Tag: Google

Gemini CLI now features Plan Mode, a read-only environment that allows the AI to analyze complex codebases and map out architectural changes without the risk of accidental execution. By leveraging the new ask_user tool and expanded Model Context Protocol (MCP) support, developers can collaboratively refine strategies and pull in external data before committing to implementation.

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.

New Gemini CLI hooks (v0.26.0+) let you tailor the agentic loop. Add context, enforce policies, and block secrets with custom scripts that run at predefined points in your workflow.

LiteRT, the evolution of TFLite, is now the universal framework for on-device AI. It delivers up to 1.4x faster GPU, new NPU support, and streamlined GenAI deployment for models like Gemma.

At Thunderhill Raceway Park, a team of Google Developer Experts (GDEs) put a new "Trustable AI Framework" to the test. Here is how they used GCP, Gemini and Antigravity to turn high-velocity racing into a masterclass for agentic architecture.

Finetuning the FunctionGemma model is made fast and easy using the lightweight JAX-based Tunix library on Google TPUs, a process demonstrated here using LoRA for supervised finetuning. This approach delivers significant accuracy improvements with high TPU efficiency, culminating in a model ready for deployment.

Google is launching the Developer Knowledge API and MCP Server in public preview. This new toolset provides a canonical, machine-readable way for AI assistants and agentic platforms to search and retrieve up-to-date documentation across Firebase, Google Cloud, Android, and more. By using the official MCP server, developers can connect tools directly to Google’s documentation corpus, ensuring that AI-generated code and guidance are based on authoritative, real-time context.

Data Commons has launched a free, hosted Model Context Protocol (MCP) service on Google Cloud Platform, eliminating the need for users to manage complex local server installations. This update simplifies connecting AI agents and the Gemini CLI to Data Commons, allowing Google to handle security, updates, and resource management while users query data natively.

To simplify the user experience and prevent startup failures, the Gemini CLI has introduced structured extension settings that eliminate the need for manual environment variable configuration. This update enables extensions to automatically prompt users for required details during installation and securely stores sensitive information, such as API keys, directly in the system keychain. Users can now easily manage and override these configurations globally or per project using the new Gemini extensions config command.

Google I/O returns May 19-20. Watch the livestreams for updates on Android, AI, Chrome, and Cloud. Registration is open on the Google I/O website.