# Gemini Published articles for Gemini. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## \[Aug 2026\] AI Community -- Activity Highlights and Achievements DevFeed: [\[Aug 2026\] AI Community -- Activity Highlights and Achievements]() Original publisher: [Read original article]() Author: Nari Yoon Published: 2026-09-17T05:12:15Z Content type: article Language: en Sources: [Google Developer Experts - Medium]() Topics: [Google AI](), [Google](), [google-antigravity](), [Artificial Intelligence](), [MCP Server](), [computer-use](), [Fine-tuning]() Tags: [2026](), [agentic-ai](), [ai](), [ai-coding-agents](), [ai-studio](), [antigravity](), [api](), [automation](), [community](), [computer-use](), [gemini](), [google](), [google-ai](), [google-cloud](), [mcp](), [mcp-server](), [multi-agent](), [ocr](), [paper](), [pitfalls]() ### AI overview A monthly roundup of Google AI community activities and achievements, covering Antigravity prototyping and engineering, AI coding agents, MCP-based remote control, computer-use agent orchestration, earthquake research, and TPU fine-tuning and migration guidance. ### Source excerpt We love sharing the accomplishments of the Google AI communities over the month. We appreciate all the hard work and dedication of our community members. Without further ado, here are the key highlights by products! Agentic DevelopmentAntigravityPrototype App: OCR and Text Extraction by the author Prototyping and Bringing Ideas to Application Using Google AI Studio and Antigravity 2.0 by AI GDE Joan Santoso (Indonesia) shares a rapid prototyping workflow building an AI-powered Form Extractor using the Gemini API, featuring a lightweight OCR and text extraction workflow. Antigravity Engineering Series by GDE Amulya Bhatia (Germany) focuses on key features of Antigravity 2.0 across 10 articles covering topics such as multi-agent orchestration, safety architecture, and workflow automation, accompanied by source code examples. (image soruce) Remote Control for Google Antigravity: Drive Your AI Coding Agent From Telegram 🛰 by GDE Nicola Guglielmi (Italy) introduces an open-source MCP server that turns Telegram into a remote control surface for AI coding agents. Before the Quake: How Antigravity CLI's AI Agents & IoT Data Predict Earthquakes by GDE Kanshi Tanaike (Japan) introduces the paper establishing Unified LAIC-AGW Theory by integrating ultra-dense IoT weather data with seismic moment tensors. It demonstrates a pre-seismic early warning capability by capturing enthalpy anomalies and acoustic-gravity waves. ADKAI GDE Henry Ruiz (US) and AI GDE Margaret Maynard-Reid (US) AI GDE Henry Ruiz (US) and AI GDE Margaret Maynard-Reid (US) introduced UISurf: An Operator-Centric Multi-Agent Platform for Observable and Cross-Environment UI Automation at the Agentic AI Summit 2026. They highlighted how the model-agnostic framework leverages the Google Cloud and Gemini ecosystems, such as GEAP and ADK, to orchestrate and evaluate computer-use agents across web, desktop, and mobile environments. Frameworks and ResearchTPU Introduction to SFT on TPU with Tunix -- 10 pitfalls until 2 ## Agent Anomaly Detection, now in Private Preview on the Gemini Enterprise Agent Platform DevFeed: [Agent Anomaly Detection, now in Private Preview on the Gemini Enterprise Agent Platform]() Original publisher: [Read original article]() Author: Achuth Narayan Rajagopal Published: 2026-09-17T01:25:27.608736Z Content type: release Language: en Sources: [Google Developers Blog]() Topics: [agent observability](), [OpenTelemetry](), [Security](), [Traces](), [API]() Tags: [agent](), [anomaly-detection](), [api](), [autonomous-agents](), [gemini](), [opentelemetry](), [security]() ### AI overview Google announces Agent Anomaly Detection in private preview on the Gemini Enterprise Agent Platform. The feature analyzes agents' reasoning traces, tool calls, logs, and execution flows to identify behavioral anomalies, suspicious intent, and policy violations. ### Source excerpt Agent Anomaly Detection is a new, out-of-band oversight layer for the Gemini Enterprise Agent Platform that analyzes OpenTelemetry traces and tool calls to catch behavioral risks without adding runtime latency to live requests. It utilizes a multi-tiered detection pipeline--combining lightweight statistical scanning with deep LLM-based reasoning--to identify logical anomalies and policy violations grounded in the OWASP Agentic Top 10. Developers can triage these automated findings within Security Command Center or leverage the exposed API to programmatically block subsequent tool calls when an agent breaches defined risk thresholds. ## BotHub выпустил полноценное приложение для ПК DevFeed: [BotHub выпустил полноценное приложение для ПК]() Original publisher: [Read original article]() Author: DashaPasha (BotHub) Published: 2026-09-16T14:21:39Z Content type: news Language: ru Sources: [Tagir Valeev]() Topics: [Electron](), [Linux](), [macOS](), [Windows]() Tags: [bothub](), [bothub-6fb4765299a5](), [chatgpt](), [claude](), [electron](), [gemini](), [linux](), [macos](), [tag-13e2af703774](), [tag-602ac1ff1e95](), [tag-61cd5a476b1d](), [tag-d027108afc56](), [vpn-3362efe1967b](), [windows]() ### AI overview BotHub has released a desktop application for Windows, macOS, and Linux. Built with Electron, it provides access to the platform's AI models and chats in a standalone window, and includes a screen-recording protection feature that hides the app's content during screen sharing. ### Source excerpt BotHub -- платформа для работы с сотнями ИИ-моделей. В одном интерфейсе доступны ChatGPT, Claude, Gemini, Grok, DeepSeek, генераторы изображений, видео и другие модели. Для использования не нужно оформлять отдельную подписку на каждый сервис: BotHub работает с оплатой по фактическому использованию. Также сервис позволяет пользоваться доступными моделями без VPN. Теперь BotHub можно установить как полноценное десктопное приложение для Windows, macOS и Linux. Это отдельный клиент на Electron, который запускается как обычная программа и находится под рукой независимо от открытых сайтов. Главное преимущество такого формата -- удобство при постоянной работе с ИИ. Не нужно держать ещё одну вкладку среди десятков других: BotHub открывается отдельным окном, а доступ ко всем моделям и чатам остаётся в одном месте. Есть и ещё одна полезная функция -- защита от записи экрана. При демонстрации экрана содержимое приложения скрывается, поэтому переписку с нейросетью не увидят участники созвона или зрители трансляции. Эта возможность доступна именно в десктопной версии. Платформа превращается в отдельное рабочее пространство для ИИ. Потестить можно здесь, читателям Хабра, кстати, дают 300 бесплатных капсов. Скачать приложение BotHub для ПК Читать далее ## Google introduces Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking DevFeed: [Google introduces Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking]() Original publisher: [Read original article]() Author: techno\_mot (Selectel) Published: 2026-09-16T13:40:43Z Content type: news Language: ru Sources: [Tagir Valeev]() Topics: [Google](), [speech-to-speech](), [Google AI](), [Artificial Intelligence](), [API]() Tags: [ai](), [api](), [audio](), [gemini](), [google](), [llm](), [realtime](), [selectel](), [speech-to-speech](), [synthid](), [tag-efc6fa45f1fe](), [voice]() ### AI overview Google introduced two native speech-to-speech models: Gemini 3.8 Live, focused on scale and cost, and Gemini 3.8 Live Extended Thinking, designed for multi-step tasks with reasoning during dialogue. The article discusses direct audio processing, asynchronous function calls, visual context, multilingual conversations, SynthID watermarking, pricing, and availability through the Gemini API and Google AI Studio. ### Source excerpt 15 сентября Google представила две нативные speech-to-speech модели, Gemini 3.8 Live и Gemini 3.8 Live Extended Thinking. Первая заточена под масштаб и цену, вторая -- под многошаговые задачи с рассуждением прямо в диалоге. Интереснее баллов то, что голосовые агенты наконец получили признаки продакшен-продукта. Асинхронные вызовы функций, предсказуемая цена, интеграции с тем, на чем такие системы реально собирают. Хочу напомнить, как это делалось раньше. Голосовой бот -- конвейер из трех сервисов. Распознавание речи, языковая модель и синтез. Задержки складываются, а вместе с текстом может потеряться все остальное -- интонация, скорость речи, эмоция, шум на фоне. Модель получает расшифровку и не знает, что собеседник злится. Проблемным было и перебивание. Пока распознавание не закрыло фразу, система вообще не понимает, что ее прервали. Нативная speech-to-speech модель работает с аудио напрямую и снимает оба ограничения разом. Читать далее ## Build zero-trust AI agents that judge intent, not just syntax DevFeed: [Build zero-trust AI agents that judge intent, not just syntax]() Original publisher: [Read original article]() Author: Eric Dong; Shubham Saboo Published: 2026-09-16T01:23:36.799575Z Content type: article Language: en Sources: [Google Developers Blog]() Topics: [Artificial Intelligence](), [Security](), [Zero Trust]() Tags: [agents](), [ai](), [ai-agents](), [gemini](), [model-context-protocol](), [python](), [security](), [zero-trust]() ### AI overview This blog post explains how to move AI-agent security from static, build-time controls to dynamic runtime governance on the Gemini Enterprise Agent Platform. It covers Model Armor, Semantic Governance Policies, and Agent Anomaly Detection with Closed-Loop Remediation for evaluating intent, enforcing business rules, and detecting multi-turn attacks. ### Source excerpt 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. ## Gemini Live audio DevFeed: [Gemini Live audio]() Original publisher: [Read original article]() Author: Simon Willison Published: 2026-09-15T22:47:07Z Content type: tutorial Language: en Sources: [Simon Willison's Weblog]() Topics: [speech-to-speech](), [WebSocket](), [Google AI](), [browser](), [Playback](), [implementation](), [API]() Tags: [api](), [audio](), [browser](), [gemini](), [gemini-196](), [generative-ai](), [generative-ai-1-982](), [google](), [google-416](), [llm-release](), [llm-release-231](), [llms](), [llms-1-948](), [model](), [models](), [openai](), [playback](), [release](), [speech-to-speech](), [speech-to-text](), [speech-to-text-21](), [tools](), [tools-78](), [ui](), [voice](), [websocket](), [websockets](), [websockets-21]() ### AI overview The article describes a browser-based web UI for trying Google's Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking speech-to-speech models. The implementation supports model and voice selection, an optional system prompt, voice conversations, and interruption while the model is speaking. It uses no libraries, connecting to a WebSocket endpoint and using the Web Audio API for capture and playback. ### Source excerpt Tool: Gemini Live audio Google released Gemini 3.8 Live and 3.8 Live Extended Thinking today - two new speech-to-speech models that are a similar shape to OpenAI's GPT-Live family. I pointed GPT-6 Astra Extra High at the documentation and had it build me this web UI for trying out the new models. You can select a model and voice preset, enter an optional system prompt and then start a voice conversation through your browser, including the ability to interrupt the model while it is talking. The implementation uses no libraries. It connects to the wss://generativelanguage.googleapis.com/ws/google.ai.generativelanguage.v1alpha.GenerativeService.BidiGenerateContent?key=... WebSocket endpoint and uses a Web Audio API AudioContext for both capture and playback. Here's the Gemini Live tutorial for getting started with that WebSockets API. Tags: google, tools, websockets, generative-ai, llms, gemini, llm-release, speech-to-text ## Introducing Gemini 3.8 Live and 3.8 Live Extended Thinking DevFeed: [Introducing Gemini 3.8 Live and 3.8 Live Extended Thinking]() Original publisher: [Read original article]() Author: Tom Ouyang Published: 2026-09-15T17:05:57Z Content type: release Language: en Sources: [Google DeepMind News]() Topics: [Artificial Intelligence](), [real-time](), [speech-to-speech](), [Google](), [API]() Tags: [ai](), [api](), [audio](), [cost](), [efficiency](), [gemini](), [google](), [none](), [real-time](), [speech-to-speech](), [tools]() ### AI overview Google introduces Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, two models designed for near-real-time voice interaction and reasoning. The release describes visual grounding, multilingual conversation, background tool and API execution, and deeper reasoning for complex workflows. ### Source excerpt Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking are our most advanced live dialogue models yet, built for natural conversation. ## Switching from Microsoft 365 to Google is unlikely to deliver significant savings, Gartner says DevFeed: [Switching from Microsoft 365 to Google is unlikely to deliver significant savings, Gartner says]() Original publisher: [Read original article]() Author: Simon Sharwood Published: 2026-09-15T07:23:34Z Content type: news Language: en Sources: [www.theregister.com - Articles]() Topics: [Google](), [Microsoft](), [Cloud]() Tags: [ai-and-ml](), [alternatives](), [cloud](), [copilot](), [gartner](), [gemini](), [google](), [google-workspace](), [microsoft](), [microsoft-365](), [saas]() ### AI overview The article reports that organizations switching from Microsoft 365 to Google are unlikely to save much money, according to Gartner. ### Source excerpt Nor are you likely to save much by making the move, says Gartner ## Gemini 3.8 Live models now available on AI Gateway DevFeed: [Gemini 3.8 Live models now available on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-15T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [real-time](), [Artificial Intelligence](), [API](), [Google](), [WebSocket](), [SDKs]() Tags: [ai](), [api](), [cost](), [failover](), [gemini](), [google](), [real-time](), [realtime](), [sdk](), [websocket]() ### AI overview Vercel announces that Google's Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking models are available on AI Gateway. The models support real-time spoken interactions, audio and visual grounding, multilingual switching, background tool calls, and parallel reasoning through the AI SDK's realtime API. ### Source excerpt Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking from Google are now available on AI Gateway. Both models support real-time spoken interactions for voice assistants, conversational experiences, and applications that respond through audio. google/gemini-3.8-live supports real-time audio, visual grounding, automatic switching across 97 languages, and background tool calls while the conversation continues. google/gemini-3.8-live-extended-thinking adds multi-step reasoning that runs in parallel with speech, allowing it to acknowledge requests and narrate progress without interrupting the conversation. Use either model through the AI SDK's realtime API. Install the Gateway provider and a WebSocket client: Mint a short-lived token, open the WebSocket, and use the model adapter to serialize and parse realtime events: See the realtime quickstart for more details on realtime events and WebSocket connections. Try Gemini 3.8 Live or Gemini 3.8 Live Extended Thinking in the model playground. AI Gateway provides a unified API for calling models, tracking usage and cost, and configuring retries, failover, and performance optimizations for higher-than-provider uptime. Read more ## How to Evaluate Live & Voice Agents in ADK DevFeed: [How to Evaluate Live & Voice Agents in ADK]() Original publisher: [Read original article]() Author: Stephen Allen Published: 2026-09-12T11:04:33.891311Z Content type: tutorial Language: en Sources: [Google Developers Blog]() Topics: [AI Bots](), [CI/CD]() Tags: [agents](), [audio](), [ci-cd](), [cli](), [evaluation](), [gemini](), [how-to](), [json](), [llm](), [production](), [testing](), [tool](), [tools](), [transcripts](), [voice](), [workflows]() ### AI overview The article explains how to evaluate live voice agents in ADK with simulated audio conversations, automated scoring, and recorded results. It covers scenario-based and fixed-conversation test cases, multi-agent workflows, and running evaluations in CI/CD. ### Source excerpt Moving live voice agents from demo to production requires rigorous, automated testing to handle the unpredictability of real multi-turn conversations. ADK now provides native live evaluation, allowing developers to test graph-based agent workflows against LLM-driven simulated users that generate actual audio via Gemini TTS. By defining evaluation scenarios and natural-language rubrics, you can automatically score audio responses and tool executions, inspect the resulting transcripts in ADK Web, or run the CLI directly in your CI/CD pipeline. ## Agent and Model Evaluations in Gemini Enterprise Agent Platform are now GA DevFeed: [Agent and Model Evaluations in Gemini Enterprise Agent Platform are now GA]() Original publisher: [Read original article]() Author: Alex Martin; Dima Melnyk Published: 2026-09-12T11:04:33.891311Z Content type: release Language: en Sources: [Google Developers Blog]() Topics: [ai observability](), [SDKs](), [ci]() Tags: [agent](), [agents](), [ci](), [cli](), [development](), [enterprise](), [evaluation](), [experiments](), [gemini](), [llm](), [metrics](), [model](), [platform](), [production](), [telemetry](), [testing](), [traces]() ### AI overview Gemini Enterprise Agent Platform's evaluation service is generally available. It provides consistent evaluation of agents and models across local experiments and production traffic, with pre-built metrics, adaptive rubrics, custom metrics, simulators, and workflow integrations. ### Source excerpt Agent Platform's evaluation service is now generally available, providing developers with a unified engine to measure agent quality consistently across local development experiments and live production traffic. You can evaluate agents using over 20 pre-built metrics, DeepMind-backed adaptive rubrics, or custom code-based and LLM-as-a-judge metrics stored in a centralized, versioned registry. The service integrates directly into existing workflows via the Agent Platform SDK, agents-cli, and ADK, offering built-in user and environment simulators to automate complex multi-turn testing and streamline CI pipelines. ## Google Is Testing a Search Bar That Works Outside Chrome DevFeed: [Google Is Testing a Search Bar That Works Outside Chrome]() Original publisher: [Read original article]() Author: Simon Sterne Published: 2026-09-10T16:00:00Z Content type: article Language: en Sources: [Web Designer Depot]() Topics: [Chrome](), [Google](), [Chromium](), [Artificial Intelligence]() Tags: [ai](), [ai-assistants](), [ai-search](), [ai-tech](), [artificial-intelligence](), [browser](), [browser-design](), [chrome](), [chrome-canary](), [chromium](), [everywhere-omnibox](), [future-of-browsers](), [future-of-search](), [gemini](), [gemini-in-chrome](), [google](), [google-chrome](), [google-search](), [project-loom](), [search](), [search-technology](), [ui-design](), [ux-design](), [web-browsers](), [web-design]() ### AI overview Google is testing Project Loom, an experimental floating Search bar that can appear over other Windows apps instead of remaining inside Chrome. The feature is unfinished, with screen sharing, Lens, and AI Mode controls reportedly not yet working. ### Source excerpt Google is quietly testing a way to bring Search outside Chrome and directly on top of whatever app you're using. It's called Project Loom, and this little floating search box could hint at a much bigger future where Google follows you around your desktop. ## Get Gemini 3.8 Flash With 75% Off DevFeed: [Get Gemini 3.8 Flash With 75% Off]() Original publisher: [Read original article]() Author: Dmitry Savelev Published: 2026-09-09T14:18:17Z Content type: release Language: en Sources: [The JetBrains Blog]() Topics: [coding](), [Google](), [releases](), [Command-line interface](), [ide]() Tags: [agentic-ai](), [agents](), [benchmark](), [cli](), [coding](), [flash](), [gemini](), [google](), [ide](), [jetbrains-ai](), [junie](), [launch](), [model](), [promotion](), [sales](), [testing]() ### AI overview Gemini 3.8 Flash is now available in Junie's IDE plugin and CLI at a limited-time 75% discount. The article presents it as a coding model for multi-step engineering tasks that explores, tests, and verifies changes before finishing. ### Source excerpt Google's newest coding model, Gemini 3.8 Flash, is tuned for long jobs and comes with an incredible launch discount. Google shipped three Flash releases in six weeks, and the newest one is built for exactly the kind of work Junie does all day: multi-step engineering tasks that take real exploration to get right. Gemini 3.8 [...] ## Rust AI in Practice: Building LLM Applications With Rig DevFeed: [Rust AI in Practice: Building LLM Applications With Rig]() Original publisher: [Read original article]() Author: Irina Mihajlovic Published: 2026-09-09T12:02:05Z Content type: article Language: en Sources: [The JetBrains Blog]() Topics: [Language models](), [Local AI](), [AI-assisted coding]() Tags: [ai](), [ai-agents](), [anthropic](), [applications](), [gemini](), [livestream](), [llm](), [llm-aplications](), [openai](), [rag](), [rust](), [rust-ai](), [rustrover]() ### AI overview The article introduces Rig, a Rust library that provides a unified interface for building LLM applications across providers. It uses a livestream coding-agent demo to explain Rig's provider clients, models, agents, tools, and prompts. ### Source excerpt Rust AI is moving from the experimentation stage toward more practical usage. We recently kicked off a new livestream series with the Rust Foundation to explore how Rust and AI are coming together in real-world applications. In the first session, our Developer Advocate Orhun Parmaksız spoke with Stephen Korzeniewski, Lead Maintainer of Rig at 0xPlaygrounds. [...] ## Supabase is now available in Gemini Enterprise DevFeed: [Supabase is now available in Gemini Enterprise]() Original publisher: [Read original article]() Author: Shaziya Bandukia; Elsa Heffernan Published: 2026-09-09T07:00:00Z Content type: release Language: en Sources: [Supabase Blog]() Topics: [Google](), [Model Context Protocol](), [Database](), [Back end]() Tags: [database](), [enterprise](), [gemini](), [google-cloud](), [mcp](), [mcp-server](), [partnership](), [real-time]() ### AI overview Supabase is available as a Gemini Enterprise connector, allowing teams to query and act on Supabase projects with natural language and live, real-time responses. ### Source excerpt Connect Supabase to Gemini Enterprise and query your Supabase projects with natural language, right inside the platform. ## 5 ways to use Gemini text-to-speech (TTS) in your apps with Firebase AI Logic DevFeed: [5 ways to use Gemini text-to-speech (TTS) in your apps with Firebase AI Logic]() Original publisher: [Read original article]() Author: Ankita Saxena Published: 2026-09-09T00:00:00Z Content type: tutorial Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [voice ai](), [Artificial Intelligence](), [digital accessibility](), [Mobile](), [Web]() Tags: [accessibility](), [ai](), [ai-logic](), [firebase](), [firebase-ai-logic](), [gemini](), [mobile](), [speech](), [text-to-speech](), [web]() ### AI overview The article presents five use cases for Gemini text-to-speech through Firebase AI Logic, including language-learning conversation practice, hands-free content reading, and accessibility-focused audio content. It also describes examples involving Finnish language exercises and recipe instructions. ### Source excerpt News, tutorials, and updates from the Firebase team. ## Android 17 AppFunction Walkthrough First Experience DevFeed: [Android 17 AppFunction Walkthrough First Experience]() Original publisher: [Read original article]() Author: Elye - A Dev By Grace Published: 2026-09-07T12:51:23Z Content type: tutorial Language: en Sources: [Mobile App Development Publication - Medium]() Topics: [Android](), [Mobile](), [App](), [Development](), [Artificial Intelligence](), [Android Studio](), [Emulator](), [Android Gradle Plugin]() Tags: [ai](), [android](), [android-app-development](), [android-gradle-plugin](), [android-studio](), [app-development](), [artificial-intelligence](), [development](), [emulator](), [gemini](), [mobile](), [mobile-app-development](), [software-development]() ### AI overview A first-hand walkthrough of Android 17 AppFunction, which lets Gemini discover an app's functionality. The article covers the required Android Studio version, Android 17 emulator, Android SDK API 37.0 target, and Android Gradle Plugin requirements. ### Source excerpt Enabling Gemini to Find Your App Functionalities Continue reading on Mobile App Development Publication " ## How MCP Toolbox turns agent text into ClickHouse vectors DevFeed: [How MCP Toolbox turns agent text into ClickHouse vectors]() Original publisher: [Read original article]() Author: Pete Hampton Published: 2026-09-07T09:00:00Z Content type: tutorial Language: en Sources: [ClickHouse Blog]() Topics: [MSP MCP]() Tags: [ai-agent](), [clickhouse](), [databases](), [embedding](), [gemini](), [go](), [google](), [how-to](), [mcp](), [search](), [sql](), [vector]() ### AI overview A tutorial for configuring Google's MCP Toolbox with ClickHouse to embed text during inserts and searches, then return cosine-ranked results without a separate embedding service. ### Source excerpt Google's MCP Toolbox for Databases embeds agent text into vectors on insert and search, then lets ClickHouse rank the results - no embedding service to build or maintain. Here's how to set it up, and what it looks like end to end. ## Pair Programming With Your AI Agent DevFeed: [Pair Programming With Your AI Agent]() Original publisher: [Read original article]() Author: blundell Published: 2026-09-06T21:50:09Z Content type: tutorial Language: en Sources: [Blundell]() Topics: [AI Agent](), [Local AI](), [Programming](), [Command-line interface]() Tags: [agent](), [ai](), [ai-agent](), [androiddev](), [antigravity](), [cli](), [gemini](), [geminicli](), [intermediate](), [intermediate-reference-ai-androiddev-gemini-geminicli-pairing](), [pair](), [pairing](), [programming](), [reference](), [terminal]() ### AI overview This tutorial presents sessions with a local AI agent as pair programming and maps four classic pairing styles--unstructured, Driver/Navigator, Strong-Style Pairing, and Ping Pong--to AI-assisted development. It uses Antigravity CLI for examples while noting that the approach is not specific to that tool. ### Source excerpt This post explains how to treat a session with a local AI agent as a pair programming session, and how the four classic pairing styles map onto working with one. I'll use Antigravity CLI for the concrete examples, though nothing here is specific to it. Swap in whichever agent sits in your terminal. The idea [...] The post Pair Programming With Your AI Agent first appeared on Blundell. ## Portal by Spotify cut my Claude Code token usage by 90% DevFeed: [Portal by Spotify cut my Claude Code token usage by 90%]() Original publisher: [Read original article]() Author: Spotify Engineering Published: 2026-09-03T16:06:40Z Content type: article Language: en Sources: [Spotify Engineering](), [Spotify Engineering Blog]() Topics: [AI Bots]() Tags: [agents](), [ai](), [ai-coding](), [claude](), [claude-code](), [cli](), [gemini](), [mcp]() ### AI overview The article describes using Portal modes to route repetitive AI coding work, such as reading large files and generating predictable code, to a cheaper model while reserving Claude for harder problems. ### Source excerpt Most of what an AI coding agent does for me isn't thinking. It's I/O. The post Portal by Spotify cut my Claude Code token usage by 90% appeared first on Spotify Engineering. ## Introducing WeatherNext 3, our most advanced and accurate global weather AI model DevFeed: [Introducing WeatherNext 3, our most advanced and accurate global weather AI model]() Original publisher: [Read original article]() Author: The WeatherNext team Published: 2026-09-03T15:02:08Z Content type: article Language: en Sources: [Google DeepMind News]() Topics: [Artificial Intelligence](), [Google](), [data]() Tags: [ai](), [cloud](), [gemini](), [generative](), [google](), [model](), [none](), [search]() ### AI overview Google DeepMind and Google Research introduce WeatherNext 3, a global weather AI model that uses real-time observations and raw satellite data for hourly, high-resolution forecasts. ### Source excerpt WeatherNext 3, our most advanced global weather AI model, is now in Search, Gemini, Maps, Google Maps Platform, and Cloud. ## Your Agent Speaks MCP. Give It a Computer. DevFeed: [Your Agent Speaks MCP. Give It a Computer.]() Original publisher: [Read original article]() Published: 2026-09-03T00:00:00Z Content type: article Language: en Sources: [The Fly Blog]() Topics: [MSP MCP](), [AI Bots]() Tags: [agents](), [api](), [auth](), [cdn](), [claude](), [claude-code](), [cli](), [close-to-users](), [cloud](), [codex](), [cursor](), [deploy-app-servers](), [docker](), [elixir](), [filesystems](), [fly](), [fly-io](), [gemini](), [heroku-alternative](), [heroku-competitor](), [hosting](), [i](), [mcp](), [mcp-server](), [networking](), [postgresql-clusters](), [servers](), [skills]() ### AI overview The article presents Sprites as disposable cloud computers for coding agents and explains using their API through MCP. It argues that MCP transport and progressive capability disclosure can work together, including through plugins and skills. ### Source excerpt Sprites are disposable cloud computers. They appear instantly, always include durable filesystems, and cost practically nothing when idle. They're the best and safest place on the Internet to run agents and we want you to create dozens of them. Sprites are a place to run agents; the first thing you should think to do with a new Sprite is to type claude (or gemini or codex). We've put a lot of effort into making sure coding agents feel safe and happy when they're on Sprites, because, to (probably) quote John von Neumann, "happy agents are productive agents." What's less obvious about Sprites is that they're great tools for agents. Want three different versions of a new feature? A test environment? An ensemble of cooperating services? It's super handy to be able to start your prompts, "On a new Sprite, do...". The Sprites API is simple, discoverable, and designed for this use case. The only real question is how your agent reaches it. For most of you the answer is MCP, and the setup is already written. You Don't Have To Pick There's an argument going around that MCP is the wrong way to extend an agent, and that command line tools and discoverable APIs are the Right Way. Half of that argument is correct, and it's the important half, so let's take it seriously. Dumping thirty tool descriptions into a context window is a bad way to teach anything. Not every Sprite command matters in every session, and cramming them all in signals to the model that they all matter to you. If you're not using network policies, gemini shouldn't burn a single token learning to configure them. Capabilities should reveal themselves progressively, the way they do when an agent works out a CLI one subcommand at a time. The wrong half is treating that as a case against MCP. Progressive disclosure is a question of what you say to the model. MCP is a question of how the bytes get there: transport, auth, structured results, a tool the model can call instead of a command whose flags it has to guess. Tho ## Proactive cyber defense for governments and enterprises DevFeed: [Proactive cyber defense for governments and enterprises]() Original publisher: [Read original article]() Author: Four Flynn Published: 2026-09-02T16:24:24Z Content type: release Language: en Sources: [Google DeepMind News]() Topics: [Cybersecurity](), [Vulnerabilities](), [Google](), [Code](), [cloud-infrastructure]() Tags: [agentic](), [ai](), [critical-infrastructure](), [cybersecurity](), [enterprise](), [gemini](), [government](), [none](), [vulnerabilities]() ### AI overview Google announces the Fairwind Program, which provides a trusted group of government, cloud, and cybersecurity partners early access to Gemini cyber models and the CodeMender harness to find, verify, and fix vulnerabilities. ### Source excerpt The Fairwind Program is a limited access program for governments and trusted partners to use our cyber defense tools. ## Introducing Gemini 3.8 Flash and 3.8 Flash Cyber DevFeed: [Introducing Gemini 3.8 Flash and 3.8 Flash Cyber]() Original publisher: [Read original article]() Author: Tulsee Doshi Published: 2026-09-02T16:18:31Z Content type: release Language: en Sources: [Google DeepMind News]() Topics: [releases](), [AI Chat](), [AI Bots]() Tags: [agentic](), [benchmark](), [coding](), [cybersecurity](), [flash](), [gemini](), [none](), [reasoning](), [release](), [software-engineering](), [vulnerability]() ### AI overview Google introduces Gemini 3.8 Flash and Gemini 3.8 Flash Cyber, highlighting coding, multi-step reasoning, autonomous-agent use, cybersecurity capabilities, pricing, and benchmark claims. ### Source excerpt Gemini 3.8 Flash and 3.8 Flash Cyber deliver next-generation intelligence for agentic workflows and cybersecurity. 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