux.

Features in this release

Basic profiling functionality

Capturing your profile data

You don’t always want to take a capture immediately at application or game launch. APA allows you to choose, and capture traces from your device at launch or triggered manually. The user interface allows you to select which GPU counters and other data is captured in a trace - and if you have more complex needs, you can provide your own custom Perfetto configuration.

Deep-Dive System Analysis

With APA, you can analyze the entire system’s behavior in one view. For example, you can easily examine CPU cores - both their frequencies and the work scheduled on them or inspect processes & their thread activity.

For graphics-heavy apps, APA provides GPU performance counter data across hardware from Qualcomm, Arm, Imagination, and Samsung. You can even track battery and power consumption to see the impact of your code on power consumption.

To understand exactly where frames are spending time, SurfaceFlinger events provide deep visibility into the rendering and display composition pipeline, from initial code acquisition to final display. And with the new screenshots feature, you can visually scrub through to easily find the exact areas where you want to focus your attention.

You can open existing Perfetto traces, zoom through the timeline for precise detail, and use rulers to measure the duration of work and events. APA also lets you bookmark and annotate interesting findings, and you can pin critical tracks to the top of your screen to keep your focus exactly where it needs to be as you optimize.

Workflow features

Tabbed interface and split windows: You can open multiple traces in side-by-side tabs or split a single trace into two windows to compare different regions of the same trace simultaneously.

Tabbed interface showing two traces side-by-side.

Project-based workflow: APA uses a project model that allows you to keep track of multiple traces from the project sidebar. This is especially useful for gathering the results of A/B testing and longitudinal tests, and keeping all of your results together for comparison & quick access purposes.

The new project window helps you manage multiple traces.

Navigate visually using screenshots: APA lets you capture screenshots during a trace (without any noticeable performance overhead) to home in on areas where you saw something affect performance by scrubbing through the timeline. Or even just to get your bearings.

Scrubbing the timeline using screenshots for navigation (trace taken from NetMarble’s Seven Deadly Sins: Origin).

Persistent view customizations: When you pin or vertically resize tracks, we save those customizations so that they persist the next time you open the trace.

Analysis tools & new skills for AI agents

Vulkan debug trace markers for render passes: We support Vulkan debug annotations for render passes - which allow you to view Render Pass names you set from your codebase directly in the tracks and slices shown in APA.

This immensely helps you to make logical connections between the workloads you see in the profiler to where they are originating from in your codebase.

Vulkan Debug Markers allow you to keep track of what kind of work is being performed in your trace.

Use AI to build SQL queries for custom analysis work: APA supports trace analysis via SQL queries and ships with a new Perfetto SQL skill for use with your favorite AI agents. This makes it easier to build queries without needing to remember Perfetto SQL schemas or the SQL syntax.

AI helps you build SQL queries to perform custom analysis on traces.

Ask Gemini to analyze traces for you: We’ve also added another Perfetto Analysis skill to answer high-level questions for you - like “Why is my app startup slow?” - helping you to find starting points when analyzing complex traces, using your favorite AI agent to pinpoint the answers.

Agentic trace analysis in Android Performance Analyzer

FPS and Frame Duration times : You can review the FPS and Frame duration time at a glance in the tracks to correlate it with other activity happening in your trace.

FPS and Frame timing tracks in APA

Speed & robustness improvements

Speed and robustness improvements: Rendering a trace is now typically 6x to 26x faster than Android GPU Inspector, and APA is significantly more stable when working with large traces.

Case studies

We’ve worked with our early access partners to create detailed case studies showcasing how APA could be used to improve performance for Vulkan apps & games.

The Forge Interactive

The Forge used Android Performance Analyzer to identify the need to batch calls to vkCmdBindDescriptorSets, which reduced CPU setup costs by ~50%. This, in turn, slowed heat production on their device by 2-3x, leading to longer session times. They also used APA to identify opportunities to move font and UI rendering work over to the GPU, improving scalability.

You can read the full case study from The Forge here.

Note: This case study demonstrates how to use custom SQL queries in the profiler to generate a total rendering cost metric.

The Forge case study showing frames presented consistently at a stable 30 FPS using APA

NetMarble – Seven Deadly Sins: Origin

Netmarble used Android Performance Analyzer to fine-tune their game Seven Deadly Sins: Origin, focusing particularly on improving performance by making changes to the precision of their shaders, and exploring the impact of upscaling on the performance of their renderer.

This allowed them to reduce the GPU cost of rendering some scenes by up to 90%.

Read the full NetMarble case study here.

Netmarble validating pre- and post-optimization performance changes using APA for their game: Seven Deadly Sins: Origin

Profiling model complexity in Google’s Filament engine

Google has been improving the Filament glTF Viewer, our physically-based rendering engine.

We spent some time digging into the viewer with a variety of scenes, and showed how to use Android Performance Analyzer to identify scenes that are too complex for the GPU, and how to trim them down to hit a target 60FPS, by improving texture compression and optimizing geometry. Memory consumption was also reduced in this process.

You can read our exploration of Filament here.

Screenshot showing GPU wait time was reduced from 25ms to 20ms by introducing dynamic resolution and measuring it through APA

Try out the Android Performance Analyzer Beta today!

The Android Performance Analyzer is available for you to try out and use today:

Standalone profiler: https://developer.android.com/android-performance-analyzer
Android Studio Canary Build (Panda 4 canary builds and later): https://developer.android.com/studio/preview

This is beta software, which means that you might run into an occasional bug – please report it to us if you find any (Help Menu > Submit a bug report).

We’re excited to see how you use the new Android Performance Analyzer, and how it will help your project’s performance and reliability.

Explore this announcement and all Google I/O 2026 updates on io.google.

Android Studio I/O Edition: What’s new in Android Developer tools

2026-05-19T02:30:00.000-07:00

Posted by Matthew Warner, Google Product Manager

This year at Google I/O we are going beyond iterative changes, towards a fundamental shift in how apps are built. Our newest tools are built for the agentic era with features that boost productivity for you as an Android developer AND supercharge the AI agents you deploy in your codebase. So, whether you are building exclusively with AI or you prefer being the architect of every line of code, our tools will keep you ahead of the curve.

As we move from "AI-assisted" to "Agentic" development, we’re making it easier than ever to turn a spark of an idea into a high-quality production app with significantly less developer effort.

So what’s new with Android developer tools? We will cover 3 main areas in this blog:

Let your agent handle it: Whatever development task you are working on, the Android Studio agent can help: from planning the app architecture and design, to writing code, to unit testing and bug fixing.
Any AI provider, anywhere you build: In Android Studio, you can use any model and we even help guide you to the best performing ones. Choose any of the top remote models from Google, Anthropic, OpenAI, or if you need to run locally - Gemma 4 is our most capable and efficient local model! And with Android CLI, you can build Android apps faster and easier using the agents and developer environments of your choice.
As always, performance and quality remain top priorities: We continue to invest in the Android developer tools you love: from the Emulator, to Profilers, performance analyzers, and more!

1: Let your agent handle it

Agent skills

Android Studio now supports Agent Skills, modular instruction sets that ground LLMs in specialized workflows and domain-specific knowledge. By adding skills to your project, you can teach the agent to follow specific best practices, architecture patterns, or library workflows. This enables more accurate, context-aware code generation and automated skill activation for an appropriate task, ensuring the agent acts as an expert. We’ve bundled many of the top Android and Firebase agent skills in the latest Android Studio Canary build, so you can skip straight to building!

Skills in Agent Mode

You can create your own skill, or use Android CLI to install our official skills - a repository that covers some of the most common workflows that some Android developers and LLMs may struggle with. They help models better understand and execute specific patterns that follow our best practices and guidance on Android development, such as XML to Compose migration, Edge-to-edge, Navigation 3, and more. You can even build for Android XR, starting with a beautiful Display Glasses app with Jetpack Compose Glimmer. Official Android skills are automatically bundled with the latest Android Studio so the Agent is ready to build!

Build full-stack apps with Firebase in Agent Mode

Firebase services like Auth and Firestore databases can now be enabled directly within Agent Mode in Android Studio using the Agent Skills for Firebase. Your agent will be able to complete Firebase integration and configure backend services. This integration empowers you to build robust, full-stack Android applications without ever leaving your IDE!

Building a full-stack app with Firebase via Agent Mode

Parallel conversations

You can now run multiple conversations with Agent Mode in parallel. In one conversation, run tests and while you are waiting, you can kick off planning mode for a new feature in your app while using a third conversation thread to write documentation for your app. These improvements will save you time and improve your productivity.

Parallel conversations in Agent Mode

A more capable New Project Agent

Android Studio's New Project Agent has evolved into a powerful full-stack development tool, utilizing a multi-step execution plan and an autonomous "generation loop" that self-corrects build errors and configures dependencies across multiple files. This advanced capability is significantly amplified by its new integration with Firebase Agent Skills, allowing developers to seamlessly build, debug, and deploy complete full-stack applications directly from a single prompt to final production.

Building an app with New Project Agent

Additionally, it now offers support for large screens. You can scaffold your project with layouts, navigation, and components optimized for tablets, foldables, and laptop devices from the get-go. It has additional logic to test your app on large-screen emulators if you have one enabled. Simply configure the required device in the Android Emulator and the Agent can test it out!

Build large screen apps for foldables and tablet devices

2: Any AI provider, anywhere you build

Build Android apps in Google AI Studio

Google AI Studio now features full Android app development capabilities. Users can generate new applications, preview them instantly via an embedded Android Emulator, and deploy them directly to physical devices using ADB over USB. Additionally, developers can publish straight to Google Play; AI Studio handles the app record creation, bundles the package, and uploads it to an internal testing track. For advanced development and production readiness, projects can be exported as a ZIP file and opened seamlessly in Android Studio. To get started, visit Google AI Studio today and start building!

Google AI Studio build mode with Android framework

Android CLI helps you build faster, more efficiently with any agent

Android CLI enables you to build apps using any agent, LLM, and tool of your choice. Android CLI is designed to help AI agents build faster, and use less tokens when compared to only using generic LLM tools. By grounding agents with Android Knowledge Base and Android skills, you can now have your agent of choice follow the latest best practices across any coding environment.

Additionally, when using the latest Canary version of Android Studio Quail, Android CLI enables your agent to leverage powerful capabilities of the IDE, such as analyzing files for issues or finding symbol declarations. Google Antigravity 2.0 now offers official support for Android development with Android CLI.

Android CLI enables any agent with the tools and knowledge to build for Android.

Google AI plan

You can now use your Google AI Pro or Ultra plan to get access to dedicated capacity and higher rate limits for Gemini in Android Studio. This is especially helpful for long agentic Android development sessions, which can require using more tokens. Android Studio detects your subscription automatically when you log in with your Google account.

Use your Google AI plan in Agent Mode

Gemma 4 for local code assist and on-device AI

Gemma 4 is a state-of-the-art local model trained for Android development. It’s our most efficient local model and is capable of complex multi-step agentic coding in Android Studio. It’s ideal for developers who require data privacy, offline access, or have run into quota issues with other models.

And now in the latest Canary build, you can download and run Gemma 4 directly from the IDE, without needing to set up an external server.

Model selector in Agent Mode

Bring your own model to Android Studio

Android Studio allows developers to bring any model they choose into the IDE for agentic AI assistance. Power your workflow with models like Gemini, GPT, and Claude or use a local model like Gemma 4. This flexibility offers developers greater control over performance, privacy, and cost.

Settings, Model Provider

Android Bench highlights the top models

Earlier this year we launched Android Bench, the benchmark and leaderboard designed to evaluate how effectively LLMs handle real-world Android development tasks. The goal is to accelerate AI improvements, leading to more helpful models for you to use for AI assistance, which will lead to better quality apps for Android users.

You asked us to evaluate open models, so we added them to the leaderboard to help you see how LLMs with additional privacy and offline access measure up. We are also working on significantly increasing the difficulty of challenges we’re giving LLMs, to continue encouraging improvements. This includes creating long running tasks, which take a typical Android engineer multiple days to complete.

Latest results as of May 18th 2026, check here for updates

3: As always, performance and quality remain top priorities:

Test multi-device interactions with the Android Emulator

The Android Emulator now features a new networking stack that enables zero-configuration, peer-to-peer connectivity between multiple virtual devices on the same host machine. This update eliminates the need for manual port forwarding, allowing developers to easily test multi-device scenarios like local multiplayer gaming, file sharing, and companion app pairing. By creating a shared virtual network backplane, the Android Emulator provides a more stable and consistent environment for building complex, interconnected app experiences across different form factors.

Multi -device testing with the Android Emulator

Android Debug Bridge Wi-Fi 2.0

ADB Wi-Fi 2.0 offers significantly more reliable wireless debugging. With the latest ADB command line tool from Android Platform Tools v37 and an Android 17 device, you can now change networks, shut down your machine, and go about your typical day and your devices will stay connected. Additionally, devices with wireless debugging enabled will automatically show in Android Studio’s Device Manager, streaming the pairing process and making it easier than ever to connect Android phones, watches, and more.

Pair devices with Wi-Fi

Android Studio now lets you publish to Google Play for testing

Android Studio now gives you the ability to upload new releases of your app directly to Google Play Console test tracks. You can do this by selecting a new option to continue to “Publish for Testing” at the end of the Generate Signed App Bundle flow. This integration supports uploading an initial release of a brand-new app to Play Console’s internal test track. You can also use this feature to upload releases to existing apps to test tracks. You need to be registered on Google Play Console to take advantage of this functionality. Read the ‘What’s new in Google Play’ blog to learn about all the updates from Play at I/O.

Upload App Bundle to Google Play

Android developer verification support

You can now see your app's registration status right in Android Studio when you generate a signed App Bundle or APK. Seeing this information in Android Studio enables you to address registration issues early and ensure your apps are ready before the verification requirement goes into effect for certified Android devices starting in September 2026.

App registration status with Android developer verification

Memory leak detection with LeakCanary

Memory leaks in Android occur when your code holds onto an object's reference long after its life cycle has ended. This prevents the Garbage Collector (GC) from reclaiming that memory, eventually leading to sluggish performance or OutOfMemoryError (OOM).

The Android Studio LeakCanary profiler task significantly enhances developer productivity by enabling the analysis and inspection of memory leak traces directly on the desktop development environment rather than on the mobile device. Furthermore, Android Studio streamlines troubleshooting by providing tools like “Go to declaration” to map the leak analysis directly to the codebase, allowing developers to quickly locate and resolve memory leaks.

Starting from the Android Studio Quail 1 release, you can now also request Gemini to review the memory leak for you using the “Fix with Agent” button.

Review memory leaks identified via LeakCanary through the “Fix with Agent” button

Android Performance Analyzer (APA)

Android Performance Analyzer (APA) is the next generation of performance profiler for Android and provides a cohesive analysis of CPU, GPU, memory, and power usage for your apps and games running on Android 12+ devices. APA is engineered for reliability and performance with trace rendering speeds which are up to 26x faster from previous tooling.

Android Performance Analyzer (APA) running in Android Studio showing two traces side by side

APA integrates natively with AI agents and offers two new skills: Perfetto SQL skill and the Perfetto Analysis skill, which helps with questions like "Why is my app startup slow?"

Analysis of traces using Perfetto Analysis skill

R8 Configuration Analyzer

R8 is one of the best ways to improve your app’s performance and reduce memory footprint. The performance benefits you can get from R8 are directly correlated to how much of your codebase R8 is able to optimize. We’ve introduced a new tool to help you to unlock the maximum optimization from R8 – the R8 Configuration Analyzer. It provides insights into R8 configuration quality and how your keep rules impact your app. We have also introduced three scores that show how much of your codebase is available for optimization, obfuscation, and shrinking.

Suggested fixes for crashes with Agent integration in AQI

The App Quality Insights tool window is now integrated with the AI agent to analyze crash data along with your source code to provide detailed explanations and suggest potential fixes. After selecting a crash in the App Quality Insights tool window, navigate to the Insights tab and click “See more” to see a detailed explanation of the crash. Click “Fix with AI” to have the agent suggest code changes that you can review and accept.

App Quality Insights and Fix with AI

Get started

Android Studio is closing the gap between ideation and implementation. With powerful tools built for agentic development, it’s never been easier to build and ship high-quality Android apps.

Download the latest Android Studio Quail preview build and try these new features. As always, your feedback is crucial to us. Check known issues, report bugs, and be part of our vibrant community on LinkedIn, YouTube, or X. Happy coding!

Explore this announcement and all Google I/O 2026 updates on io.google.

Android UI Development is Compose First

2026-05-19T02:00:00.000-07:00

Posted by Nick Butcher, Product Manager

In the almost-5-years since Jetpack Compose launched, we've invested in bringing you all the features, performance and tools that you need to build amazing UIs across the variety of Android devices. Compose helps you to build beautiful, adaptive UIs that meet the demands of modern UI design.

Rich feature set: With a powerful library of layouts, input, graphics, animation APIs, and the latest Material Design components, Compose empowers you to build anything.
Highly performant: Out of the box, Compose offers native performance, delivering a delightful experience to your users.
Adaptive: Compose offers the easiest way to build adaptive apps that work across the range of Android form factors.
Productive: With powerful tools like Previews and Live Edit and the full expressiveness of Kotlin, teams tell us that they move much faster when building with Jetpack Compose, reducing the time to market.

Compose has matured into the standard for Android UI development—we believe that all Android UI should be built with Compose; we call this going Compose First. From today, we'll provide all APIs, libraries, tools and guidance in Compose. We now consider the View components that Compose replaces (components in the android.widget package) to be in maintenance mode. We have no plans to deprecate or remove View components and will continue to support them with critical bug fixes, but they will receive no new features.

View-based Jetpack Libraries
The same goes for View based libraries like Fragments, RecyclerView or Viewpager — we consider them complete and will only publish critical bugfixes. For a complete list of libraries now in maintenance mode, see here.

Tools
Any new Android Studio UI tools will be built for Jetpack Compose only. Existing view-based tools (such as the Navigation Editor and Layout Editor) are now in maintenance mode and will not receive new features.

Guidance
Documentation, codelabs, and samples will focus on building UI with Jetpack Compose. You can still find Views-specific documentation linked from pages that contain generic and Compose information, where relevant.

Happy Composing

We recommend that you build all new features with Compose and convert existing features when you touch them to gain the many Compose benefits. Check out our XML to Compose migration skill to help you convert existing layouts to Compose.

To learn about the latest Compose release, check out What’s new in the Jetpack Compose April ‘26 release blog and the roadmap for what’s planned ahead.

Thank you for all of the feature-requests and feedback that have helped shape Compose to become our recommended UI toolkit. As always, if you have any more feedback, let us know. Happy composing!

Explore this announcement and all Google I/O 2026 updates on io.google.

What's new in Android for Cars: Unifying platforms and unlocking premium experiences

2026-05-19T01:30:00.000-07:00

Posted by Jan Kleinert, Developer Relations Engineer, Android for Cars, Noam Gefen, Senior Product Manager, and Thomas Weathers, Developer Relations Engineer, Android for Cars

We're thrilled to see developers continuing to bring their apps and experiences to Android for Cars! Over the past year, we've continued to see strong growth and momentum in the app ecosystem on Android Auto and cars with Google built-in. This year at Google I/O, we're introducing updates that benefit both drivers and developers by enabling richer, more differentiated in-car experiences. With new features and templates that allow you to build once to reach users across different infotainment screens and car platforms, it's easier than ever to build for the road.

What's new in the Car App Library

We're bringing more flexibility, new components, and new template capabilities to the Car App Library. Car App Library 1.8.0-beta01 and Car App Library 1.9.0-alpha01 are now available.

Build templated media apps for both Android Auto and Android Automotive OS

Developers can now build customized, distraction-optimized, media browsing and playback experiences for Android Automotive OS, making it easier to build once and deliver these templated media apps to more users and more cars.

To help you test the experiences on Android Automotive OS, we'll be launching updated system images for the Android Automotive OS emulator. Beginning with revision 3, the API level 35-ext15 system images will support apps built using the Car App Library media templates.

Unlocking developer creativity with Car App Library 1.9.0 alpha

With the 1.9.0-alpha01 release of the Car App Library, we're bringing features to help you build more differentiated, expressive experiences across Android Auto and cars with Google built-in.

We're increasing the modularity of existing templates to give developers more flexibility and options for laying out content. These improvements include expanded headers for better visual emphasis, such as on detail pages, spotlight sections that can be placed in scrollable areas to highlight specific content, and grid item variations to support different content types and states.

We're introducing new components and template capabilities to help developers build even more engaging experiences. For media apps, we're introducing an adaptive mini-player, so users can browse while still easily managing playback. Finally, we're adding more component types including Chip and CondensedItem to increase the ways that content can be displayed and interacted with.

App developers, including those shown below, have already begun building upgraded media experiences using these new Car App Library features. You can join these developers and prepare to distribute your own media apps built with the Car App Library templates by applying to participate in our early-access beta program.

Amazon Music, Gaana, PocketFM, Spotify, TuneIn, YouTube Music

Distribute your adaptive video apps to more cars with minimal effort

You’ve already built the apps, now we’re helping you reach more users. For the first time in Android Auto, users will be able to sit back, relax, and watch videos while parked. Apps, like YouTube, will be able to deliver smooth, 60fps HD video playback. This brings the Android Auto parked experience in line with the high-fidelity, immersive experiences users already enjoy in cars with Google built-in.

This capability will start rolling out to compatible vehicles later this year, for users with phones running Android 17 and higher. If your video app is already adaptive, making it available for parked use cases in cars requires minimal effort. To express interest in making your video app available on Android Auto, fill out this form.

Widgets are coming to cars

The next generation of Android Auto brings a more expansive user interface and the Material 3 Expressive design system you know from the phone into the car, built to seamlessly fill larger screens no matter what shape they are. With this new design, the investments you've already made in mobile widgets will be available to users of Android Auto this year, and cars with Google built-in later on, opening up new ways to reach and engage with your users while they're on the road. We're excited to unlock these new glanceable user journeys!

The road ahead

You can look forward to even more updates coming to cars later this year.

To deliver a more continuous user experience, we're making it possible for you to provide a templated experience while driving that can seamlessly transition to a native, adaptive app experience when the vehicle is parked.
New components and conversational templates will be coming to the Car App Library, so you can integrate agentic and voice-based flows more seamlessly in apps.
Improved app brand expression across all car surfaces allow experiences built with the Car App Library to feel easily recognizable by your users.
Google Maps SDK support is coming to cars with Google built-in. With this change, you'll be able to use the Google Maps SDK to render map-based content with the MapWithContentTemplate in point-of-interest (POI) and Weather apps on both Android Auto and cars with Google built-in.

Stay updated on these features and start building with the latest at goo.gle/cars-whats-new.

Explore this announcement and all Google I/O 2026 updates on io.google.

I/O 2026: What's new in Google Play

2026-05-19T01:15:00.000-07:00

Posted by Paul Feng, VP, Google Play Eng, Product, UX

At Google Play, we’re passionate about helping people connect with the experiences they’ll love, while empowering developers like you to turn great ideas into lasting business success.

At this year’s Google I/O, we talked about our evolving business model that offers more choice and new ways for your apps and content to be discovered on and off the store. We also unveiled advanced tools and insights that will help scale your business with less complexity. Watch the keynote video below, or keep reading for the biggest updates from this year’s event.

Expanding your reach by meeting users where they are

Your apps and the incredible worlds you build are no longer just a single destination, but connected experiences that reach users across surfaces and devices. To help you meet users where they are, Google Play continues to evolve into a content-forward destination that delivers immersive and personalized experiences on the store, across their devices, and directly within your apps and games.

Beyond the store: Expanding discovery to new surfaces & devices

We're unlocking new opportunities for your apps and content to be discovered across the wider Android ecosystem.

Surfacing your apps and content in Gemini: As people increasingly start their journeys with virtual assistants, we want to ensure your apps and their content are an essential part of this. In the coming weeks, we're enabling app discovery in the Gemini app on Android and Web, connecting your apps and games to millions of Gemini users. Later this year, Gemini will also surface over 450,000 movies and TV shows, as well as where to stream live sports, and deep-link users directly into your app content.

Gemini will provide users with app suggestions and direct access
to entertainment content during a search.

Delivering personalized content across the ecosystem: Engage SDK surfaces deliver your content to over 30 million monthly active users and drive millions of app opens every month—a massive 45% increase year-over-year. And we’re making it even more powerful by expanding support for new surfaces and devices.
- Store listing integration: Starting next month, existing users will see Engage SDK content directly on your store listings.
- New tablet surfaces: We’re broadening reach across Android tablet surfaces, including home screen Collections.
- Global scale: Every Engage SDK surface can now scale your content across over 80 Play markets.

Boost re-engagement by integrating with Engage SDK today. If your app is already integrated, no further action is required to benefit from these updates.

On the store: Enhancing content formats and conversational search

We’re also optimizing the Play Store to help grow your audience with engaging content formats and a more intelligent search experience, to make it easier than ever for users to find and connect with your app.

Capturing attention with Play Shorts: Our full-screen, portrait, short-form video feed gives users a glimpse of your app’s look, feel, and functionality. Play Shorts is rolling out to users in the US and select developers, and we look forward to expanding this to more markets and developers in the coming months.

Play Shorts provides a glimpse into your app’s look, feel & functionality.

Enabling deeper search journeys with Ask Play: Building on AI-powered Q&A, which already answers 95% of user queries, we’re introducing Ask Play. This AI-powered overlay turns discovery into a natural conversation, understanding the full context of a user's question and adapting to follow-ups to recommend the right app. Plus, with Ask Play highlights, users can get a high-level summary of complex searches directly on the search results page to help find the right apps or games more effortlessly.

Ask Play understands the full context and helps users find the right apps or games.

In your games: Deepening player engagement and community

Once players launch your title, the real challenge is keeping them in the action. Play Games Sidekick provides an in-game overlay that gives players instant access to gaming information—like AI-generated Game Tips, rewards, and achievements — driving higher engagement while keeping players immersed. Sidekick has already debuted in over 100+ titles, and we’re building on this momentum with:

New social features: Starting next month, players can see which friends are playing the same game and track their achievements
Global expansion: Sidekick expands to all participating titles this summer. Head over to Play Console to enable Sidekick and begin testing the user experience so that you're ready for our global launch, while also meeting one of our core Level Up program guidelines.

Scaling your business with less complexity

We’re streamlining your day-to-day tasks while providing more comprehensive reporting to help you capture more growth opportunities.

Streamline your Play Store operations with AI

We’re using Gemini models to handle the heavy lifting of localizing your store content and managing your catalog.

Localize with less effort: Eliminate manual copy-pasting by uploading a structured file (like a CSV or Google Sheet). Gemini models enable Play Console to pre-populate your listings across different languages for your review. You can also leverage AI-translated subscription benefits to quickly scale your localization efforts.

Instantly pre-populate store listings with localized translations.

Convert search trends into growth: We’ve simplified the path from insight to action. When you click a keyword recommendation on your Grow overview page, Gemini creates a new custom store listing automatically tailored to that keyword—ready to deploy with just one click.
Simplify catalog management: We’re introducing agentic catalog management to help you manage your one-time products. Soon, you can leverage new in-console capabilities to execute bulk price changes, import SKUs, and configure metadata, saving hours of manual work.

New agentic capabilities in Play Console will make managing your catalog seamless.

For a detailed look at these features and more, watch this video.

Behind-the-scenes features that optimize your revenue

We’re building tools to maximize your revenue at every stage—with zero developer work required. When a user decides to buy, our platform helps ensure that the transaction completes at the point of conversion, renewal, and retention.

Optimizing conversion with delayed charging: When a payment initially fails, our risk models evaluate the transaction. If it’s low-risk, we grant the user access to your paid content while we retry the charge in the background. This means your lowest-risk subscribers get the best experience and you are less likely to lose them due to a temporary glitch.
Boosting renewals with extended recovery periods: To prevent involuntary churn, we’ve extended the default account recovery period from 30 to 60 days to give subscribers more time to fix failed payments, like expired credit cards. This shift has driven up to an 18% reduction in involuntary churn and a 9% reduction in total churn for top developers.
Maximizing retention with flexible flows: A rigid experience makes retention nearly impossible. Coming soon, our new in-app subscription management API lets subscribers change plans or accept a downgrade offer the moment they hit “cancel.” Combined with replacement modes that automate prorated refunds, you’ll have a powerful toolkit to save at-risk subscribers.

Flexible flows let subscribers change plans or accept downgrades to boost retention.

More reporting and AI-powered insights

We’re providing more data and more AI-powered insights to help you understand your performance and ROI on Play.

Measure your full marketing impact: See your app’s total visibility on Play with our new reach metric. Gain better insight into store listing performance with indirect value not previously reported. Analyze downstream impact—like engagement, retention, and monetization—with our new traffic source breakdowns.
Optimize the path to purchase and retention: We’ve added cart conversion rates to your core performance metrics to help you identify and fix friction in your checkout flow. New data on subscriber tenure and churn reasons allow you to better pinpoint why subscribers leave and which segments are most at risk.
Get faster answers: Using Gemini models, we’re expanding chart descriptions from the Statistics page to the Reach & Devices and Store Performance pages to help you spot trends instantly. With new interactive Q&A and proactive monetization insights, you can ask why a metric shifted and instantly receive tailored recommendations to optimize your business.

Get instant answers and recommendations for optimizing your business.

Protecting your success

In addition to making it easier and faster to publish safer apps, we’re also making it easier to secure your app’s revenue and reputation.

Defend your business against fraud and abuse: The new Protected with Play dashboard helps you monitor and configure your integrity, distribution, and monetization defenses all in one place. We’re also reducing warm-up latency for Play Integrity API, so you can use these checks during speed-critical user journeys to block threats and risky devices faster.

The Protected with Play dashboard provides centralized insights to help you safeguard your app.

Get proactive protection for your store and revenue: We work behind the scenes to help stop malicious activity before it impacts your business. Last year, our automated anti-spam protections blocked 160 million spam ratings and reviews while our anti-fraud efforts automatically protected apps using Play Billing from 3.2 billion dollars in fraud and abuse.

Growing your business on Google Play

Our latest updates reinforce our commitment to deliver the highest return on your team’s investment, by expanding your reach beyond the store, simplifying your day-to-day operations, and helping you better safeguard your success. We’re excited to see you use these new capabilities to create even more impactful experiences. Thank you for being a part of the Google Play community.

Learn more about these announcements and all other Google I/O 2026 updates on io.google starting May 21.

What's New in Wear OS 7

2026-05-19T01:00:00.000-07:00

Posted by John Zoeller, Developer Relations Engineer

Today, we are excited to introduce Wear OS 7, a major update that brings a new era of power efficiency and intelligence to users and developers alike.

We recognize that watches are essential, all-day companions to your users. That’s why we're continuing to invest in power optimizations so your users can do more with their favorite apps. For watches upgrading from Wear OS 6 to Wear OS 7, average users can expect up to 10% improvement in battery life.

As part of a broader rollout to the Android ecosystem, select watches arriving later this year will come with Gemini Intelligence, providing proactive and personalized help to our users so they can focus on what matters.

With Wear OS 7, we’re introducing new system capabilities and enhanced developer tools. New user-facing features like Live Updates, and enhanced media controls deliver a smarter, more intuitive personalized experience on the wrist. And with enhancements to our developer toolkit such as Wear Compose 1.6 and AppFunctions, developers will be able to streamline their apps for efficient, intuitive experiences on the wrist.

Let's dive right in!

Wear OS 7 Canary

You can now try out the next version of Google’s smartwatch platform, Wear OS 7 Canary Emulator, based on Android 17 that's arriving later this year.

The new emulator allows you to get hands-on with the developer features and tools mentioned above while testing your app for compatibility with the upcoming platform.

Check out what’s changed and start testing your app today.

Explore new Wear OS features

Wear OS Widgets

Full-screen Tiles have been a go-to surface on Wear OS, providing users with instant, glanceable access to their essential updates. As the Android ecosystem moves further toward a unified vision for widgets, we’re bringing the watch closer to the rest of the Android family with the goal of minimizing efforts for developers.

Today, we’re excited to introduce the next step in the evolution of Tiles: flexible and dynamic Wear Widgets.

Powered by Jetpack Glance and the new RemoteCompose framework, Wear Widgets offer greater expressiveness and consistency with Compose than the Tiles ProtoLayout libraries. Wear Widgets support two new card layouts—small and large, that align perfectly with the 2x1 and 2x2 formats on mobile, ensuring your designs feel cohesive across devices, while still allowing you to optimize your designs for the wrist.

It’s easy to adapt the UI from the mainSlot of your full-screen tile to a 2x2 Widget. Take a look!

Check out the Widgets I/O Talk later this week for full details on the new features, and try out our Widgets Getting Started Guide to add a Widget to your Wear OS experience.

Live Updates

Wear OS 7 brings Live Updates to watches!

You can use Live Updates to surface real-time, important information from your watch or mobile app, providing your users with timely updates at a glance.

In your watch app, use Live Updates instead of the Ongoing Activities API to provide local update publishing on all Wear 7 devices. For supporting OEMs, Live Updates published by your phone app will also be bridged to users' watches.

Check out how Just Eat provides updates to their users, above!

For more information, check out Notifications on Wear OS.

Connect your app to the intelligence system

We're working on several ways for developers to provide agentic experiences on the watch, from AppFunctions to task automation tools.

We’ll announce these on our developer blog when they’re ready, and provide an all-encompassing developer guide to help you choose the right one and craft a robust implementation. For now, here's a quick look.

AppFunctions

The AppFunctions API allows developers to integrate their apps with agents and assistants, like Google Gemini, enabling users to complete tasks using voice, often replacing the need for step-by-step, manual navigation with your UI.

For example, to start a run with the Samsung Health app, users are able to tell Gemini: “Start tracking my run.”

We’re currently running an Early Access Program for any developers who are interested. Sign up in our form to express your interest.

Task automation

Also coming soon, without any development effort at all, users will be able to invoke and track automated app tasks, for selected phone apps, directly from their watch, like placing an order with DoorDash!

Keep an eye out for these flexible options on how to prepare and connect your app to the Android intelligence system on our developer blog.

Wear Workout Tracker

We know that building a full-featured, high-quality fitness tracking experience on Wear OS from scratch is resource-intensive, so we built the all new Wear Workout Tracker experience for exercise apps. It will be included in Wear OS later in the year.

The workout tracker provides a rich standardized workout tracking experience which includes heart rate monitoring, media control, and a collection of other useful features to help you reduce development investment while guaranteeing a high-quality experience for your users.

We’ve been working closely with ASICS Runkeeper to bring it to their users, check it out!

Enhanced System Media Controls in Wear OS 7

Wear OS 7 enhances the System Media Controls, giving users more control and seamless experiences for their media.

Per-App media auto-launch controls

Users can now personalize their media auto-launch experience per-app directly from the System Media Controls on the watch.

For any app where the user has ‘Auto-launch Settings’ toggled on, media controls will automatically appear on the watch when media is started on the phone.

Developers with an existing implementation of media apps that extend on the watch can benefit from this feature without additional effort.

Seamless audio routing with the Remote Output Switcher

Managing audio output is now easier than ever with the new Remote Output Switcher integrated into the System Media Controls.

When listening to media on a paired phone, users can effortlessly switch the device the media is played back on directly from their wrist.

UI Library updates

To go along with all these new features for users, we’re introducing some powerful enhancements to our developer toolkits to help developers prepare for the future of Wear OS!

Compose for Wear OS 1.6

As the foundation for Wear OS development, Compose for Wear OS 1.6 has arrived.

It includes powerful updates including:

Streamlined navigation with Navigation 3

Developers can Integrate with Navigation 3 to provide a more flexible and Compose-idiomatic way to handle navigation on Wear OS.

@Composable
fun WearApp() {
    val backStack = rememberNavBackStack(MenuScreen)
    WearAppTheme {
        AppScaffold {
            val entryProvider = remember {
                entryProvider<NavKey> {
                    entry<MenuScreen> { GreetingScreen() }
                    entry<ListNavScreen> { ListScreen() }
                }
            }
            val swipeDismissableSceneStrategy = rememberSwipeDismissableSceneStrategy<NavKey>()
            NavDisplay(
                backStack = backStack,
                entryProvider = entryProvider,
                sceneStrategies = listOf(swipeDismissableSceneStrategy)
            )
        }
    }
}

List management improvements for TransformingLazyColumn

Significant improvements are here for advanced list management with TransformingLazyColumn, including enhanced padding support via the new minimumVerticalContentPadding modifier, and other new features like snapping and reverse layout.

val listState = rememberTransformingLazyColumnState()
val transformationSpec = rememberTransformationSpec()

/*
 * TransformingLazyColumn takes care of the horizontal and vertical
 * padding for the list and handles scrolling.
 */
ScreenScaffold(scrollState = listState) { contentPadding ->
    TransformingLazyColumn(
        state = listState,
        contentPadding = contentPadding
    ) {
        item {
            ListHeader(
                modifier = Modifier
                    .fillMaxWidth()
                    .transformedHeight(this, transformationSpec)
                    .minimumVerticalContentPadding(
                        ListHeaderDefaults.minimumTopListContentPadding
                    ),
                    transformation = SurfaceTransformation(transformationSpec)
            ) { Text(text = "Header") }
        }
    }
}

Optimize ambient experiences with LocalAmbientModeManager

The all new LocalAmbientModeManager is optimized for handling ambient flows, giving developers greater control over how their ambient experiences are presented to users.

override fun onCreate(savedInstanceState: Bundle?) {
    setContent {
        val ambientModeManager = rememberAmbientModeManager()
        CompositionLocalProvider(LocalAmbientModeManager provides ambientModeManager) {
            val localAmbientModeManager = LocalAmbientModeManager.current
            val ambientMode = localAmbientModeManager?.currentAmbientMode

            Column(
                verticalArrangement = Arrangement.Center,
                horizontalAlignment = Alignment.CenterHorizontally,
                modifier = Modifier.fillMaxSize(),
            ) {
                val ambientModeName =
                    when (ambientMode) {
                        is AmbientMode.Interactive -> "Interactive"
                        is AmbientMode.Ambient -> "Ambient"
                        else -> "Unknown"
                    }

                val color = if (ambientMode is AmbientMode.Ambient) Color.Gray
                    else Color.Yellow
                Text(text = "$ambientModeName Mode", color = color)
            }
        }
    }
}

Protolayout & Tiles updates

While we encourage developers to adopt the new Wear Widgets, we will continue to support our Protolayout and Tiles libraries for some time, and we’ve got new stable versions of both.

Protolayout 1.4 and Tiles 1.6 work together to provide several notable new features including:

Inlined Image Resources: ImageResource can now be directly inlined within a layout, and Tiles now support automatic resource collection through ProtoLayoutScope,removing the need for manual resource mapping and splitting into separate methods. In addition to better code quality, this improves Tiles loading latency via consolidation into a single binder call from system to the provider service.
Material3TileService: Tiles can be implemented as a Material3TileService – an all-encompassing suspend function which returns both tile layout and resources, while automatically managing the MaterialScope and ProtoLayoutScope to simplify the development experience.
Dynamic Service Switching: On Wear 7, multiple TileService instances can now be grouped in the manifest to enable dynamic switching between different services that represent the same tile.

Check out the new Tiles sample here.

WFF 5

Watch Face Format version 5 (WFF5) is now available with a host of new features to make it easier to build watch faces, including:

Enhanced Alignment Options: Text elements like TextCircular have additional alignment options, including verticalAlign on the same baseline for multiple text elements.
Auto-Size Enhancements: isAutoSize can now be used on TextCircular,and a new attribute, minSize, has been added to the Font element to limit the minimum size when autosizing is enabled.
Blend Modes: Group and ComplicationSlot elements now support blend mode, in addition to existing support on Part* elements.
Stroke Joins: Stroke and WeightedStroke elements now include a join attribute.
Hierarchical settings: User Styles can now be structured as a hierarchy, where some settings are visible only when other settings have specific values. User Styles can now enable or disable complication slots as well. These can be configured using the childSettingIds and complicationSlotIds on User Style Options.

Check out our new developer guidance to learn more about WFF 5.

Start building for Wear OS 7 now

With these updates, there’s never been a better time to develop an app on Wear OS. These technical resources are a great place to learn more about how to get started:

We’re looking forward to seeing the experiences that you build on Wear OS!

Explore this announcement and all Google I/O 2026 updates on io.google.

How FotMob leveraged cross-device discovery to score record Wear OS adoption

2026-05-15T09:00:00.000-07:00

Posted by Garan Jenkin, Wear OS Developer Relations Engineer

FotMob recently experienced its largest single-day increase on Wear OS among its installed audience in 5 years, at 2-3x the daily average. The secret? A simple cross-device installation flow that helps users discover their Wear OS app directly from their phone.

FotMob is one of the world’s most popular football (some call it soccer!) platforms, known for its mobile app that provides real-time scores, statistical analysis, and news.

FotMob is available on mobile and Wear OS

In addition to the mobile app, FotMob is available on Wear OS, allowing users to keep on top of the latest scores and results directly from their wrist.

“Many FotMob users follow matches live, and that often happens when they’re not actively using their phone,” says Roy Solberg, Android Tech Lead at FotMob. “Wear OS gives fans a quick way to glance at scores, match events, and updates directly from their wrist, so we saw it as a natural extension of the FotMob experience.”

By providing a smooth experience across different form factors, FotMob ensures that their users can continue to get the most from their platform, in the most convenient form. This includes ensuring that settings and preferences–such as favorite teams–are synced across devices.

The Discovery Gap

Despite many FotMob users having a Wear OS device, FotMob realized that some users might not be aware of the Wear OS app. This led the team to consider technical options for how to educate users about and ultimately install the Wear OS app directly from within the core phone app.

Fortunately, the Wearable library on Android and Wear OS provides exactly the building blocks that FotMob needed to create an in-app experience that would allow their users to do just that.

Detecting Eligible Wear OS Devices

Within the FotMob phone app, the team used the NodeClient to identify connected Wear OS devices - candidates for the Wear OS app:

val connectedNodes = nodeClient.connectedNodes.await()

Additionally, the team defined a capability within the Wear OS app, indicating that FotMob was installed on the device. This is defined as an XML resource in the Wear OS package, and then queried within the phone app:

val nodesWithApp = capabilityClient
    .getCapability(CAPABILITY_WEAR_APP, CapabilityClient.FILTER_REACHABLE)
    .await()
    .nodes

By looking for only nodes without the capability, the team ensured the FotMob phone app only lists Wear OS devices without the app.

Initiating the install flow

The FotMob team designed an educational half-page prompt that quickly makes the user aware of the opportunity, allowing them either to kick off the install flow, or dismiss it. This featured a prominent screenshot of the Wear OS experience, allowing the user to immediately see how the app might look on their watch.

To start the installation, the app uses the RemoteActivityHelper API, to launch the Play Store on the watch:

val remoteActivityHelper = RemoteActivityHelper(context)

remoteActivityHelper.startRemoteActivity(
    Intent(Intent.ACTION_VIEW)
        .setData("market://details?id=${context.packageName}".toUri())
        .addCategory(Intent.CATEGORY_BROWSABLE),
    nodeId
).await()

Results

“The Wearable APIs made the implementation straightforward,” says Roy. “Being able to detect connected devices and query capabilities meant we could quickly determine whether the watch app was already installed. From there it was mostly about designing a prompt that felt helpful to users rather than intrusive.”

The rollout of the cross-device installation feature saw the largest single-day increase in FotMob’s installed audience on Wear OS in 5 years, 2-3x higher than the normal install rate. Within 48 hours of the rollout reaching 100%, the watch app gained over 1,500 new installs¹.

“Within the first 10 days we saw a significant jump in new Wear OS installs,” says Roy. “The watch app has been around for years, but this confirmed that many users with compatible devices simply weren’t aware it existed.”

Evolving cross-device installs

In addition to the solution employed by FotMob, we’ve now launched a library to make it even easier to implement these cross-device installation journeys through the In-App Install Prompts library.

The following is an example of adding an installation prompt at the appropriate point in your app:

val crossDevicePromptManager = CrossDevicePromptManagerFactory.create(activity)
val request = CrossDevicePromptInstallationRequest.create()

try {
    val info = crossDevicePromptManager.requestInstallationPromptFlow(request).await()
    crossDevicePromptManager.launchPromptFlow(activity, info).await()
} catch (e: CrossDevicePromptException) {
    Log.e(TAG, "Cross-device prompt failed with error: ${e.errorCode}", e)
}

Next steps: Start building your own cross-device journey today

Dive into the DataLayer sample to learn more about how to add cross-device functionality to your app, and explore the new In-App Install Prompts library, providing you with options for how you help your users achieve cross-device installation.

[1]. Install data from Play Developer Console

Bring Native Visibility to Your VoIP App Experience with Telecom's Latest Alpha

2026-05-14T13:00:00.000-07:00

Posted by Nataraj KR, Android Developer Relations Engineer

The initial launch of the Jetpack Telecom library introduced CallsManager, replacing the legacy ConnectionService API to simplify VoIP integration. CallsManager streamlines call lifecycle management and audio routing while enabling interactions with remote surfaces like smartwatches, Bluetooth devices, and Android Auto. Additionally, it supports call extensions for richer features—such as participant handling, custom icons, call silencing and meeting summary on remote surfaces—all while maintaining backward compatibility down to Android O (API Level 26).

Building on this foundation, Jetpack Telecom v1.1.0 brings native-level visibility and convenience to third-party VoIP apps. This latest release introduces powerful new capabilities, including unified call history, call log exclusion, and native callback functionality, making call management more seamless than ever for users.

Here is a closer look at what’s new and how you can implement these features in your applications.

Bridging the Dialer Gap: Unified Call History and Callbacks

Historically, users have had to open individual third-party apps to view their VoIP call history or return a missed call. With the new integrated call logging feature, system dialer apps can now surface call logs directly from third-party VoIP apps.

Even better, users can now initiate a callback to a VoIP contact straight from their native system dialer, streamlining the communication experience.

How it works:

To opt-in to this feature, do the following:

Register for Callbacks: Your VoIP app must register a new system-protected intent: TelecomManager.ACTION_CALL_BACK.
Log the Call: Use TelecomManager.addCall (or related Jetpack APIs) to ensure the system automatically logs the call.
Manage Call IDs: When a call is registered, CallControlScope.getCallId provides a unique UUID. The system dialer uses this exact TelecomManager.EXTRA_UUID when creating the callback intent.
Initiate the Callback: Your application must store and manage the call details associated with this UUID. When the system dialer fires the callback intent with the EXTRA_UUID, your app can seamlessly resolve the ID and initiate the call with the correct details.

Fine-Grained Control: Call Log Exclusion

We recognize that not every VoIP call should be visible in the system's native dialer history. Whether for privacy reasons, ephemeral communication, or app-specific behavior, you need control over what gets surfaced.

To address this, we are introducing Call Log Exclusion. You can now prevent specific calls from being logged into the system call logs by setting the isLogExcluded boolean to true within CallAttributesCompat. By configuring this flag, the call remains completely hidden from the system logs, and the native dialer will not display it.

Important Note on Compatibility
These integrated logging and callback features are available for devices running Android 16.1 (SDK 36.1) and higher. Refer here to compile your app with Android SDK 36.1.

Get Started

We encourage developers to test these integrations and explore how unified call history and callbacks can improve the daily user experience of your VoIP applications.

To help you get started and see these APIs in action, we have put together a sample application demonstrating the new integrations.

View the sample app here: https://github.com/android/platform-samples/tree/main/samples/connectivity/telecom

Check out the release notes and documentation to start implementing these features today!

Note: Although Jetpack Telecom v1.1.0 APIs are accessible for integration, the system dialer's ability to render native call logs is being introduced in phases, beginning with Google Meet. To safeguard against spam, native dialers utilize secure package allowlists to control VoIP display. For local testing of your callback and logging implementations, we recommend using the open-source Telecom Sample Dialer app as your emulator environment.

Building for the Intelligence System on Android

2026-05-12T07:00:00.000-07:00

Posted by Matthew McCullough, VP, Product Management, Android Developer

Announced today during The Android Show, Android is transitioning from an operating system to an intelligence system, creating more opportunities for engagement with your apps. Through deep integration between hardware and software, Android devices will be able to handle the heavy lifting of anticipating user needs, so your app can focus on delivering that experience at the right moment. As part of this, we are announcing Gemini Intelligence, a suite of new features that bring the best of Gemini to our most advanced Android devices.

Task Automation with Gemini

With Gemini Intelligence, we’re expanding Gemini’s ability to automate tasks across selected apps on behalf of the user with built-in transparency and control. This creates another avenue for user engagement, driving high-intent traffic to your app without requiring code or major engineering work from you. By allowing Gemini to navigate complex, multi-step tasks, such as ordering a latte from a cafe or building a shopping cart from a grocery list in a notes app, Gemini handles the logistics for users, so you’re free to focus on innovation and building great features.

We know there are times when people like to browse, and others when they want to quickly handle a task. Initially launched with selected food and ridesharing partners to build a grocery order or request a ride, this capability is expanding across more verticals and form factors, including foldables, watches, cars, and XR glasses.

Increase Engagement with AppFunctions

For more control over how agents interact with your app, you can use Android AppFunctions. This empowers you to provide specific tools, such as services, data, and actions directly to the OS and agents, paired with natural language descriptions. The system can then discover and execute these tools across form factors, enabling users to trigger your app’s functionality through the intelligence system for richer and more customized experiences with task automation. We’ve started testing these early stage APIs in a private preview with apps like KakaoTalk to enable users to “send messages” or “initiate voice calls” through this new framework. AppFunctions have already enabled local execution of 25 apps’ use cases across device manufacturers. You can experiment with the API locally and already register your interest to join the AppFunctions Early Access Program for full integration opportunities.

We’re providing multiple integration paths to meet you wherever you are on this intelligence journey, whether it’s with an effortless, “no-code change” app automation or using the AppFunctions API, to provide you with more control in an MCP-like fashion.

Enhanced User Experience with Widgets

We’re elevating the user experience by expanding widget support to new form factors, starting with cars. This creates new opportunities for you to engage with users on 250M Android Auto compatible vehicles.

Jetpack Glance makes it easy to build high-quality widgets, and it is now getting powerful new capabilities thanks to a new underlying framework called RemoteCompose.

New richer, premium interactions: Built to be deeply adaptive and battery efficient, RemoteCompose allows Glance to deliver richer, more premium interactions. You can soon leverage new capabilities, including snapscroll, expressive buttons, and particle effects to create more engaging widgets.
Built-in Backward Compatibility: These expressive RemoteCompose features are supported out-of-the-box on Android 16 and above. By using Jetpack Glance as your API, you maintain complete backward compatibility. Your widgets will automatically leverage these premium UI features on newer devices while gracefully degrading to support older OS versions.

Furthermore, RemoteCompose is the engine behind Create My Widget, a feature where users can ask Gemini to build fully adaptive custom widgets that can be resized and optimized seamlessly for the user's home screen or Wear OS watch.

Building Adaptively Beyond the Phone

From foldables, tablets, compatible cars, and XR headsets to the new Googlebooks, the canvas for Android apps has expanded across screens and form factors. Here are some of the updates to help you build adaptively:

Jetpack Navigation 3: Our latest Jetpack Navigation 3 offers deeper adaptive support adding Scene decorators to the Scene API. Scene decorators can be used to modify the scene calculated by your app's scene strategy. For example, they can be used to add common UI elements such as top app bars and navigation bars/rails that you’d like to add at the scene, rather than nav entry level. NavDisplay now includes built-in functionality that makes nav entries shared elements so now you can smoothly transition between scenes. Check out our Nav3-recipes for more.
Jetpack Compose: Adopting Compose into your app remains the easiest way to start building adaptive UIs, and we want to ensure that you have the right level of architectural support. We are working on a new set of building blocks in Compose 1.11 for responsive layouts and customization with Grid, Flexbox, MediaQuery and Style. We would love your feedback on them before removing the Experimental flag.
Design guidance: Explore our updated design gallery to be inspired, our new desktop design hub or our adaptive layout guidance to get started.

For device-differentiated experiences, take advantage of the latest updates to:

Car App Library: We’re streamlining development by expanding the Car App Library, which allows you to "build once" and deliver customized, distraction-optimized media experiences to both Android Auto and Android Automotive OS. We’re further enabling richer in-car engagement by expanding support for adaptive video apps, so that videos can played full screen when cars are parked.
Android XR SDK: The Android XR SDK allows you to build deeply differentiated, custom experiences for a growing spectrum of XR devices, including upcoming wired XR glasses (like XREAL’s Project Aura), while existing adaptive apps automatically surface in immersive environments without additional developmental effort. You can get ready for display glasses by using Jetpack Compose Glimmer to build glanceable UIs tailored for display glasses, alongside Jetpack Projected APIs to bridge app experiences from the phone to the user’s field of view. The developer preview 4 of the Android XR SDK, coming next week, introduces new interactive components like Title Chips and Button Groups that optimize input for glasses touchpads. It streamlines your workflow with the new ProjectedTestRule API to automate testing environments.

A New Age for Your Users on Android

From the shift to an intelligence system to the expansion of new form factors like Googlebooks, Android is creating new ways for people to get more out of their device experiences with developers and app makers at the center of it.

Gemini Intelligence features will roll out in waves as they become ready, starting with the latest Samsung Galaxy and Google Pixel phones this summer. They will also become available across your Android devices including your watch, car, glasses and laptops later this year.

Stay tuned for even more news about app development in this new era at Google I/O next week.

Gratitude saw 25% higher retention for widget users

2026-05-08T09:00:00.000-07:00

Posted by Ash Nohe and Amrit Sanjeev, Android Developer Relations Engineers

Practicing gratitude may decrease symptoms of depression and anxiety, and improve mental health and life satisfaction¹. Consistent gratitude practice may lead to sustained improvements that last months². The mindfulness app Gratitude encourages consistency through micro daily journaling, affirmations, and vision boards. The app has over 6 million downloads, 150 thousand 5-star ratings, and 100 million journal entries logged.

Developers Divij Gupta and Narendra Aanjna developed widgets for each of their app’s core user journeys. Their goal was to meet users in their everyday moments without requiring the overhead of a full app session.

By surfacing interactive journaling prompts, affirmations, vision board images and metrics directly on the user’s home screen, the team lowered the barrier to entry for daily reflection and reported a 25% increase in retention for widget users and ~1K weekly journal entries from widgets. This increase in user loyalty translates to tangible health outcomes for the users: consistent habit formations that support long-term mental well-being.

“Widgets helped us make the app more present in users’ daily routines by providing quick inspiration, reminders, and reflections directly on the home screen. This increased engagement and made it easier for users to stay consistent with their mindfulness practices.” – Divij Gupta

The Challenge: modernize without decreasing retention

While the impact of widgets was clear, Gratitude’s original XML-based RemoteViews implementation created technical debt. As the app’s design system evolved toward Material 3, the legacy widgets became increasingly difficult to align with the modern UI. Every visual update required manual XML overhead and brittle workarounds, slowing developer velocity.

The Solution Part 1: migrating from XML to Jetpack Glance

To modernize their widgets, the team turned to Jetpack Glance.

They first consulted the Widgets on Android design page and canonical widget layouts to understand best practices for displaying information within a limited amount of space.

Then, they migrated their widget suite to Jetpack Glance. This declarative framework enabled the developers to move from planning to shipping in less than a month, saving about 50% development time, and saw two additional advantages:

Replacing restrictive XML layouts with declarative code made the codebase easier to read, maintain, and reduced developer effort.
Jetpack Glance allowed the team to more easily implement dynamic colors, flexible resizing, and expanded configuration options. These features ensure the widgets harmonize with a user's unique home screen layout.

The following GIF shows two Gratitude widgets and adaptive resizing:

While Glance simplified the UI, the team noted that testing across various OEM launchers was also essential to ensure layout consistency across devices.

The team also implemented Generated Widget Previews so users can see personalized previews. They noted that testing Generated Previews could be slow, as the previews are rate limited to preserve battery. To bypass the rate limiting for testing, use the adb command:

adb shell device_config put systemui

generated_preview_api_reset_interval_ms 0

All of their efforts have made the Gratitude widget high quality and differentiated.

The Solution Part 2: promote new widgets in-app

The developers then used in-app widget pinning to increase widget discoverability and widget installs. Asking users to install widgets at a contextually relevant moment within the app helps users find their widgets without needing to go through the system widget picker. The following GIF shows Gratitude’s bottom sheet to add widgets from within the app:

The team also refactored widget packages, which changed widget receiver paths and caused widgets to be deleted from users’ home screens. Using previously stored user flags to identify widget users, they triggered another requestPinGlanceAppWidget prompt inviting widget users to use the new modernized widgets.

Developer Tip: To maintain widget installs while migrating from RemoteViews to Jetpack Glance, ensure your GlanceAppWidgetReceiver uses the same class name and package as your previous AppWidgetProvider in the Android Manifest. If a new class name or package location is required, follow the Gratitude’s lead by using in-app pinning to help users restore their widgets.

The strategy is working, as 10% of total DAU have adopted widgets.

Conclusion

This Gratitude story shows that widgets can be tools for habit formation. By implementing quick actions to self-reflect right from the home screen, the team may have improved user loyalty. Gratitude reduced technical debt and modernized their widgets by adopting Jetpack Glance, and prompted users to add widgets within their app.

“Our experience with Jetpack Glance has been excellent. The Compose-based approach feels much more modern, flexible, and aligned with the way we build the rest of our UI today. It allows us to express widget layouts more naturally, reuse familiar Compose components, and iterate on UI changes much faster. Many of the UI constraints we previously faced with RemoteViews are no longer an issue, which made it easier to build widgets that better match our app’s design and experience.” – Divij Gupta

Getting Started

To get started with Jetpack Glance and learn about the technologies mentioned in this post, see these guides:

See other widget case studies:

1: Diniz, G., Korkes, L., Tristão, L. S., Pelegrini, R., Bellodi, P. L., & Bernardo, W. M. (2023). The effects of gratitude interventions: a systematic review and meta-analysis. einstein (Sao Paulo)., 21, eRW0371. https://doi.org/10.31744/einstein_journal/2023RW0371

2: Bohlmeijer, E., Kraiss, J., Schotanus-Dijkstra, M., & ten Klooster, P. (2022). Gratitude as mood mediates the effects of a 6-weeks gratitude intervention on mental well-being: post hoc analysis of a randomized controlled trial. Front. Psychol., 12, 799447. https://doi.org/10.3389/fpsyg.2021.799447

A look ahead: Making it easier and faster to publish safer apps

2026-05-07T10:00:00.000-07:00

Posted by Vijaya Kaza, VP, Product, App & Ecosystem Trust

The mobile ecosystem is always evolving, bringing both new opportunities and new threats. Through these changes, Android and Google Play remain committed to ensuring that billions of users can continue to enjoy their apps with confidence and developer innovation can thrive. Earlier this year, we shared how Android and Google Play kept the ecosystem safe in 2025 by deepening our investments in AI and real-time defenses. Today, we’re giving you a look at how we’re making it easier and faster than ever for millions of developers to publish safer apps.

Simpler ways to build safer apps from the start

To help you catch potential issues before you hit submit, we’re integrating insights and new customized guidance built with AI to your publishing journey:

Catch policy issues while you code with expanded Play Policy Insights in Android Studio, which now offer warnings for common issues, like missing login credentials. Later this year, when you choose to connect your Play developer account directly to Android Studio, you’ll get tailored insights.
Choose the right SDKs with confidence by leveraging SDK Index. Later this year, we are bringing SDK insights directly into your development workflow so you can instantly see which SDKs comply with Play policies.

More powerful protection for your business and users

With new ways to stay ahead of fraud and abuse, and better tools to protect your users, we’re also making it easier to secure your app’s revenue and reputation.

Detect security threats and abuse faster with our stronger Play Integrity API, which developers rely on to make billions of checks everyday to help keep their business secure. With significantly shorter warm-up latency, you can use these real-time checks in your most speed-critical user journeys, like logins or payments, to catch unauthorized access and risky interactions.
Simplify how you manage user privacy with easy-to-integrate tools like the contact picker and location button to give users clearer choices. We're also updating our policies to raise the standard for user privacy.
Future-proofing app signing security on your behalf. We’re adding support for post-quantum cryptography in Play App Signing this year, which will protect your apps and app updates from potential threats with the emergence of quantum computing.

Faster, more predictable app publishing

We know how important it is to maintain a predictable release cycle, so we’re making the publishing process faster and more transparent.

Avoid unexpected review rejections with our expanding pre-review checks, which now identify unnecessary photo permission requests and other common violations before you submit.
Improve the speed and predictability of your review cycles by using the new release status API to check if your release is approved and published. We also added a new way for you to block new commits if a review is already in progress, so you don’t unintentionally restart your place in the queue.
Publish your releases even faster when we change our review architecture later this year to enable parallel publishing and faster reviews for your test tracks. You’ll be able to isolate your closed, open, and production tracks so that a review on one track no longer holds up updates on another.
Track your release history with the Submission history log later this year. Built at your request, this feature provides a complete record of every time you send an app or update for review and its status. This makes it easier for your team to coordinate and troubleshoot without digging through multiple menus.
Manage business changes securely with the account transfers feature to help you move ownership to new partners, entities, or team members (video). We’ve designed this highly developer-requested feature with safeguards to protect your business from fraud and account hijacking.
Get the right policy support when you need it. In the coming months you'll see AI-powered recommendations directly in your Play Console that help you resolve minor issues immediately. For more complex issues, you can create a ticket to connect with our policy specialists. We’re also giving new developers more guided support, including new Play Academy courses, to publish their first app with confidence. Later this year, we’ll expand this coaching experience for new developers.

Stronger security across the ecosystem

Finally, we’re bringing developer verification to the entire Android ecosystem to add another layer of security and make it much harder for malicious actors to repeatedly spread harm. Starting in September, these protections will roll out in select countries to help users feel more confident in the apps they download and without changing most users’ install experience. We will also update Android Bench to uplift the entire ecosystem’s ability to build and launch safer, higher quality apps using generative AI.

What’s next

Google Play is committed to helping you grow your business while keeping users safe, and we appreciate your continued feedback on the tools and programs. Thank you for partnering with us to make Android and Google Play a secure, trusted platform for everyone.

Gemini and Firebase AI Logic enabled Karrot to increase sales with a translation feature built in under 2 weeks

2026-05-04T10:00:00.000-07:00

Posted by Thomas Ezan, Sr Developer Relations Engineer and Tracy Agyemang, Product Marketing Manager

Karrot is a hyperlocal, community-driven peer-to-peer marketplace app that enables users to buy, sell, and trade items with other verified users. Since launching in South Korea in 2015, the platform has expanded into global markets, amassing over 43 million registered users.

After launching in North America, engineers at Karrot observed that 30% of users in the region use a non-English device language, such as Spanish. To make the app more accessible, the team wanted to bring seamless translation functionality to Karrot quickly and at scale. The developers determined that the most efficient way to implement quality translations would be through integrating an AI service directly into the app, so they selected the Firebase AI Logic and its Android SDK to access Gemini Flash Lite, which led to higher purchasing conversion among non-English users.

Integrating Gemini Firebase AI Logic

The team initially tested two on-device options: the ML Kit Translation SDK and Gemini Nano. But the team found challenges with each: ML Kit Translation didn’t meet the team’s quality expectations, and Gemini Nano, if it isn’t already on the device, required the user to download the model data.

The team then tested Firebase AI Logic. By calling the Gemini API directly from the app, Firebase AI Logic delivered accuracy at speeds that mirrored a natural conversational cadence.

Integrating Firebase AI Logic into the app was a “remarkably straightforward experience,” according to TaeGyu An, an Android Software Engineer on Karrot’s Mobile Platform team. TaeGyu and the team used the platform’s documentation and code samples to build a proof of concept in under three hours.

This allowed the team to spend more time refining prompts and finding optimal configuration values. “Even without extensive experience writing prompts, the official documentation's guides and tips made it easy to quickly identify the right direction for improving translation quality,” said WonJoong Lee, an Android Software Engineer on Karrot’s North America Product Team.

This low barrier to entry and rapid turnaround time enabled engineers to keep development costs low and go from proof of concept to production code in just two weeks—all without setting up a dedicated backend. That also freed up time to focus on UX and policy design, such as opt-in behavior and the conditions for the translation banner.

Driving sales with enhanced AI features

Since implementing translation using Gemini and Firebase AI Logic, the Karrot team observed higher purchasing conversion among non-English users, indicating that the translation feature is helping drive sales.

Of users who used a non-English device language, one in three of them who were shown the translation banner actively used the feature. The team has also observed that buyers offered translation functionality were 2.4X more likely to start a chat with a seller than those who weren’t.

The flexibility and simplicity of deploying Firebase AI Logic has led the team to explore other features to simplify the workstreams of its engineers. “It’s rewarding to build features that scale across diverse Android devices while helping neighbors connect and interact within their local communities,” concluded TaeGyu.

Going forward, the team plans to implement Server Prompt Templates to adjust prompts after release without shipping a new version of the app. This, combined with Remote Config, should help the team iterate faster and reduce operational overhead.

Get started

Learn how to build Gemini-enabled features like AI translations and in-app personalization and more with Firebase AI Logic to deliver better experiences to your users, faster.

What's new in the Jetpack Compose April '26 release

2026-04-22T16:00:00.000-07:00

Posted by Meghan Mehta, Android Developer Relations Engineer

Today, the Jetpack Compose April ‘26 release is stable. This release contains version 1.11 of core Compose modules (see the full BOM mapping), shared element debug tools, trackpad events, and more. We also have a few experimental APIs that we’d love you to try out and give us feedback on.

To use today’s release, upgrade your Compose BOM version to:

implementation(platform("androidx.compose:compose-bom:2026.04.01"))

Changes in Compose 1.11.0

Coroutine execution in tests

We’re introducing a major update to how Compose handles test timing. Following the opt-in period announced in Compose 1.10, the v2 testing APIs are now the default, and the v1 APIs have been deprecated. The key change is a shift in the default test dispatcher. While the v1 APIs relied on UnconfinedTestDispatcher, which executed coroutines immediately, the v2 APIs use the StandardTestDispatcher. This means that when a coroutine is launched in your tests, it is now queued and does not execute until the virtual clock is advanced.

This better mimics production conditions, effectively flushing out race conditions and making your test suite significantly more robust and less flaky.

To ensure your tests align with standard coroutine behavior and to avoid future compatibility issues, we strongly recommend migrating your test suite. Check out our comprehensive migration guide for API mappings and common fixes.

Shared element improvements and animation tooling

We’ve also added some handy visual debugging tools for shared elements and Modifier.animatedBounds. You can now see exactly what’s happening under the hood—like target bounds, animation trajectories, and how many matches are found—making it much easier to spot why a transition might not be behaving as expected. To use the new tooling, simply surround your SharedTransitionLayout with the LookaheadAnimationVisualDebugging composable.

LookaheadAnimationVisualDebugging(
    overlayColor = Color(0x4AE91E63),
    isEnabled = true,
    multipleMatchesColor = Color.Green,
    isShowKeylabelEnabled = false,
    unmatchedElementColor = Color.Red,
) {
    SharedTransitionLayout {
        CompositionLocalProvider(
            LocalSharedTransitionScope provides this,
        ) {
            // your content
        }
    }
}

Trackpad events

We’ve revamped Compose support for trackpads, like built-in laptop trackpads, attachable trackpads for tablets, or external/virtual trackpads. Basic trackpad events will now generally be considered PointerType.Mouse events, aligning mouse and trackpad behavior to better match user expectations. Previously, these trackpad events were interpreted as fake touchscreen fingers of PointerType.Touch, which led to confusing user experiences. For example, clicking and dragging with a trackpad would scroll instead of selecting. By changing the pointer type these events have in the latest release of Compose, clicking and dragging with a trackpad will no longer scroll.

We also added support for more complicated trackpad gestures as recognized by the platform since API 34, including two finger swipes and pinches. These gestures are automatically recognized by components like Modifier.scrollable and Modifier.transformable to have better behavior with trackpads.

These changes improve behavior for trackpads across built-in components, with redundant touch slop removed, a more intuitive drag-and-drop starting gesture, double-click and triple-click selection in text fields, and desktop-styled context menus in text fields.

To test trackpad behavior, there are new testing APIs with performTrackpadInput, which allow validating the behavior of your apps when being used with a trackpad. If you have custom gesture detectors, validate behavior across input types, including touchscreens, mice, trackpads, and styluses, and ensure support for mouse scroll wheels and trackpad gestures.

Before	After

Composition host defaults (Compose runtime)

We introduced HostDefaultProvider, LocalHostDefaultProvider, HostDefaultKey, and ViewTreeHostDefaultKey to supply host-level services directly through compose-runtime. This removes the need for libraries to depend on compose-ui for lookups, better supporting Kotlin Multiplatform. To link these values to the composition tree, library authors can use compositionLocalWithHostDefaultOf to create a CompositionLocal that resolves defaults from the host.

Preview wrappers

Android Studio custom previews is a new feature that allows you to define exactly how the contents of a Compose preview are displayed.

By implementing the PreviewWrapperProvider interface and applying the new @PreviewWrapper annotation, you can easily inject custom logic, such as applying a specific Theme. The annotation can be applied to a function annotated with @Composable and @Preview or @MultiPreview, offering a generic, easy-to-use solution that works across preview features and significantly reduces repetitive code.

class ThemeWrapper: PreviewWrapper {
    @Composable
    override fun Wrap(content: @Composable (() -> Unit)) {
        JetsnackTheme {
            content()
        }
    }
}

@PreviewWrapperProvider(ThemeWrapper::class)
@Preview
@Composable
private fun ButtonPreview() {
    // JetsnackTheme in effect
    Button(onClick = {}) {
        Text(text = "Demo")
    }
}

Deprecations and removals

As announced in the Compose 1.10 blog post, we’re deprecating Modifier.onFirstVisible(). Its name often led to misconceptions, particularly within lazy layouts, where it would trigger multiple times during scrolling. We recommend migrating to Modifier.onVisibilityChanged(), which allows for more precise manual tracking of visibility states tailored to your specific use case requirements.
The ComposeFoundationFlags.isTextFieldDpadNavigationEnabled flag was removed because D-pad navigation for TextFields is now always enabled by default. The new behavior ensures that the D-pad events from a gamepad or a TV remote first move the cursor in the given direction. The focus can move to another element only when the cursor reaches the end of the text.

Upcoming APIs

In the upcoming Compose 1.12.0 release, the compileSdk will be upgraded to compileSdk 37, with AGP 9 and all apps and libraries that depend on Compose inheriting this requirement. We recommend keeping up to date with the latest released versions, as Compose aims to promptly adopt new compileSdks to provide access to the latest Android features. Be sure to check out the documentation here for more information on which version of AGP is supported for different API levels.

In Compose 1.11.0, the following APIs are introduced as @Experimental, and we look forward to hearing your feedback as you explore them in your apps. Note that @Experimental APIs are provided for early evaluation and feedback and may undergo significant changes or removal in future releases.

Styles (Experimental)

We are introducing a new experimental foundation API for styling. The Style API is a new paradigm for customizing visual elements of components, which has traditionally been performed with modifiers. It is designed to unlock deeper, easier customization by exposing a standard set of styleable properties with simple state-based styling and animated transitions. With this new API, we’re already seeing promising performance benefits. We plan to adopt Styles in Material components once the Style API stabilizes.

A basic example of overriding a pressed state style background:

@Composable
fun LoginButton(modifier: Modifier = Modifier) {
    Button(
        onClick = {
            // Login logic
        },
        modifier = modifier,
        style = {
            background(
                Brush.linearGradient(
                    listOf(lightPurple, lightBlue)
                )
            )
            width(75.dp)
            height(50.dp)
            textAlign(TextAlign.Center)
            externalPadding(16.dp)

            pressed {
                background(
                    Brush.linearGradient(
                        listOf(Color.Magenta, Color.Red)
                    )
                )
            }
        }
    ){
        Text(
            text = "Login",
        )
    }
}

Check out the documentation and file any bugs here.

MediaQuery (Experimental)

The new mediaQuery API provides a declarative and performant way to adapt your UI to its environment. It abstracts complex information retrieval into simple conditions within a UiMediaScope, ensuring recomposition only happens when needed.

With support for a wide range of environmental signals—from device capabilities like keyboard types and pointer precision, to contextual states like window size and posture—you can build deeply responsive experiences. Performance is baked in with derivedMediaQuery to handle high-frequency updates, while the ability to override scopes makes testing and previews seamless across hardware configurations.

Previously, to get access to certain device properties — like if a device was in tabletop mode — you’d need to write a lot of boilerplate to do so:

@Composable
fun isTabletopPosture(
    context: Context = LocalContext.current
): Boolean {
    val windowLayoutInfo by
        WindowInfoTracker
            .getOrCreate(context)
            .windowLayoutInfo(context)
            .collectAsStateWithLifecycle(null)

    return windowLayoutInfo.displayFeatures.any { displayFeature ->
        displayFeature is FoldingFeature &&
            displayFeature.state == FoldingFeature.State.HALF_OPENED &&
            displayFeature.orientation == FoldingFeature.Orientation.HORIZONTAL
    }
}

@Composable
fun VideoPlayer() {
    if(isTabletopPosture()) {
        TabletopLayout()
    } else {
        FlatLayout()
    }
}

Now, with UIMediaQuery, you can add the mediaQuery syntax to query device properties, such as if a device is in tabletop mode:

@OptIn(ExperimentalMediaQueryApi::class)
@Composable
fun VideoPlayer() {
    if (mediaQuery { windowPosture == UiMediaScope.Posture.Tabletop }) {
        TabletopLayout()
    } else {
        FlatLayout()
    }
}

Check out the documentation and file any bugs here.

Grid (Experimental)

Grid is a powerful new API for building complex, two-dimensional layouts in Jetpack Compose. While Row and Column are great for linear designs, Grid gives you the structural control needed for screen-level architecture and intricate components without the overhead of a scrollable list.

Grid allows you to define your layout using tracks, gaps, and cells, offering familiar sizing options like Dp, percentages, intrinsic content sizes, and flexible "Fr" units.

@OptIn(ExperimentalGridApi::class)
@Composable
fun GridExample() {
    Grid(
        config = {
            repeat(4) { column(0.25f) }
            repeat(2) { row(0.5f) }
            gap(16.dp)
        }
    ) {
        Card1(modifier = Modifier.gridItem(rowSpan = 2)
        Card2(modifier = Modifier.gridItem(colmnSpan = 3)
        Card3(modifier = Modifier.gridItem(columnSpan = 2)
        Card4()
    }
}

You can place items automatically or explicitly span them across multiple rows and columns for precision. Best of all, it’s highly adaptive—you can dynamically reconfigure your grid tracks and spans to respond to device states like tabletop mode or orientation changes, ensuring your UI looks great across form factors.

Check out the documentation and file any bugs here.

FlexBox (Experimental)

FlexBox is a layout container designed for high performance, adaptive UIs. It manages item sizing and space distribution based on available container dimensions. It handles complex tasks like wrapping (wrap) and multi-axis alignment of items (justifyContent, alignItems, alignContent). It allows items to grow (grow) or shrink (shrink) to fill the container.

@OptIn(ExperimentalFlexBoxApi::class)
fun FlexBoxWrapping(){
    FlexBox(
        config = {
            wrap(FlexWrap.Wrap)
            gap(8.dp)
        }
    ) {
        RedRoundedBox()
        BlueRoundedBox()
        GreenRoundedBox(modifier = Modifier.width(350.dp).flex { grow(1.0f) })
        OrangeRoundedBox(modifier = Modifier.width(200.dp).flex { grow(0.7f) })
        PinkRoundedBox(modifier = Modifier.width(200.dp).flex { grow(0.3f) })
    }
}

Check out the documentation and file any bugs here.

New SlotTable implementation (Experimental)

We’ve introduced a new implementation of the SlotTable, which is disabled by default in this release. SlotTable is the internal data structure that the Compose runtime uses to track the state of your composition hierarchy, track invalidations/recompositions, store remembered values, and track all metadata of the composition at runtime. This new implementation is designed to improve performance, primarily around random edits.

To try the new SlotTable, enable ComposeRuntimeFlags.isLinkBufferComposerEnabled.

Start coding today!

With so many exciting new APIs in Jetpack Compose, and many more coming up, it's never been a better time to migrate to Jetpack Compose. As always, we value your feedback and feature requests (especially on @Experimental features that are still baking) — please file them here. Happy composing!

Streamline User Journeys with Verified Email via Credential Manager

2026-04-22T13:00:00.000-07:00

Posted by Niharika Arora, Senior Developer Relations Engineer and Jean-Pierre Pralle, Product Manager, Credential Manager

In the modern digital landscape, the first encounter a user has with an app is often the most critical. Yet, for decades, this initial interaction has been hindered by the friction of traditional verification methods. Today, we're excited to announce a new verified email credential issued by Google, which developers can now retrieve directly from Android’s Credential Manager Digital Credential API.

The Problem: Authentication Friction in the Modern Era

The "current era" of authentication is defined by a trade-off between security and convenience. To ensure that a user owns the email address they provide, you typically rely on One-Time Passwords (OTPs) or "magic links" sent by email or SMS.

While effective, these traditional steps introduce significant hurdles:

Context switching: Users must leave the app, open their inbox or messaging app, find the code, and return, a process where many potential users simply drop off.
Delivery issues: While Emails are free, they can be delayed or diverted to spam folders.
Onboarding friction: Every extra second spent in the "verification loop" is a second where a user might lose interest, directly impacting conversion rates.

The Solution: Seamless, Verified Email

Google now issues a cryptographically verified email credential directly to Android devices. This verified email credential is delivered through the Credential Manager API, which is Android's implementation of the W3C's Digital Credential API standard.

For users, this completely removes the need to manually verify their email through external channels. For developers, the API securely delivers these verified user claims for any scenario whether you are building an account creation flow, a recovery process, or a high-risk step-up authentication.

While this specific verified email address is sourced securely from the user's Google Account on their device, the underlying Digital Credentials API is issuer-agnostic. This fosters an open ecosystem, allowing any holder of a digital credential with an email claim to offer that verification to your app.

User Experience

The beauty of this API lies in its simplicity for the end user. Instead of hunting for OTP codes, the experience is integrated directly into the Android OS:

Initiation: The process begins when a user focuses on an email input field or taps a "Sign up" or "Recover account" button. You can also initiate the process on page load.
Transparency: A native Android bottom sheet appears, clearly detailing exactly what data is being requested (for example, user’s verified email address).
One-tap consent: The user simply taps "Agree and continue" to share the data.
Immediate progress: Once consent is given, the app receives the data instantly. For sign-up or account recovery flows, you can then seamlessly transition the user into passkey creation, ensuring:
- Users do not have to enter any user information manually, as compared to the traditional username/password registration.
- Their next login is even faster and more secure.

Use case 1. Sign up

Accelerate onboarding by fetching a verified email the moment the user taps "Sign up". We strongly recommend you pair the verified email retrieval with passkey creation, also part of the Credential Manager API:

Note: You can also fetch other unverified fields such as a user’s given name, family name, name, profile picture and the hosted domain connected with the verified email.

Use case 2. Account recovery

Eliminate the frustration of users hunting for recovery codes in their spam folders by allowing them to recover their account using the verified email securely stored on their device.

Use case 3. Re-authentication for sensitive actions

Protect sensitive user actions, such as changing settings or updating profile details, by requiring a quick re-authentication step. Instead of an OTP, you can provide a low-friction verification using the device's verified email.

Important Considerations

As you design your authentication architecture around the Digital Credentials API, keep the following details in mind:

Account support: For the specific email credential issued by Google, only regular consumer Google Accounts are supported (Workspace and supervised accounts are currently not supported). Keep in mind that the Credential Manager API itself is issuer-agnostic, meaning other identity providers can issue credentials with their own account support policies.
Other user data: Beyond email, you can request the user's given name, family name, full name, and profile picture. However, note that only the email is verified by Google.
Auto verify your @gmail accounts: The API provides verified emails for all consumer Google Accounts. We recommend auto-verifying @gmail.com users and routing custom domains to your existing verification flow - for example, an OTP flow. This ensures you maintain long-term access for external domains not directly managed by Google.
Complementary to Sign in with Google: While both the new verified email credential & Sign in with Google API provides a verified email, the choice depends on the intended user experience:
- Use Sign in with Google when your users want to create a federated login session.
- Use Verified Email when your users want to sign in traditionally with a username/password or passkey but want to auto-verify the email address without the manual chore of an OTP.

Conclusion and Next steps

By integrating the new verified email via Credential Manager API, you can drastically reduce onboarding friction and provide users with a more streamlined, secure authentication journey. This represents a shift toward a future where "verification" is no longer a manual chore for the user, but a seamless, integrated part of the native mobile experience.

Ready to see how this fits into your own app? To get started, update your project to the latest Credential Manager API and explore our Integration Guide. We encourage you to explore how this streamlined verification can simplify your critical user journeys from optimizing account creation, to enhancing re-authentication flows.

Level up your development with Planning Mode and Next Edit Prediction in Android Studio Panda 4

2026-04-21T07:00:00.000-07:00

Posted by Matt Dyor, Senior Product Manager

Android Studio Panda 4 is now stable and ready for you to use in production. This release brings Planning Mode, Next Edit Prediction, and more, making it easier than ever to build high-quality Android apps.

Here’s a deep dive into what’s new:

Planning Mode

Before the Agent starts working on complex tasks for you, it would be helpful if it could come up with a detailed plan. Jumping straight into a large coding project without a design often leads to technical debt or logic errors; the same is true for AI. That’s why we’re adding Planning Mode.

In this mode, the Agent comes up with a detailed project plan before executing tasks. Instead of a single pass where the model directly predicts the next token of code, Planning Mode facilitates a multi-stage reasoning process — giving the agent additional space to evaluate its own proposed logic for potential issues before presenting it to you. This is especially useful for complex and long-running tasks which demand a high degree of architectural precision.

To use Planning Mode, switch your conversation mode to "Planning" in the agent input box and enter your prompt. to “Planning” and enter your prompt.

Switch to Planning Mode

In Planning Mode, the agent examines your request and may generate an implementation plan for large or complex tasks. You have the opportunity to fix mistakes or clarify which approaches to use—all before the agent has spent any time or tokens heading in the wrong direction.

Open Implementation Plan

Add Comments to Implementation Plan

After adding comments, simply hit “Submit Comments” and the agent will use your feedback to revise the implementation plan. To stay on track during execution—which is particularly important with larger changes—the agent organizes its work and generates a "Task List" artifact. You can sit back and watch as the agent methodically completes all of the tasks.

Task List Artifact

After the work is done, the agent produces a “Walkthrough” artifact, giving you a clear summary of exactly what has been changed—making it easy to review the agent's changes. Build with more confidence and control using Planning Mode in the latest release of Android Studio.

Add Comments to Implementation Plan

Next Edit Prediction

Classic autocomplete is great for finishing your sentences, but coding is rarely a linear path. Often, a change in one place requires a secondary change elsewhere—like adding a new parameter to a function and then needing to update its invocations, or a UI preview update when a Composable is changed. Traditionally, this meant breaking your focus to hunt down the related lines of code that need attention.

Next Edit Prediction (NEP) evolves code completion by anticipating your next move, even when it’s not at your current cursor position. By analyzing your recent edits, Android Studio recognizes the logical pattern of your workflow. If you modify a data class or update a constructor, NEP can suggest the next relevant edit—perhaps in a distant function—allowing you to jump straight to the fix.

Instead of manually navigating back and forth, you can accept these multi-location suggestions with a single keystroke. This keeps you deep in the "flow state," reducing the cognitive load of routine updates and letting you focus on the complex logic that truly matters to your application. Experience a more intuitive, non-linear way to code in the latest version of Android Studio.

NEP Updating Function Name

NEP Adding New Line

Gemini API Starter Template

Adding powerful AI features to your app just got easier, introducing the Gemini API Starter Template for Android Studio!

Integrating generative AI into your Android application used to mean managing complex backend plumbing and worrying about API key security. With the new Gemini API Starter template in Android Studio, developers can now jump straight into building features rather than spending time configuring infrastructure.

Key benefits include:

Zero API key management: Stop worrying about provisioning or rotating keys. By leveraging Firebase AI Logic, the template eliminates the need to embed sensitive credentials in your client-side code.
Automated Firebase integration: The backend plumbing is handled for you. The template automatically connects your project to Firebase services, ensuring a secure bridge between your app and Google’s Gemini models.
Built to scale: This isn't just for prototypes. The production-ready architecture allows you to scale from a local test to a global user base without redesigning your foundation.
Multimodal processing: Supports text, image, video, and audio inputs. You can build features like real-time image analysis, video summarization, and audio transcription.

Get Started

Open Android Studio.
Navigate to File > New > New Project.
Select the Gemini API Starter template from the gallery.

Gemini API Starter new project template

Agent Web Search

When you’re deep in development, the right answer is often just a search away—but leaving your IDE to find it can snap you out of your flow. Whether you need the exact version number for a dependency or the latest API changes for a third-party library, the Agent Web Search tool is here to help without you ever having to leave Android Studio.

While Android Studio’s agent already leverages the Android Knowledge Base for official documentation, modern Android development relies on a vast ecosystem of external libraries. Agent Web Search expands Gemini's reach, allowing it to query Google directly to fetch current reference material from across the web. From checking the latest setup guides for Coil to finding advanced configuration tips for Koin or Moshi, the agent can now pull in the most up-to-date information in real time.

The Agent Web Search tool is designed to be helpful but unobtrusive; it will automatically trigger a web search when it identifies a gap in its local knowledge. You can also take the wheel by asking it to find something specific—simply include "search the web for..." in your prompt. By integrating live web results directly into your workspace, Agent Web Search ensures you’re always building with the most current data available, speeding up your workflow and keeping your project on the cutting edge.

Agent Web Search Tool Invocation

Android Studio Panda Releases

Panda 4 continues Android Studio’s focus on accelerating developer productivity with AI. Check out Go from prompt to working prototype with Android Studio Panda 2 and Increase Guidance and Control over Agent Mode with Android Studio Panda 3.

Android Studio Panda 2

AI-powered New Project flow: Allows you to build a working app prototype with a single prompt. The agent manages initial setup, navigation configuration, and proper dependencies, and features an autonomous generation loop to handle build errors and deploy to an emulator.
Version Upgrade Assistant: Automates dependency management and updates, iteratively attempting builds and resolving conflicts until a stable configuration is found.

Android Studio Panda 3

Agent skills: Specialized, user-defined instructions (stored in a .skills directory) that teach the AI agent project-specific capabilities, coding standards, or library usage.
Agent permissions: Provides fine-grained control over what agents can do, with features like "Always Allow" rules for trusted operations. For even more security, you can also use an optional sandbox to enforce strict, isolated control over the agent.
Empty Car App Library App template: Simplifies building driving-optimized apps for Android Auto and Android Automotive OS by handling required boilerplate code.

Get started

Dive in and accelerate your development. Download Android Studio Panda 4 and start exploring these powerful new agentic features today.

As always, your feedback is crucial to us. Check known issues, report bugs, and be part of our vibrant community on LinkedIn, Medium, YouTube, or X. Happy coding!

Android Studio, androidstudio, Android Studio Panda, featured, Gemini in Android Studio, AI-powered new project flow, version upgrade assistant

Experimental hybrid inference and new Gemini models for Android

2026-04-17T13:00:00.000-07:00

Posted by Thomas Ezan, Senior Developer Relations Engineer

If you are an Android developer looking to implement innovative AI features into your app, we recently launched powerful new updates: Hybrid inference, a new API for Firebase AI Logic to leverage both on-device and Cloud inference, and support for new Gemini models including the latest Nano Banana models for image generation.

Let’s jump in!

Experiment with hybrid inference

With the new Firebase API for hybrid inference, we implemented a simple rule-based routing approach as an initial solution to let you use both on-device and cloud inference via a unified API. We are planning on providing more sophisticated routing capabilities in the future.

It allows your app to dynamically switch between Gemini Nano running locally on the device and cloud-hosted Gemini models. The on-device execution uses ML Kit's Prompt API. The cloud inference supports all the Gemini models from Firebase AI Logic in both Vertex AI and the Developer API.

To use it, add the firebase-ai-ondevice dependencies to your app along with Firebase AI Logic:

dependencies {
 [...] 
 implementation("com.google.firebase:firebase-ai:17.11.0")
 implementation("com.google.firebase:firebase-ai-ondevice:16.0.0-beta01")
}

During initialization, you create a GenerativeModel instance and configure it with specific inference modes, such as PREFER_ON_DEVICE (falls back to cloud if Gemini Nano is not available on the device) or PREFER_IN_CLOUD (falls back to on-device inference if offline):

val model = Firebase.ai(backend = GenerativeBackend.googleAI())
    .generativeModel(
        modelName = "gemini-3.1-flash-lite",
        onDeviceConfig = OnDeviceConfig(
           mode = InferenceMode.PREFER_ON_DEVICE
        )
    )

val response = model.generateContent(prompt)

The Firebase API for hybrid inference for Android is still experimental, and we encourage you to try it in your app, especially if you are already using Firebase AI Logic. Currently, on-device models are specialized for single-turn text generation based on text or single Bitmap image inputs. Review the limitations for more details.

We just published a new sample in the AI Sample Catalog leveraging the Firebase API for hybrid; it demonstrates how the Firebase API for hybrid inference can be used to generate a review based on a few selected topics and then translating it into various languages. Check out the code to see it in action!

The new hybrid inference sample in action

Try our new models

As part of the new Gemini models, we've released two models particularly helpful to Android developers and easy to integrate in your application via the Firebase AI Logic SDK.

Nano Banana

Last year we released Nano Banana, a state-of-the-art image generation model. And a few weeks ago, we released a couple of new Nano Banana models.

Nano Banana Pro (Gemini 3 Pro Image) is designed for professional asset production and can render high-fidelity text, even in a specific font or simulating different types of handwriting.

Nano Banana 2 (Gemini 3.1 Flash Image) is the high-efficiency counterpart to Nano Banana Pro. It's optimized for speed and high-volume use cases. It can be used for a broad range of use cases (infographics, virtual stickers, contextual illustrations, etc.).

The new Nano Banana models leverage real-world knowledge and deep reasoning capabilities to generate precise and detailed images.

We updated our Magic Selfie sample (use image generation to change the background of your selfie!) to use Nano Banana 2. The background segmentation is now handled directly with the image generation model which makes the implementation easier and lets Nano Banana 2 improved image generation capabilities shine. See it in action here.

The updated Magic Selfie sample uses Nano Banana 2 to update a selfie background

You can use it via Firebase AI Logic SDK. Read more about it in the Android documentation.

Gemini 3.1 Flash-Lite

We also released Gemini 3.1 Flash-Lite, a new version of the Gemini Flash-Lite family. The Gemini Flash-Lite models have been particularly favored by Android developers for its good quality/latency ratio and low inference cost. It’s been used by Android developers for various use-cases such as in-app messaging translation or generating a recipe from a picture of a dish.

Gemini 3.1 Flash-Lite, currently in preview, will enable more advanced use cases with latency comparable to Gemini 2.5 Flash-Lite. To learn more about this model, review the Firebase documentation.

Conclusion

It’s a great time to explore the new Hybrid sample in our catalog to see these capabilities in action and understand the benefits of routing between on-device and cloud inference. We also encourage you to check out our documentation to test the new Gemini models.

The Fourth Beta of Android 17

2026-04-16T13:00:00.000-07:00

Posted by Dan Galpin, Developer Relations Engineer

Android 17 has reached beta 4, the last scheduled beta of this release cycle, a critical milestone for app compatibility and platform stability. Whether you're fine-tuning your app's user experience, ensuring smooth edge-to-edge rendering, or leveraging the newest APIs, Beta 4 provides the near-final environment you need to be testing with.

Get your apps, libraries, tools, and game engines ready!

If you develop an Android SDK, library, tool, or game engine, it's critical to prepare any necessary updates now to prevent your downstream app and game developers from being blocked by compatibility issues and allow them to target the latest SDK features. Please let your downstream developers know if updates are needed to fully support Android 17.

Testing involves installing your production app or a test app making use of your library or engine using Google Play or other means onto a device or emulator running Android 17 Beta 4. Work through all your app's flows and look for functional or UI issues. Each release of Android contains platform changes that improve privacy, security, and overall user experience; review the app impacting behavior changes for apps running on and targeting Android 17 to focus your testing, including the following:

Resizability on large screens: Once you target Android 17, you can no longer opt out of maintaining orientation, resizability and aspect ratio constraints on large screens.
Dynamic code loading: If your app targets Android 17 or higher, the Safer Dynamic Code Loading (DCL) protection introduced in Android 14 for DEX and JAR files now extends to native libraries. All native files loaded using System.load() must be marked as read-only. Otherwise, the system throws UnsatisfiedLinkError.
Enable CT by default: Certificate transparency (CT) is enabled by default. (On Android 16, CT is available but apps had to opt in.)
Local network protections: Apps targeting Android 17 or higher have local network access blocked by default. Switch to using privacy preserving pickers if possible, and use the new ACCESS_LOCAL_NETWORK permission for broad, persistent access.
Background audio hardening: Starting in Android 17, the audio framework enforces restrictions on background audio interactions including audio playback, audio focus requests, and volume change APIs. Based on your feedback, we’ve made some changes since beta 2, including targetSDK gating while-in-use FGS enforcement and exempting alarm audio. Full details available in updated guidance.

App memory limits

Android is introducing app memory limits based on the device's total RAM to create a more stable and deterministic environment for your applications and Android users. In Android 17, limits are set conservatively to establish system baselines, targeting extreme memory leaks and other outliers before they trigger system-wide instability resulting in UI stuttering, higher battery drain, and apps being killed. While we anticipate minimal impact on the vast majority of app sessions, we recommend the following memory best practices, including establishing a baseline for memory.

In the current implementation, getDescription in ApplicationExitInfo will contain the string "MemoryLimiter" if your app was impacted. You can also use trigger-based profiling with TRIGGER_TYPE_ANOMALY to get heap dumps that are collected when the memory limit is hit.

The LeakCanary task in the Android Studio Profiler

To help you find memory leaks, Android Studio Panda adds LeakCanary integration directly in the Android Studio Profiler as a dedicated task, contextualized within the IDE and fully integrated with your source code.

A lighter memory footprint translates directly to smoother performance, longer battery life, and a premium experience across all form factors. Let’s build a faster, more reliable future for the Android ecosystem together!

Profiling triggers for app anomalies

Android introduces an on-device anomaly detection service that monitors for resource-intensive behaviors and potential compatibility regressions. Integrated with ProfilingManager, this service allows your app to receive profiling artifacts triggered by specific system-detected events.

Use the TRIGGER_TYPE_ANOMALY trigger to detect system performance issues such as excessive binder calls and excessive memory usage. When an app breaches OS-defined memory limits, the anomaly trigger allows developers to receive app-specific heap dumps to help identify and fix memory issues. Additionally, for excessive binder spam, the anomaly trigger provides a stack sampling profile on binder transactions.

This API callback occurs prior to any system imposed enforcements. For example, it can help developers collect debug data before the app is terminated by the system due exceeding memory limits. To understand how to use the trigger check out our documentation on trigger based profiling.

val profilingManager = applicationContext.getSystemService(ProfilingManager::class.java)
val triggers = ArrayList<ProfilingTrigger>()  
triggers.add(ProfilingTrigger.Builder(
             ProfilingTrigger.TRIGGER_TYPE_ANOMALY))
val mainExecutor: Executor = Executors.newSingleThreadExecutor()
val resultCallback = Consumer<ProfilingResult> { profilingResult ->
    if (profilingResult.errorCode != ProfilingResult.ERROR_NONE) {
        // upload profile result to server for further analysis          
        setupProfileUploadWorker(profilingResult.resultFilePath)
    } 
}
profilingManager.registerForAllProfilingResults(mainExecutor, resultCallback)
profilingManager.addProfilingTriggers(triggers)

Post-Quantum Cryptography (PQC) in Android Keystore

Android Keystore added support for the NIST-standardized ML-DSA (Module-Lattice-Based Digital Signature Algorithm). On supported devices, you can generate ML-DSA keys and use them to produce quantum-safe signatures, entirely in the device’s secure hardware. Android Keystore exposes the ML-DSA-65 and ML-DSA-87 algorithm variants through the standard Java Cryptographic Architecture APIs: KeyPairGenerator, KeyFactory, and Signature. For further details, see our developer documentation.

KeyPairGenerator generator = KeyPairGenerator.getInstance(
        “ML-DSA-65”, "AndroidKeyStore");
generator.initialize(
        new KeyGenParameterSpec.Builder(
                “my-key-alias”,
                KeyProperties.PURPOSE_SIGN | KeyProperties.PURPOSE_VERIFY)
        .build());
KeyPair keyPair = generator.generateKeyPair();

Get started with Android 17

You can enroll any supported Pixel device to get this and future Android Beta updates over-the-air. If you don’t have a Pixel device, you can use the 64-bit system images with the Android Emulator in Android Studio.

If you are currently in the Android Beta program, you will be offered an over-the-air update to Beta 4. Continue to report issues and submit feature requests on the feedback page. The earlier we get your feedback, the more we can include in our work on the final release.

For the best development experience with Android 17, we recommend that you use the latest preview of Android Studio (Panda). Once you’re set up, here are some of the things you should do:

Compile against the new SDK, test in CI environments, and report any issues in our tracker on the feedback page.
Test your current app for compatibility, learn whether your app is affected by changes in Android 17, and install your app onto a device or emulator running Android 17 and extensively test it.

We’ll update the preview/beta system images and SDK regularly throughout the Android 17 release cycle. Once you’ve installed a beta build, you’ll automatically get future updates over-the-air for all later previews and Betas. For complete information, visit the Android 17 developer site.

Join the conversation

Your feedback remains our most valuable asset. Whether you’re an early adopter on the Canary channel or an app developer testing on Beta 4, consider joining our communities and filing feedback. We’re listening.