How Google Uses HTML

Distributed AI training is notoriously fragile because losing a single machine typically crashes the entire multi-node job, forcing a time-consuming, full-workload infrastructure restart. To address this, Google’s JAX ecosystem utilizes elastic training via Pathways, which converts a hardware failure into a catchable Python exception so the running process can survive. When an unplanned failure occurs, the system automatically replaces only the broken worker, restores the last viable checkpoint from Cloud Storage, and resumes training in place—minimizing total downtime to under two minutes without ever restarting the main controller process.

This post introduces three architectural patterns designed to integrate Model Context Protocol (MCP) Apps and Agent-to-User Interface (A2UI) to solve the tradeoff between highly custom iframe environments and native, declarative rendering. By combining these approaches, developers can serve native-feeling UIs directly over MCP servers, embed complex and stateful iframe apps securely inside declarative views, or inject generative UI components into legacy systems. Ultimately, these hybrid frameworks empower engineering teams to deliver secure, performant, and brand-consistent agentic user experiences tailored to their specific project constraints.

Google announced the transition from assistive AI to independent agents, highlighting the launch of the Gemini 3.5 series and major updates to its Antigravity agent-first development platform. For mobile developers, the post introduces new Android CLI tools, the Android Bench evaluation leaderboard, and an automated Migration agent designed to rapidly convert various frameworks into native Kotlin code. Web development is also being transformed through Chrome DevTools for agents, the HTML-in-Canvas API, and the proposal of WebMCP, an open web standard that enables browser-based AI agents to execute complex tasks.

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.

The article discusses the advancements in agentic AI with Gemini 3, emphasizing its role as a core orchestrator for complex workflows.

The article introduces A2UI, an open-source project designed for agent-driven interfaces that allows agents to generate contextually relevant user interfaces.

The article discusses the integration of Gemini 3 Pro into Gemini CLI, highlighting its capabilities to enhance productivity and performance in terminal operations.

The article announces the general availability of the URL context tool for the Gemini API, highlighting its new features that allow developers to provide URLs for context instead of manual content ...

LangExtract is an open-source Python library powered by Gemini, designed to facilitate the extraction of structured information from unstructured text.

The article discusses the development of a research prototype that simulates a neural operating system using Gemini 2. 5 Flash-Lite.

The article discusses how to implement Google Pay within a sandboxed iframe to ensure compliance with PCI DSS v4 requirements.

The Google I/O 2025 Developer keynote highlighted innovations across Google platforms, focusing on the integration of AI models from Google DeepMind.

The article explores the multimodal capabilities of Gemini, showcasing its ability to understand and process images and videos through various real-world applications.

The article discusses the enhancements and features of the Google Wallet API announced at Google I/O 2024, focusing on security, wearables, push notifications, and developer experience.

The article explores the development of ShiffBot, an AI-powered tool designed to enhance the coding learning experience using the Gemini API.

This article explores the capabilities of Gemini, a multimodal AI model, through various interactive experiments that combine image and text prompts.

This article commemorates 25 years of Google Search, highlighting its impact on developer trends and the evolution of web, mobile, cloud, and AI technologies.

The Google Dev Library Newsletter: 20th Edition highlights innovative projects developed using Google technologies, showcasing contributions to the Google Dev Library platform.

The article discusses how App Engine users can leverage Cloud Functions to modernize their applications by refactoring monolithic apps into microservices.

This article provides a comprehensive guide on integrating App Engine push queues into Flask applications.

The article discusses deploying a single application across three Google Cloud serverless platforms: App Engine, Cloud Functions, and Cloud Run.

The article discusses the modernization of Google App Engine applications, highlighting the evolution of the platform since its launch in 2008.