Google just integrated computer use directly into its mainstream Gemini 3.5 Flash model, doing away with the standalone Gemini 2.5 experimental setup. Developers can now build agents that observe and act across browser, mobile, and desktop environments out of the box, backed by new prompt injection safeguards and optional approval gates. It gives Google a fast, production-ready competitor in the automated workflow race.
Google just introduced Agentic RAG for its Gemini Enterprise Agent Platform, ditching the single-step retrieval approach. A specialized Sufficient Context Agent evaluates draft answers, spots missing details, and runs targeted follow-up queries, driving a 34% jump in factual accuracy with almost zero added latency.
Google just made Gemini 3.1 Flash-Lite generally available on its Enterprise Agent Platform, pitching it as the fastest and most cost-effective model in the Gemini 3 lineup. The lightweight model is built for high-throughput agent workflows like live coding and customer support—with early adopter Gladly seeing 60% lower costs and 1.8-second p95 latency. Why it matters: multi-agent automation is finally getting cheap and fast enough to run in real time.
Google just made Gemini Embedding 2 generally available via the Gemini API. The natively multimodal embedding model can search and reason across text, images, video, and audio in a single pipeline, helping developers move complex multimodal search and analysis projects straight into production.
