Search

64 results

Clear filters
  • AUG. 4, 2026 / AI

    A unified API for AI model routing

    Google Cloud API Gateway now offers a model routing feature in Public Preview, allowing developers to dynamically route traffic to models like Gemini, Claude, or OpenAI OSS-GPT without hardcoding endpoints or managing open-source proxies. Developers can easily configure these routing rules directly within their OpenAPI 3.x specifications by mapping virtual model names to specific backend targets on a shared host. Once deployed, the Gateway acts as a serverless ingress layer that accepts standard OpenAI-compatible requests, automatically transcodes the payload to the native schema of the target model, and routes the traffic on the fly.

    Model Routing via API Gateway _ Header
  • AUG. 3, 2026 / AI

    Scaling real-time AI agents with session-aware load balancing

    Real-time AI agents break traditional request-response load balancing paradigms because they rely on long-lived, stateful bidirectional streams that obscure true server capacity. To solve this, developers must implement application-level session tracking directly within the runtime to accurately measure the committed concurrent workload of active conversations. By feeding these precise session counts alongside standard CPU utilization metrics into a hybrid routing algorithm, infrastructure can effectively distribute stateful AI traffic and prevent individual backend bottlenecks.

    Ai-1-banner (8)
  • JULY 16, 2026 / AI

    Building scalable AI agents with modular prompt transpilation

    To resolve the scaling bottlenecks and runtime errors caused by monolithic system prompts, engineering teams should treat prompts as build artifacts by modularizing instructions into reusable templates. By running these modular "skill files" through a transpiler, developers can enforce static validation, catch missing dependencies at build time, and integrate prompt generation directly into their CI/CD pipelines. This deterministic approach prevents code drift and ultimately establishes a safe framework where agents can propose updates to their own logic via standard pull requests.

    Agent Development Kit: Making it easy to build multi-agent applications
  • JULY 1, 2026 / AI

    Why we built ADK 2.0

    Answering the questions of "why we built ADK 2.0". This explains the rationale, some of the features, and why a developer should consider upgrading. This will be published the day after ADK go 2.0 launches.

    gfd-why-adk2-banner
  • JUNE 22, 2026 / AI

    Build Cross-Language Multi-Agent Team with Google’s Agent Development Kit and A2A

    How a Python agent and a Go agent collaborate on contract compliance using the Agent2Agent protocolY...

    banner
  • JUNE 17, 2026 / Web

    A2UI + MCP Apps: Combining the best of declarative and custom agentic UIs

    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.

    header
  • JUNE 16, 2026 / Mobile

    Enhance Security and Trust: New Session Metadata in Sign in with Google

    Google is enhancing Sign in with Google by introducing new OIDC standard claims—specifically auth_time and amr (Authentication Methods Reference) to provide developers with deeper session metadata. These updates allow verified apps to verify the "freshness" of a user's login and the specific authentication methods used (such as MFA or hardware keys), enabling more dynamic, risk-based access controls. By leveraging these federated identity signals, platforms can better prevent account takeover and fraud while implementing granular security policies like step-up authentication for sensitive actions.

    Usability and Safety Updates to Google Auth Platform
  • MAY 26, 2026 / Google Pay

    Enhancing Android Checkout with Dynamic Callbacks in Google Pay

    We are excited to bring Express checkout with Google Pay for Android native apps enabling developers...

    64hUBg8v5KEHEW6 (2)
  • MAY 14, 2026 / Mobile

    Accelerating on-device AI: A look at Arm and Google AI Edge optimization

    Integration of Arm Scalable Matrix Extension 2 (SME2) and the Google AI Edge software stack enables high-performance, on-device generative AI by turning the CPU into a powerful matrix-compute accelerator. Using Stability AI’s "stable-audio-open-small" model as a case study, it outlines a streamlined "Convert, Optimize, and Deploy" pipeline that utilizes LiteRT, XNNPACK, and KleidiAI to automate hardware acceleration. The resulting implementation achieves over a 2x speedup in audio generation and a 4x reduction in memory usage while maintaining high audio quality on Arm-powered mobile devices and laptops.

    ARM Audio
  • MAY 12, 2026 / AI

    Build Long-running AI agents that pause, resume, and never lose context with ADK

    How to transition from stateless chatbots to production-grade agents capable of managing long-running enterprise workflows, such as HR onboarding, that span days or weeks. It introduces the Agent Development Kit (ADK) and its architectural shifts, specifically using durable state machines and persistent session storage to ensure an agent never loses context during "idle time" or server restarts. By leveraging event-driven webhooks and multi-agent delegation, the tutorial demonstrates how to build resilient systems that "sleep" during pauses and wake up to resume complex tasks with high reasoning accuracy.

    Long-running-agent-banner