109 results
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.
DEC. 2, 2025 / AI
The new Data Commons extension for the Gemini CLI makes accessing public data easier. It allows users to ask complex, natural-language questions to query Data Commons' public datasets, grounding LLM responses in authoritative sources to reduce AI hallucinations. Data Commons is an organized library of public data from sources like the UN and World Bank. The extension enables instant data analysis, exploration, and integration with other data-related extensions.
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. 13, 2025 / AI
Google has launched the redesigned **Android AI Sample Catalog**, a dedicated, open-source application to inspire and educate Android developers on building AI-powered apps. It showcases examples using both on-device (Gemini Nano via ML Kit GenAI API) and Cloud models (via Firebase AI Logic SDK), including image generation with Imagen, on-device summarization, and a "Chat with Nano Banana" chatbot. The code is easy to copy and paste to help developers quickly start their own projects.
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. 13, 2025 / AI
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.
NOV. 13, 2025 / AI
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.
NOV. 4, 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.
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.
