46 results
JUNE 30, 2026 / AI
Building AI agents often leaves developers uncertain if prompt tweaks to fix single errors will accidentally cause widespread regressions in production. To bridge this gap, Google has introduced a new developer skill for coding agents that automates a five-stage evaluation flywheel: preparing data, running inference, grading with adaptive AutoRaters, analyzing failure clusters, and executing targeted optimizations. Running continuously against production traffic or on-demand via synthetic scenarios, this tool allows developers to describe testing goals in plain language while an independent evaluation service safely validates and counts actual performance improvements.
JUNE 17, 2026 / Web
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.
MAY 4, 2026 / AI
Researchers at UCSD have successfully implemented DFlash, a block-diffusion speculative decoding method, on Google TPUs to bypass the sequential bottlenecks of traditional autoregressive drafting. By "painting" entire blocks of candidate tokens in a single forward pass rather than predicting them one-by-one, the system achieved average speedups of 3.13x, with peak performance nearly doubling that of existing methods like EAGLE-3. This open-source integration into the vLLM ecosystem optimizes TPU hardware by leveraging "free" parallel verification and high-quality draft predictions for complex reasoning tasks.
DEC. 17, 2025 / AI
Introducing the Agent Development Kit (ADK) for TypeScript, an open-source framework for building complex, multi-agent AI systems with a code-first approach. Developers can define agent logic in TypeScript, applying traditional software development best practices (version control, testing). ADK offers end-to-end type safety, modularity, and deployment-agnostic functionality, leveraging the familiar TypeScript/JavaScript ecosystem.
DEC. 15, 2025 / Mobile
A2UI is an open-source project for agent-driven, cross-platform, and generative UI. It provides a secure, declarative data format for agents to compose bespoke interfaces from a trusted component catalog, allowing for native styling and incremental updates. Designed for the multi-agent mesh (A2A), it offers a framework-agnostic solution to safely render remote agent UIs, with integrations in AG UI, Flutter's GenUI SDK, Opal, and Gemini Enterprise.
DEC. 11, 2025 / AI
The new Gemini Interactions API enables stateful, multi-turn AI agent workflows, providing a single interface for raw models and the Gemini Deep Research Agent. It can be integrated with existing ADK systems as a superior inference engine with simplified state management, or used as a transparent remote A2A agent via InteractionsApiTransport, allowing seamless expansion of multi-agent systems with minimal refactoring.
DEC. 9, 2025 / AI
Google Cloud enables end-to-end confidential applications, protecting sensitive data 'in-use' with hardware isolation. The solution combines Confidential Space (TEE/attestation), Oak Functions (private sandbox), and Oak Session (attested end-to-end encryption for scale). This framework anchors user trust in open-source components, proving confidentiality for sensitive workloads like proprietary GenAI models, even when running behind untrusted load balancers.
NOV. 20, 2025 / AI
Introducing Google Antigravity, a new agentic development platform for orchestrating code. It combines an AI-powered Editor View with a Manager Surface to deploy agents that autonomously plan, execute, and verify complex tasks across your editor, terminal, and browser. Agents communicate progress via Artifacts (screenshots, recordings) for easy verification. Available now in public preview.
NOV. 7, 2025 / AI
Agent Garden is now available to all users to simplify AI agent creation and deployment using the Agent Development Kit (ADK). It provides curated agent samples, one-click deployment via Agent Starter Pack, and customization through Firebase Studio. It helps developers with complex business challenges and multi-agent workflows, with Renault Group cited as an early success story.
NOV. 7, 2025 / AI
The Agent Development Kit (ADK), an open-source, code-first toolkit for building powerful and sophisticated AI agents, now supports Go. ADK moves LLM orchestration and agent behavior directly into your code, giving you robust debugging, versioning, and deployment freedom. ADK for Go is idiomatic and performant, leveraging Go's strengths, and includes support for over 30+ databases and the Agent-to-Agent (A2A) protocol for collaborative multi-agent systems. Start building today!
