Tag: Google

ADK introduces **Context Engineering** to scale AI agents beyond large context windows. It treats context as a compiled view over a tiered, stateful system (**Session, Memory, Artifacts**). This architecture uses explicit processors for transformation, enables efficient compaction and caching, and allows for strict, scoped context handoffs in multi-agent workflows to ensure reliability and cost-effectiveness in production.

Code Wiki is a new platform that tackles the bottleneck of reading existing code by providing an automated, continuously updated, structured wiki for code repositories. It features hyper-linked documentation, a Gemini-powered chat agent that understands your repo, and automated diagrams. A public preview is available for open-source projects, and a Gemini CLI extension is coming soon for secure use on private repos.

We're excited to announce an enhancement to Gemini CLI that makes your workflow more powerful a...

Introducing the Jules extension for Gemini CLI, an autonomous sidekick for developers. It accelerates coding workflows by offloading tasks like asynchronous work, bug fixes, and changes in new branches to Jules, while you stay in flow with Gemini CLI. Get started by installing the extension and using the /jules command to initiate and check task statuses.

The blog post argues the request-response model fails for advanced multi-agent AI. It advocates for a real-time bidirectional streaming architecture, implemented by the Agent Development Kit (ADK). This streaming model enables true concurrency, natural interruptibility, and unified multimodal processing. ADK's core features are real-time I/O management, stateful sessions for agent handoffs, and streaming-native tools.

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.

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!

The new **User Simulation** feature in the Agent Development Kit (ADK) replaces rigid, brittle manual test scripts with dynamic, LLM-powered conversation generation. Developers define a high-level `conversation_plan`, and the simulator handles the multi-turn interaction to achieve the goal. This dramatically reduces test creation time, builds more resilient tests, and creates a reliable regression suite for AI agents.

Google Colab has launched an official VS Code extension, bridging the gap between the popular code editor and the AI/ML platform. The extension combines VS Code's powerful development environment with Colab's seamless access to high-powered runtimes (GPUs/TPUs), allowing users to connect local notebooks to Colab. This aims to meet developers where they are and brings the best of both worlds.

Metrax is a high-performance JAX-based metrics library developed by Google. It standardizes model evaluation by offering robust, efficient metrics for classification, NLP, and vision, eliminating manual re-implementation after migrating from TensorFlow. Key strengths include parallel computation of "at K" metrics (e.g., PrecisionAtK) for multiple K values and strong integration with the JAX AI Stack, leveraging JAX's performance features. It is open-source on GitHub.