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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Google Developers Blog</title><link>https://developers.googleblog.com/rss/</link><description>Updates on changes and additions to the Google Developers Blog.</description><atom:link href="https://developers.googleblog.com/feeds/posts/default/" rel="self"/><language>en-us</language><lastBuildDate>Sat, 18 Apr 2026 05:56:27 +0000</lastBuildDate><item><title>A2UI v0.9: The New Standard for Portable, Framework-Agnostic Generative UI</title><link>https://developers.googleblog.com/a2ui-v0-9-generative-ui/</link><description>A2UI v0.9 introduces a framework-agnostic standard designed to help AI agents generate real-time, tailored UI widgets using a company’s existing design system. This update simplifies the developer experience with a new Agent SDK for Python, a shared web-core library, and official support for renderers like React, Flutter, and Angular. By decoupling UI intent from specific platforms, the release enables seamless, low-latency streaming of generative interfaces across web and mobile applications. Integrating with broader ecosystems like AG2 and Vercel, A2UI v0.9 aims to move generative UI from experimental demos to production-ready digital products.</description><guid>https://developers.googleblog.com/a2ui-v0-9-generative-ui/</guid></item><item><title>MaxText Expands Post-Training Capabilities: Introducing SFT and RL on Single-Host TPUs</title><link>https://developers.googleblog.com/maxtext-expands-post-training-capabilities-introducing-sft-and-rl-on-single-host-tpus/</link><description>MaxText has introduced new support for Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) on single-host TPU configurations, leveraging JAX and the Tunix library for high-performance model refinement. These features enable developers to easily adapt pre-trained models for specialized tasks and complex reasoning using efficient algorithms like GRPO and GSPO. This update streamlines the post-training workflow, offering a scalable path from single-host setups to larger multi-host configurations.</description><guid>https://developers.googleblog.com/maxtext-expands-post-training-capabilities-introducing-sft-and-rl-on-single-host-tpus/</guid></item><item><title>New enhancements for merchant initiated transactions with the Google Pay API</title><link>https://developers.googleblog.com/new-enhancements-for-merchant-initiated-transactions-with-the-google-pay-api/</link><description>Google has introduced enhancements to the Google Pay API to provide developers with greater flexibility and control over merchant-initiated transactions (MIT). The update includes new objects within the PaymentDataRequest to specifically handle recurring subscriptions, deferred payments like hotel bookings, and automatic account reloads. By allowing merchants to clearly define future payment terms, these changes improve transparency for users and help reduce transaction declines through better token management. Developers can now implement these features to create more seamless and secure long-term payment experiences.</description><guid>https://developers.googleblog.com/new-enhancements-for-merchant-initiated-transactions-with-the-google-pay-api/</guid></item><item><title>Subagents have arrived in Gemini CLI</title><link>https://developers.googleblog.com/subagents-have-arrived-in-gemini-cli/</link><description>Gemini CLI has introduced subagents, specialized expert agents that handle complex or high-volume tasks in isolated context windows to keep the primary session fast and focused. These agents can be customized via Markdown files, run in parallel to boost productivity, and are easily invoked using the @agent syntax for targeted delegation. This architecture prevents "context rot" by consolidating intricate multi-step executions into concise summaries for the main orchestrator.</description><guid>https://developers.googleblog.com/subagents-have-arrived-in-gemini-cli/</guid></item><item><title>Build Better AI Agents: 5 Developer Tips from the Agent Bake-Off</title><link>https://developers.googleblog.com/build-better-ai-agents-5-developer-tips-from-the-agent-bake-off/</link><description>The Google Cloud AI Agent Bake-Off highlights a shift from simple prompt engineering to rigorous agentic engineering, emphasizing that production-ready AI requires a modular, multi-agent architecture. The post outlines five key developer tips, including decomposing complex tasks into specialized sub-agents and using deterministic code for execution to prevent probabilistic errors. Furthermore, it advises developers to prioritize multimodality and open-source protocols like MCP to ensure agents are scalable, integrated, and future-proof against rapidly evolving model capabilities.</description><guid>https://developers.googleblog.com/build-better-ai-agents-5-developer-tips-from-the-agent-bake-off/</guid></item><item><title>Get ready for Google I/O: Livestream schedule revealed</title><link>https://developers.googleblog.com/get-ready-for-google-io-livestream-schedule-revealed/</link><description>Google I/O returns May 19–20 to showcase major updates in AI, Android, Chrome, and Cloud, beginning with a keynote on the "agentic era" of development. The event will focus on new tools designed to automate complex workflows and simplify the creation of high-quality, AI-ready applications. Attendees can register to access live sessions, technical demos, and professional development resources both live and on-demand.</description><guid>https://developers.googleblog.com/get-ready-for-google-io-livestream-schedule-revealed/</guid></item><item><title>TorchTPU: Running PyTorch Natively on TPUs at Google Scale</title><link>https://developers.googleblog.com/torchtpu-running-pytorch-natively-on-tpus-at-google-scale/</link><description>TorchTPU is a new engineering stack designed to provide a native, high-performance experience for running PyTorch workloads on Google’s TPU infrastructure with minimal code changes. It features an "Eager First" approach with multiple execution modes and utilizes the XLA compiler to optimize distributed training across massive clusters. Moving into 2026, the project aims to further reduce compilation overhead and expand support for dynamic shapes and custom kernels to ensure seamless scalability for the next generation of AI.</description><guid>https://developers.googleblog.com/torchtpu-running-pytorch-natively-on-tpus-at-google-scale/</guid></item><item><title>Supporting Google Account username change in your app</title><link>https://developers.googleblog.com/supporting-google-account-username-change-in-your-app/</link><description>Google has updated its account settings to allow U.S. users to change their @gmail.com usernames while keeping all existing account data and inboxes intact. For developers, this means that while old email addresses will remain active as aliases, apps that rely solely on email addresses for identification may face issues with account duplication or lost access. To ensure a seamless user experience, Google recommends migrating to the "subject ID" as the primary user identifier and allowing users to manually update their contact information within app settings.</description><guid>https://developers.googleblog.com/supporting-google-account-username-change-in-your-app/</guid></item><item><title>Bring state-of-the-art agentic skills to the edge with Gemma 4</title><link>https://developers.googleblog.com/bring-state-of-the-art-agentic-skills-to-the-edge-with-gemma-4/</link><description>Google DeepMind has launched Gemma 4, a family of state-of-the-art open models designed to enable multi-step planning and autonomous agentic workflows directly on-device. The release includes the Google AI Edge Gallery for experimenting with "Agent Skills" and the LiteRT-LM library, which offers a significant speed boost and structured output for developers. Available under an Apache 2.0 license, Gemma 4 supports over 140 languages and is compatible with a wide range of hardware, including mobile devices, desktops, and IoT platforms like Raspberry Pi.</description><guid>https://developers.googleblog.com/bring-state-of-the-art-agentic-skills-to-the-edge-with-gemma-4/</guid></item><item><title>Developer’s Guide to Building ADK Agents with Skills</title><link>https://developers.googleblog.com/developers-guide-to-building-adk-agents-with-skills/</link><description>The Agent Development Kit (ADK) SkillToolset introduces a "progressive disclosure" architecture that allows AI agents to load domain expertise on demand, reducing token usage by up to 90% compared to traditional monolithic prompts. Through four distinct patterns—ranging from simple inline checklists to "skill factories" where agents write their own code—the system enables agents to dynamically expand their capabilities at runtime using the universal agentskills.io specification. This modular approach ensures that complex instructions and external resources are only accessed when relevant, creating a scalable and self-extending framework for modern AI development.</description><guid>https://developers.googleblog.com/developers-guide-to-building-adk-agents-with-skills/</guid></item><item><title>ADK Go 1.0 Arrives!</title><link>https://developers.googleblog.com/adk-go-10-arrives/</link><description>The launch of Agent Development Kit (ADK) for Go 1.0 marks a significant shift from experimental AI scripts to production-ready services by prioritizing observability, security, and extensibility. Key updates include native OpenTelemetry integration for deep tracing, a new plugin system for self-healing logic, and "Human-in-the-Loop" confirmations to ensure safety during sensitive operations. Additionally, the release introduces YAML-based configurations for rapid iteration and refined Agent2Agent (A2A) protocols to support seamless communication across different programming languages. This framework empowers developers to build complex, reliable multi-agent systems using the high-performance engineering standards of Golang.</description><guid>https://developers.googleblog.com/adk-go-10-arrives/</guid></item><item><title>Boost Training Goodput: How Continuous Checkpointing Optimizes Reliability in Orbax and MaxText</title><link>https://developers.googleblog.com/boost-training-goodput-how-continuous-checkpointing-optimizes-reliability-in-orbax-and-maxtext/</link><description>The newly introduced continuous checkpointing feature in Orbax and MaxText is designed to optimize the balance between reliability and performance during model training, addressing issues with conventional fixed-frequency checkpointing. Unlike fixed intervals—which can either compromise reliability or bottleneck performance—continuous checkpointing maximizes I/O bandwidth and minimizes failure risk by asynchronously initiating a new save operation only after the previous one successfully completes. Benchmarks demonstrate that this approach significantly reduces checkpoint intervals and results in substantial resource conservation, especially in large-scale training jobs where mean-time-between-failure (MTBF) is short.</description><guid>https://developers.googleblog.com/boost-training-goodput-how-continuous-checkpointing-optimizes-reliability-in-orbax-and-maxtext/</guid></item><item><title>Announcing ADK for Java 1.0.0: Building the Future of AI Agents in Java</title><link>https://developers.googleblog.com/announcing-adk-for-java-100-building-the-future-of-ai-agents-in-java/</link><description>Google has released version 1.0.0 of the Agent Development Kit (ADK) for Java, introducing powerful new features like Google Maps grounding, built-in URL fetching, and a standardized Agent2Agent protocol for cross-framework collaboration. The update enhances agent control through a new "App" and "Plugin" architecture, which allows for global logging, automated context window management via event compaction, and "Human-in-the-Loop" workflows for action confirmations. Additionally, the release provides robust session and memory services using Google Cloud integrations like Firestore and Vertex AI to manage long-term state and large data artifacts.</description><guid>https://developers.googleblog.com/announcing-adk-for-java-100-building-the-future-of-ai-agents-in-java/</guid></item><item><title>Closing the knowledge gap with agent skills</title><link>https://developers.googleblog.com/closing-the-knowledge-gap-with-agent-skills/</link><description>To bridge the gap between static model knowledge and rapidly evolving software practices, Google DeepMind developed a "Gemini API developer skill" that provides agents with live documentation and SDK guidance. Evaluation results show a massive performance boost, with the gemini-3.1-pro-preview model jumping from a 28.2% to a 96.6% success rate when equipped with the skill. This lightweight approach demonstrates how giving models strong reasoning capabilities and access to a "source of truth" can effectively eliminate outdated coding patterns.</description><guid>https://developers.googleblog.com/closing-the-knowledge-gap-with-agent-skills/</guid></item><item><title>Jump to play: Building with Gemini &amp; MediaPipe</title><link>https://developers.googleblog.com/jump-to-play-building-with-gemini-mediapipe/</link><description>The provided workflow streamlines motion-controlled game development by using Gemini Canvas to rapidly prototype mechanics like the MediaPipe Pose Landmarker through high-level prompting. Developers can refine these prototypes in Google AI Studio by optimizing for low-latency "lite" models and stable tracking points, such as shoulder landmarks, to ensure responsive gameplay. The process concludes by using Gemini Code Assist to refactor experimental code into a modular, production-ready application capable of supporting various multimodal inputs.</description><guid>https://developers.googleblog.com/jump-to-play-building-with-gemini-mediapipe/</guid></item><item><title>Build a smart financial assistant with LlamaParse and Gemini 3.1</title><link>https://developers.googleblog.com/build-a-smart-financial-assistant-with-llamaparse-and-gemini-31/</link><description>This blog post introduces a workflow for extracting high-quality data from complex, unstructured documents by combining LlamaParse with Gemini 3.1 models. It demonstrates an event-driven architecture that uses Gemini 3.1 Pro for agentic parsing of dense financial tables and Gemini 3.1 Flash for cost-effective summarization. By following the provided tutorial, developers can build a personal finance assistant capable of transforming messy brokerage statements into structured, human-readable insights.</description><guid>https://developers.googleblog.com/build-a-smart-financial-assistant-with-llamaparse-and-gemini-31/</guid></item><item><title>Developer’s Guide to AI Agent Protocols</title><link>https://developers.googleblog.com/developers-guide-to-ai-agent-protocols/</link><description>This blog post introduces a suite of six protocols, such as MCP and A2A, designed to eliminate custom integration code by standardizing how AI agents access data and communicate. Using a "kitchen manager" agent as a practical example, it demonstrates how these tools handle complex tasks like real-time inventory checks, wholesale commerce via UCP, and secure payment authorization through AP2. By leveraging the Agent Development Kit (ADK), developers can also implement A2UI and AG-UI to deliver interactive dashboards and seamless streaming interfaces to users.</description><guid>https://developers.googleblog.com/developers-guide-to-ai-agent-protocols/</guid></item><item><title>Announcing the Colab MCP Server: Connect Any AI Agent to Google Colab</title><link>https://developers.googleblog.com/announcing-the-colab-mcp-server-connect-any-ai-agent-to-google-colab/</link><description>When you’re prototyping locally with AI agents like Gemini CLI, Claude Code, or your own agent, thei...</description><guid>https://developers.googleblog.com/announcing-the-colab-mcp-server-connect-any-ai-agent-to-google-colab/</guid></item><item><title>Plan mode is now available in Gemini CLI</title><link>https://developers.googleblog.com/plan-mode-now-available-in-gemini-cli/</link><description>Gemini CLI now features Plan Mode, a read-only environment that allows the AI to analyze complex codebases and map out architectural changes without the risk of accidental execution. By leveraging the new ask_user tool and expanded Model Context Protocol (MCP) support, developers can collaboratively refine strategies and pull in external data before committing to implementation.</description><guid>https://developers.googleblog.com/plan-mode-now-available-in-gemini-cli/</guid></item><item><title>Unleash Your Development Superpowers: Refining the Core Coding Experience</title><link>https://developers.googleblog.com/unleash-your-development-superpowers-refining-the-core-coding-experience/</link><description>The Gemini Code Assist team has introduced a suite of updates focused on streamlining the core coding workflow through high-velocity tools like Agent Mode with Auto Approve and Inline Diff Views. These enhancements, along with new features for precise context management and custom commands, aim to transform the AI from a general assistant into a highly tailored, seamless collaborator that adapts to your specific development style.</description><guid>https://developers.googleblog.com/unleash-your-development-superpowers-refining-the-core-coding-experience/</guid></item></channel></rss>