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Conductor Update: Introducing Automated Reviews
Conductor for the Gemini CLI has introduced a new Automated Review feature designed to verify the quality and accuracy of AI-generated code. This update addresses the challenge of validating agentic development by automatically checking implementations against original plans, enforcing style guides, and identifying security risks or bugs. by incorporating test-suite validation and providing actionable reports, Conductor helps developers ensure that their AI agents deliver safe, predictable, and architecturally sound code before it is finalized.
Real-World Agent Examples with Gemini 3
Gemini 3 is powering the next generation of reliable, production-ready AI agents. This post highlights 6 open-source framework collaborations (ADK, Agno, Browser Use, Eigent, Letta, mem0), demonstrating practical agentic workflows for tasks like deep search, multi-agent systems, browser and enterprise automation, and stateful agents with advanced memory. Clone the examples and start building today.
Pick up exactly where you left off with Session Management in Gemini CLI
Gemini CLI's new automatic **Session Management** (v0.20.0+) saves your conversation history, tool outputs, and reasoning, providing project-specific context. Resume easily using the **Interactive Session Browser** (`/resume`) or command-line flags (`--resume`). This feature ensures you never lose your work state, capturing prompts, tool execution details, and usage stats. Customize history with cleanup policies in `settings.json`.
Building agents with the ADK and the new Interactions API
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.
Introducing A2UI: An open project for agent-driven interfaces
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.
Developer’s guide to multi-agent patterns in ADK
Learn how to build modular and reliable agentic applications using 8 effective multi-agent design patterns with the Agent Development Kit (ADK).
Introducing Agent Development Kit for TypeScript: Build AI Agents with the Power of a Code-First Approach
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.
Conductor: Introducing context-driven development for Gemini CLI
Conductor is a new Gemini CLI extension that promotes context-driven development. It shifts project context from chat logs to persistent Markdown files for formal specs and plans, ensuring AI agents adhere to project goals, style, and tech stack. This structured workflow is great for "brownfield" projects and teams, allowing for safe iteration and consistent code contributions while keeping the human developer in control.
Gemini 3 Flash is now available in Gemini CLI
Gemini 3 Flash is now available in Gemini CLI. It delivers Pro-grade coding performance with low latency and a lower cost, matching Gemini 3 Pro's SWE-bench Verified score of 76%. It significantly outperforms 2.5 Pro, improving auto-routing and agentic coding. It's ideal for high-frequency development tasks, handling complex code generation, large context windows (like processing 1,000 comment pull requests), and generating load-testing scripts quickly and reliably.
A Developer's Guide to Debugging JAX on Cloud TPUs: Essential Tools and Techniques
A practical guide to debugging and profiling JAX on Cloud TPUs. It outlines core components (libtpu, JAX/jaxlib) and essential techniques. Tools covered include: Verbose Logging (via libtpu env vars), TPU Monitoring Library for performance metrics, tpu-info for real-time utilization, XLA HLO Dumps for compiler debugging, and the XProf suite for in-depth performance analysis.