53 results
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.
DEC. 4, 2025 / AI
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.
NOV. 25, 2025 / AI
Gemini 3 is available via API with updates for developers: new `thinking_level` for depth control, `media_resolution` for multimodal processing, and enforced `Thought Signatures` for agentic workflows, especially with function calling and image generation. It also introduces combining Google Search/URL Grounding with Structured Outputs and new usage-based pricing for Grounding. Best practices, like using default temperature, are advised for optimal results.
NOV. 19, 2025 / AI
Gemini 3 Pro Preview is introduced as a powerful, agentic model for complex, (semi)-autonomous workflows. New agentic features include `thinking_level` for reasoning control, Stateful Tool Use via Thought Signatures, and `media_resolution` for multimodal fidelity. It has Day 0 support for open-source frameworks like LangChain, AI SDK, LlamaIndex, Pydantic AI, and n8n. Best practices include simplifying prompts and keeping temperature at 1.0.
NOV. 19, 2025 / AI
Jules, an always-on, multi-step software development agent, now features Gemini 3, offering clearer reasoning and better reliability. Recent improvements include parallel CLI runs, a stable API, and safer Git handling. Upcoming features include directory attachment without GitHub and automatic PR creation. Jules aims to reduce software writing overhead so developers can focus on building.
NOV. 13, 2025 / AI
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.
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!
NOV. 7, 2025 / AI
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.
OCT. 30, 2025 / AI
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.
