Hi r/AndroidDev,
ICYMI, Android Dev Summit returned last week after a four-year hiatus (Oct. 28–29), featuring over 50 sessions covering agentic development workflows (Android CLI, Agent Client Protocol support in Android Studio [i.e. Bring Your Own Agent], and declarative builds with Lightbuild), on-device and hybrid AI (Gemini Nano 4, Gemma 4, and Android MCP), our shift to a Compose-first UI architecture, and building across form factors like Googlebook and Android XR. If you couldn't make it out in person, the recorded session VODs are now live on YouTube so you can catch up on the talks relevant to your stack at your own pace—I've rounded up all of the links and descriptions by track below so everything is in one place.
Also worth noting if you'd rather skim or feed sessions straight into your coding workflow: the Android Dev Summit site is set up for agents this year:
- 📄 Download any talk as Markdown: Includes a summary, resource links, a speaker-labeled transcript, and code blocks in one file—drop a few into your agent and ask what changed for your app.
- 🗂️ Point an agent at one JSON feed: Structured metadata covering every session.
- 🧩 Grab the Agent Skills: Install the modular instruction sets each talk references.
If you're short on time and want to quickly catch up on the biggest announcements from ADS, start with the Android Dev Summit 2026 Keynote and check out these three recap posts on the Android Developers Blog:
- Your favorite agents are now integrated in Android Studio
- What's new in Android developer tools and performance at Android Dev Summit
- Agentic and Flexible: A next era of Android development
Integrate your app with the Android intelligence system
Android is evolving into an intelligence system where agents like Gemini orchestrate tasks across apps. To unlock new user experiences and participate in these agentic workflows, your app must expose its core capabilities.
This session is a practical guide to integrating your app with Android's intelligence layer. We'll survey key integration paths - including on-device Android MCP, server-side MCP, and Task Automation - and provide a decision framework for choosing the right path for your use case. We'll also explore proactive experiences with Personal Context.
You will learn how to:
* Select the optimal integration path for your app's needs.
* Implement both reactive and proactive intelligence features.
* Balance performance and security in agentic integrations.
Inside Gemini Nano and Gemma 4 powering on-device intelligence
Gemma 4 brings capable, multimodal AI directly to Android devices. In this session, we'll trace how Gemma evolved into a model family built for efficiency and explore what the edge-optimized E2B and E4B models can do on-device, from vision and audio understanding to agentic function calling. We'll cover the architecture behind that efficiency, including Per-Layer Embeddings (PLE), and show how Gemma and Gemini Nano work together through AICore. You'll learn how Quantization-Aware Training (QAT) preserves model capability within 1.1–3.5 GB RAM footprints, while Multi-Token Prediction (MTP) accelerates decoding speeds 1.5x–3x for responsive, real-time experiences.
On-device intelligence: Optimized performance and quality using Android ML Kit APIs
In this session, we'll explore different GenAI use cases using ML Kit APIs to understand when on-device GenAI is ideal for an app and also understand how to evaluate existing GenAI use cases to see if on-device models can satisfy their quality bar.
Build optimized Android Apps with Firebase AI Logic and Gemini Nano 4
Building production-ready generative AI into Android apps requires more than connecting to an LLM—it demands enterprise-grade security and cost controls. In this session, discover how Firebase AI Logic empowers developers to deploy secure, budget-conscious AI experiences at scale.
We will cover from security foundations and Firebase App Check, cost management, dynamic model routing to leveraging the multimodal capabilities.
Extend your app to Gemini and Search with the Connected Apps Platform
Explore how to connect your applications seamlessly to Gemini, Search and the Android intelligence system.
The new Connected Apps Platform lets you integrate your app's services directly into Gemini, AI Mode in Search, and the Android intelligence system. This session provides a practical guide to getting started. Using code examples and learning from real-life case studies, we’ll walk through the development lifecycle: building, testing, and publishing your first connected app to reach users within their AI-powered workflows.
By the end of this session, you'll be able to:
* Integrate your service with the Connected Apps Platform.
* Test your integration across different AI surfaces.
* Publish your app’s features into users' AI workflows.
Mastering on-device intelligence with ML Kit and LiteRT in Google Play services
Stop choosing between plug-and-play AI convenience and custom model flexibility—you can deploy both in a single, ultra-lean app without adding megabytes of binary bloat.
In this session, we’ll demonstrate how to build this exact dual-stack architecture in a single Android app. You’ll see how to leverage ML Kit for ready-to-use classical ML tasks (like doc scan) alongside LiteRT standalone in Play services for your custom computer vision or audio workloads. We’ll dive deep into how both implementation paths unite under the hood to utilize the modern LiteRT runtime, giving your app seamless, hardware-accelerated performance on CPU and GPUs with a virtually zero-byte download footprint.
Key takeaways for developers:
* Uncompromised performance: Both turnkey and custom models are hardware-accelerated automatically using the unified CompiledModel API.
* Micro-APKs: Dramatically reduce your app’s download size by offloading both the ML Kit and LiteRT runtimes to Play services.
* Hybrid integration: Master running multiple ML workflows side-by-side in production without resource conflicts.
Unlock agentic capabilities in your app with ML Kit GenAI
Take your Android AI features to the next level by building autonomous on-device agents. In this session, we dive into ML Kit’s new agentic APIs, built directly on top of the direct model access APIs you already know.
Using the open-source Jetpacker app, you’ll learn how to chain multi-step actions across local data, manage stateful multi-turn sessions with isolated contexts, and wire up Android MCP to power both in-app assistants and Android system-level surfaces with a single codebase.
Agentic coding workflows with small models
While large frontier models dominate the headlines, small language models (SLMs) like Gemma 4 offer low-latency, cost-effective, and fully offline intelligence to augment daily developer workflows.
This talk explores practical patterns for integrating small models into Android development, from smart task routing to cost optimization, using Gemma 4 as our primary hands-on case study to demonstrate real-world use cases and how to configure developer tools and agentic workflows.
Let agents generate UI in your Android apps with A2UI
A2UI is transitioning from web-centric components to native Android. The new Jetpack Compose renderer for A2UI v0.9 enables developers to render dynamic, LLM-generated UI natively. Instead of webviews, it leverages a Coroutine-driven actor framework, sealed-class lifecycles, and native Material 3 integration.
This session walks through the new architecture, explaining how server-driven component trees translate into reactive Compose nodes, and how built-in layout transitions handle structural updates smoothly without blocking the UI.
Building a Formula E co-driver on Android with ML Kit and Gemini Nano
Android tools & performanceA racing car is a demanding environment of high speed, heat, and telemetry constraints. How can an on-device agent help process real-time vehicle data for sports and engineering applications?
This technical session explores an experimental hybrid architecture combining edge hardware and cloud agents. We'll walk through a research proof-of-concept using a Raspberry Pi to stream CAN bus telemetry, a Pixel phone running an on-device conversational agent powered by ML Kit and Gemini Nano, and an agent-to-agent (A2A) Cloud connection for post-race workflows.
https://preview.redd.it/b7k2ewbws8zh1.png?width=2489&format=png&auto=webp&s=cb0454dcf4726e6a164889d90eff93fb8b5f785a
Agentic engineering with Claude Code and Android CLI
Stop copy-pasting into AI chat windows and start delegating to your agent. This practical, example-driven session shows you how to level up your agentic engineering using Claude Code and the Android CLI. We will walk through a complete workflow to automate complex development tasks and ship features faster.
You will learn to:
* Optimize the token efficiency of your harness using Android CLI, Skills, Hooks and MCP.
* Offload and parallelize long-running tasks to subagents.
* Set up continuous verification loops that stop early termination and run until tests pass.
The latest in Android dev tools from Android Dev Summit 2026
Discover what’s next for Android development across Android Studio and the terminal with Android CLI. In this session, we unveil the latest in Android Studio Canary and Stable—from AI-assisted code migrations to Compose and Agent Client Protocol (ACP) support, to Lightbuild’s declarative architecture. We’ll also dive into the latest updates to the Android CLI toolchain. Learn how you can use it to automate your inner-loop workflows with improved access to devices, diagnostics tools for local and production issues, profiling workflows that let your agents test and validate optimizations and much more.
Declarative, agent-ready Android builds with Lightbuild
As Android apps grow and AI coding assistants become essential, using executable code to configure your build can create bottlenecks with slow sync times, fragile logic, and added complexity.
Enter Lightbuild: Google's declarative, config-driven interface to the build engine, designed for modern Android development.
In this session, we'll explore Lightbuild's new approach to managing builds and how to use it to build a demo app. Learn how decoupling build config from execution delivers faster project opens with lightning-fast sync in Android Studio, while offering a predictable schema for safer, more reliable AI editing. We’ll also cover Lightbuild's agent-friendly CLI tools for creating reproducible builds across local machines, teams, and CI/CD pipelines.
Decoding Play Policy AMA
An open and honest panel about Play policies to keep your app compliant and quickly published.
App security in the agentic era
This presentation explores the strategic shift from viewing AI as a generic coding assistant to leveraging it as a context-aware, automated security peer reviewer integrated directly into the Android development lifecycle. We discuss how specialized AI agents, connected to the Android toolchain via skills, can help improve app security. By bridging the gap between raw LLM capabilities and deep project context, this approach empowers development teams to maintain high-velocity feature delivery without compromising rigorous security and policy standards.
Trace me if you can: Automated instrumentation and field profiling
Optimizing Android apps requires deep visibility into concurrent workflows and coroutine suspensions. While local profiling offers a useful snapshot, scaling these insights to production without overhead remains a challenge.
This session delivers an architectural blueprint for a continuous performance feedback loop:
* androidx.tracing 2.0: Swap backends dynamically and propagate coroutine contexts (Perfetto flows) across threads.
* Smart Instrumentation: Use local ART tracing to find hotspots, then automate the injection of low-overhead trace points.
* Macrobenchmarking: Track regressions and verify performance gains on physical devices in CI.
* Field Tracing: Go beyond local and CI tracing, with ProfilingManager.
Type safe keep rules and DEX optimization
Android apps often ship under-optimized due to overly conservative keep rules often from third-party libraries, leading to bloated APKs, slower cold starts, and degraded runtime performance.
With Google Play’s new performance thresholds for DEX optimization, app visibility now directly depends on staying ahead of the optimization curve.
This talk introduces a modern R8 workflow to tackle rule bloat. You will learn to:
* Use the R8 config analyzer and skill to identify legacy rule overhead.
* Transition from broad wildcard keep rules to precise, type-safe, generated annotations.
* Prevent optimization regressions with new Android CLI tools.
Agentic coding: A roundtable with industry leaders
As AI tools rapidly reshape modern software engineering, this panel will explore how developers are leveraging AI-assisted coding, automated agents and specialized developer tooling in their daily workflows. We aim to highlight practical applications, discuss measurable productivity improvements and candidly address the challenges engineering teams face when integrating AI at scale.
Memory troubleshooting with Firebase Crashlytics
Keep your app's memory footprint lean-and-mean and non-segfaulty with Firebase Crashlytics. This session explores our comprehensive suite of memory troubleshooting tools available in the Firebase console and in Android Studio. We’ll start by covering how to leverage ANR insights and GWP-ASan reports to diagnose elusive memory bugs and then dive into our latest tooling for Out-Of-Memory (OOM) and Memory Limiter Kill (MLK) events, designed specifically to help you navigate and adapt to the new memory limits introduced in Android 17.
Navigating multi-device quality & publishing beyond mobile on Google Play
As the Android ecosystem expands across wrists, living rooms, vehicles, and XR, the opportunity to reach users on new screens is growing. However, distributing across Wear OS, Android TV, Android Auto, Android Automotive OS, or Android XR introduces distinct considerations for testing, store listings, and app reviews.
This session explores how to effectively utilize Google Play Console for non-mobile form factors to help streamline a predictable multi-device launch. We will cover key distribution decisions, including how to structure track strategies and package names, configure targeted testing tracks, and tailor store listings. You'll get a practical walkthrough of form-factor App Quality guidelines to help avoid common review pitfalls and publish on Google Play with greater confidence.
Android developer verification: Publishing paths for all developers
Android Developer Verification is crucial for a safer ecosystem. This session breaks down the compliance pathways for all developers, from large studios to hobbyists. We will outline the key requirements for publishing on Google Play and third-party app stores. The talk will feature a live demo of the new Limited Distribution accounts, showing how students and hobbyists can easily and safely share apps.
By the end of this session, you will be able to:
* Understand the 3 main developer verification paths.
* See the new Limited Distribution account flow live.
* Identify your specific next steps for compliance.
Outperform yourself in Compose
Jetpack Compose makes it easy to design high-quality user interfaces, but it can be difficult to track down issues that affect UI performance. These kinds of issues can lead to problems that your users notice, like startup latency, and dropped frames that appear as scroll jank or choppy animations.
In this talk, we’ll introduce tools to uncover what’s impacting your UI’s performance, focusing on Perfetto and (re-)composition tracing. We’ll then explore specific anti-patterns you may be using that are secretly costing you, how you can find them in your code, and what positive patterns you can replace them with. By the end of this talk, you’ll understand how to think in Compose with a performance mindset, and how to profile, analyze, and verify performance optimizations in your app.
Actionable strategies for reducing your app's Bitmap memory footprint
Managing Bitmap memory is critical for mitigating Out-Of-Memory (OOM) risks in visually rich Android apps. While developers know to reduce image sizes, achieving long-term app stability comes from mastering two other key pillars: Reuse and Recycle. This session delivers a practical playbook for optimizing memory performance using modern tools, open-source libraries like Glide and Coil, and system-level APIs.
In this session, you will learn how to diagnose real-world memory regressions using Android Vitals, implement advanced caching (Reuse) patterns with Glide and Coil, and proactively release memory (Recycle) using the onTrimMemory callback.
Insights into agent code generation from Android Bench
Android apps foundationAI models can generate entire features in minutes, but is the code correct? We built Android Bench, our AI evaluation benchmark, to answer this question after analyzing thousands of generated code changes.
This talk shares insights from our journey, including all the ways we saw models cheats, how prompt specificity leads to higher code quality and how different agents approach the same task.
Scale your app for every screen with Compose
The Android ecosystem is vast, with users shifting seamlessly across phones, tablets, foldables, and desktop environments. Now that we are Compose First, this session explores how to architect your app for resizable windows and diverse aspect ratios—where traditional layout assumptions break down, leading to stretched UIs and lost state.
Explore how the latest capabilities in Jetpack Compose, Navigation 3, and WindowManager can help you build dynamic layouts that naturally scale from compact screens to dual-pane displays. Walk away with strategies to accelerate your development workflow using Gemini and our skills, like the adaptive skill, to automatically refactor legacy codebases for larger screens.
Migrating two decades of the Google Play app to Jetpack Compose
This year, Android off