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  • SEPT. 15, 2026 / AI

    Build zero-trust AI agents that judge intent, not just syntax

    This blog post explores how to transition AI agents from static, build-time security controls to dynamic runtime governance using the Gemini Enterprise Agent Platform. It highlights three primary managed defenses: Model Armor for screening edge prompts, Semantic Governance Policies for evaluating tool intent against business rules, and Agent Anomaly Detection for catching multi-turn exploits. By shifting these capabilities to the platform level, security administrators can dynamically enforce policies and neutralize complex attacks without needing to modify or redeploy the agent's underlying code.

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  • AUG. 17, 2026 / AI

    Build zero-trust AI agents with Google's Agent Development Kit

    Building autonomous AI agents that mutate production state requires moving beyond soft system prompts to a robust zero-trust architecture. To secure Google Agent Development Kit (ADK) workflows against prompt injections and malicious execution, developers must implement hardware-backed cryptographic signatures for database writes, kernel-level sandboxing with gVisor for dynamic code, and deterministic semantic gateways for I/O validation. By enforcing these hard security boundaries at the infrastructure level, you can safely deploy multi-tool AI agents without risking unauthorized data manipulation or server compromise.

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  • 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...

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  • JULY 30, 2025 / Gemini

    Introducing LangExtract: A Gemini powered information extraction library

    LangExtract is a new open-source Python library powered by Gemini models for extracting structured information from unstructured text, offering precise source grounding, reliable structured outputs using controlled generation, optimized long-context extraction, interactive visualization, and flexible LLM backend support.

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  • JULY 10, 2025 / Gemini

    Announcing GenAI Processors: Build powerful and flexible Gemini applications

    GenAI Processors is a new open-source Python library from Google DeepMind designed to simplify the development of AI applications, especially those handling multimodal input and requiring real-time responsiveness, by providing a consistent "Processor" interface for all steps from input handling to model calls and output processing, for seamless chaining and concurrent execution.

    Announcing GenAI Processors: Streamline your Gemini application development
  • JUNE 26, 2025 / AI

    Unlock deeper insights with the new Python client library for Data Commons

    Google has released a new Python client library for Data Commons – an open-source knowledge graph that unifies public statistical data, and enhances how data developers can leverage Data Commons by offering improved features, support for custom instances, and easier access to a vast array of statistical variables – developed with contributions from The ONE Campaign.

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