# AI studio Published articles for AI studio. 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 ## Where do a compliance dashboard's numbers actually come from? DevFeed: [Where do a compliance dashboard's numbers actually come from?]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-11T09:52:40Z Content type: article Language: en Sources: [Tyk API Management]() Topics: [dashboards](), [Amazon API Gateway](), [Script]() Tags: [ai-gateway](), [ai-governance](), [ai-studio](), [api-management](), [api-platform-teams](), [complexity](), [compliance](), [llm-security](), [ppi-redaction](), [tengo](), [tutorial]() ### AI overview The article explains where a compliance dashboard's metrics come from. Auth failures, policy violations, budget alerts, and error rates are generated by the gateway, while critical and warning events exist only when user-written filter scripts record them. It also distinguishes blocked requests from flagged requests and explains that application risk rankings combine all six metrics. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today I have been given something I consider a genuine privilege: an entire dashboard, and the question of where its numbers come from. That question is less obvious than it sounds. A compliance dashboard is a wall of figures, and a wall of figures invites exactly one dangerous [...] The post Where do a compliance dashboard's numbers actually come from? appeared first on Tyk API Management. ## One name in, whichever vendor you like out DevFeed: [One name in, whichever vendor you like out]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-10T11:21:00Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [Tutorial](), [API](), [Large Language Model](), [App](), [Bot]() Tags: [ai-gateway](), [ai-governance](), [ai-strategy](), [ai-studio](), [api](), [api-management](), [api-platform-teams](), [developers](), [enterprise](), [llm](), [llm-governance](), [model](), [router](), [tutorial]() ### AI overview A tutorial explains how to use Tyk's Model Router as a single OpenAI-compatible endpoint that routes requests to registered LLM providers. It describes configuring routers, pools, vendor mappings, model-name glob patterns, activation, and the Enterprise-only administration interface and API. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today I have been given a router. Not the sort that sits in a cupboard blinking reproachfully at you. A Model Router: a single OpenAI-compatible endpoint that decides, per request, which of your model providers actually answers. Your application asks for a model by name. Which vendor serves [...] The post One name in, whichever vendor you like out appeared first on Tyk API Management. ## The same question twice, paid for once: installing an LLM response cache DevFeed: [The same question twice, paid for once: installing an LLM response cache]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-09T09:15:00Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [Large Language Model](), [Cache](), [Caching](), [Tutorial](), [Open Source](), [Go](), [Code]() Tags: [ai-gateway](), [ai-strategy](), [ai-studio](), [api-management](), [api-platform-teams](), [article](), [cache](), [container](), [container-image](), [go](), [llm](), [llm-governance](), [open-source](), [tutorial]() ### AI overview A tutorial showing how to install a community plugin that caches LLM responses in AI Studio. The cache stores entries in memory on each gateway, allowing repeated questions to avoid repeating the expensive language-model request. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today's assignment involves no code whatsoever, which I am told is a selling point. Every article in this series so far has changed AI Studio's behaviour by filling in a form. This one changes what AI Studio is. We are going to install a plugin -- a compiled [...] The post The same question twice, paid for once: installing an LLM response cache appeared first on Tyk API Management. ## Somebody else's API, safely on your menu DevFeed: [Somebody else's API, safely on your menu]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-08T14:28:00Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [API](), [shadow AI](), [audit trail](), [Template](), [Tool](), [data]() Tags: [ai](), [ai-gateway](), [ai-studio](), [api](), [api-management](), [api-platform-teams](), [article](), [audit-trail](), [community](), [governance](), [llm](), [llm-governance](), [markdown](), [password](), [policy](), [resource](), [shadow-ai](), [tools](), [tutorial]() ### AI overview This tutorial explains how to submit an internal API for governed use by colleagues and organizational language models. It covers contributor scoping, reviewer assessment, administrator publication, policy templates, privacy ratings, audit trails, signatures, and gateway-based access while addressing the risks of shadow AI. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today's assignment is one I have been looking forward to rather a lot. Somebody on your engineering team has written an API. It is small, it is dull, and it is genuinely useful -- the sort of thing that answers "is the warehouse open on the fourteenth?" without [...] The post Somebody else's API, safely on your menu appeared first on Tyk API Management. ## Who can use which model? Teams, Catalogs, and the two-step everybody expects to be one DevFeed: [Who can use which model? Teams, Catalogs, and the two-step everybody expects to be one]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-08T11:07:00Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [Tutorial](), [Authorization](), [Language models]() Tags: [access-control](), [ai](), [ai-gateway](), [ai-studio](), [api-management](), [api-platform-teams](), [article](), [developer](), [governance](), [llm](), [llm-governance](), [tutorial](), [uncategorized]() ### AI overview This tutorial explains how to govern which users can access language models and other resources in Tyk AI Studio. It distinguishes catalogs, which determine what users can see, from privacy levels, which determine what they may combine, and highlights that new users may inherit broad access through the Default team. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today's assignment is a slightly different sort of thing. Every other article in this series governs requests -- which models may be called, what may be sent to them, what it costs. This one governs people. By the end, one person in this organisation will be able to [...] The post Who can use which model? Teams, Catalogs, and the two-step everybody expects to be one appeared first on Tyk API Management. ## One Tool, three surfaces: from an OpenAPI file to an MCP server, without writing it twice DevFeed: [One Tool, three surfaces: from an OpenAPI file to an MCP server, without writing it twice]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-07T09:27:00Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [OpenAPI Specification](), [Model Context Protocol (MCP)](), [MCP Server](), [API](), [ASCII](), [HTTP](), [cURL]() Tags: [ai-gateway](), [ai-governance](), [ai-readiness](), [ai-studio](), [api](), [api-management](), [api-platform-teams](), [article](), [ascii](), [curl](), [developer](), [http](), [llm-governance](), [llm-observability](), [mcp-server](), [model-context-protocol](), [openapi]() ### AI overview This tutorial shows how to define an HTTP API once in an OpenAPI document and expose it through three surfaces: model-initiated tool calls, a REST endpoint accessed with curl, and an MCP server. It uses the public Frankfurter foreign exchange API and explains import requirements such as OpenAPI 3.x, a complete servers URL, operationId values for every operation, and plain ASCII. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today I have been given a genuinely satisfying assignment. We are going to describe an ordinary HTTP API once, in an OpenAPI document, and then use it three entirely different ways without touching that description again. A model will call it on its own initiative inside a chat. [...] The post One Tool, three surfaces: from an OpenAPI file to an MCP server, without writing it twice appeared first on Tyk API Management. ## Your redaction filter works. Are you quite sure? DevFeed: [Your redaction filter works. Are you quite sure?]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-03T09:03:23Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [Tutorial](), [pii](), [Artificial Intelligence](), [Script](), [Regular expression](), [payload](), [API]() Tags: [ai-gateway](), [ai-studio](), [api](), [api-management](), [api-platform-teams](), [data-privacy](), [how-to](), [llm-governance](), [payload](), [pii](), [pii-redaction](), [tengo](), [tutorial]() ### AI overview This tutorial explains how to create and test a Tyk request filter that redacts personal data before a request reaches an AI model. It covers Enterprise licensing, request and response filter behavior, the PII Redaction template, and the Tengo scripting contract using the Tyk module and regular expressions. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today I have been given something genuinely useful to explain: how to stop personal data reaching a model in the first place. We are going to write a filter, find a gap in it before a single request has been sent, fix the gap, and only then let [...] The post Your redaction filter works. Are you quite sure? appeared first on Tyk API Management. ## One environment variable, and Claude Code is suddenly accountable DevFeed: [One environment variable, and Claude Code is suddenly accountable]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-02T10:38:00Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [Claude Code](), [anthropic](), [API](), [configuration](), [Tutorial]() Tags: [ai-gateway](), [ai-studio](), [anthropic](), [api](), [api-management](), [api-platform-teams](), [article](), [claude-code](), [configuration](), [llm-governance](), [llm-observability](), [secrets](), [tutorial]() ### AI overview This tutorial explains how to route Claude Code through Tyk AI Studio's Anthropic-compatible endpoint using one environment variable. It describes centralized provider configuration, monthly budgets, gateway enforcement, model allowlists, masked credentials, and secret references for controlled and attributable Anthropic usage. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today I have been handed something slightly unusual: an article in which the thing being governed is very probably the thing you are using right now. Claude Code. Somebody on your team is running it. Possibly everybody is. It is excellent, it is fast, and from where your [...] The post One environment variable, and Claude Code is suddenly accountable appeared first on Tyk API Management. ## Nobody Should Be Sharing Your OpenAI Key DevFeed: [Nobody Should Be Sharing Your OpenAI Key]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-02T08:35:50Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [OpenAI](), [Large Language Model](), [Tutorial](), [API]() Tags: [ai](), [ai-gateway](), [ai-studio](), [anthropic](), [api](), [api-management](), [api-platform-teams](), [developer](), [gpt](), [large-language-model](), [llm](), [llm-governance](), [models](), [openai](), [secrets](), [tutorial]() ### AI overview This tutorial explains how an organization can register OpenAI as a provider in Tyk, expose it through a portal and gateway, keep the provider key hidden from developers, optionally reference the key through Secrets, and restrict permitted models with a regular-expression pattern such as gpt-5.*. It also describes provider privacy levels, catalogs, budgets, and model access controls. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and I have been given the considerable privilege of explaining how a large language model gets from "we have an account with OpenAI" to "a developer is shipping with it, inside a budget, and has never seen the key". It is a shorter journey than you might expect. It [...] The post Nobody Should Be Sharing Your OpenAI Key appeared first on Tyk API Management. ## PereStruct: Modular Pipeline and Dataset for Parsing Historical Newspapers DevFeed: [PereStruct: Modular Pipeline and Dataset for Parsing Historical Newspapers]() Original publisher: [Read original article]() Author: makSShan (Яндекс, Yandex Cloud & Yandex Infrastructure) Published: 2026-09-01T07:05:21Z Content type: tutorial Language: ru Sources: [Яндекс - Как мы делаем Яндекс / Статьи]() Topics: [Artificial Intelligence](), [яндекс](), [vlm]() Tags: [ai](), [ai-studio](), [bleu](), [computervision](), [ocr](), [perestruct](), [rouge](), [tag-4004cf5948d3](), [tag-65c8d6d9e736](), [tag-9bf5e01ce62e](), [tag-d27a0708d400](), [vision](), [vlm](), [yandex-ai-studio](), [yolo]() ### AI overview The article presents PereStruct, a modular pipeline for reconstructing articles from historical newspaper scans. It combines YOLO-based layout detection, Yandex Vision OCR, Yandex AI Studio models for error correction, and a semantic model for assembling article blocks; the authors also publish code, an annotated dataset, and a benchmark. ### Source excerpt Попробуйте открыть скан советской газеты и прочитать одну статью от начала до конца. Человек быстро замечает крупный заголовок, продолжение в соседней колонке и подпись под фотографией. Для алгоритма перед ним -- это выцветшая страница с десятками тесно расположенных прямоугольников, нестандартными шрифтами и неоднозначным порядком чтения. Даже если OCR правильно распознаёт почти все слова, на выходе ещё не получится документ. Нужно понять, какие фрагменты относятся к одной статье, где её начало, в каком порядке соединить блоки и что не следует включать в основной текст. Мы разработали PereStruct -- модульный пайплайн для разбора исторических газет. Он объединяет детектор вёрстки на базе YOLO, Yandex Vision OCR, коррекцию ошибок с помощью моделей Yandex AI Studio и отдельную модель семантической сборки статей. Вместе с кодом мы публикуем размеченный датасет и бенчмарк, чтобы другие команды могли изучать подход и ставить эксперименты на исторических документах. Читать далее ## What's new from Firebase at Google I/O 2026 DevFeed: [What's new from Firebase at Google I/O 2026]() Original publisher: [Read original article]() Author: Seba Gnagnarella; Arthur Thompson; Kristen Richards Published: 2026-05-19T01:00:00Z Content type: news Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Agent Skills](), [Google](), [Mobile](), [Android Studio](), [Flutter](), [Model Context Protocol]() Tags: [2026](), [a-b-testing](), [agent-skills](), [ai-logic](), [ai-studio](), [android](), [android-studio](), [antigravity](), [app-check](), [application-design-center](), [authentication](), [cloud-logging](), [cloud-run](), [crashlytics](), [firebase](), [firestore](), [flutter](), [google](), [google-i-o](), [hybrid-inference](), [ios](), [mcp](), [mobile](), [news](), [remote-config](), [security]() ### AI overview Firebase announces updates from Google I/O 2026, including integrations with Google Antigravity and Android Studio, expanded Agent Skills for mobile development, and support for Firestore, Firebase Authentication, Crashlytics, and Remote Config. ### Source excerpt News, tutorials, and updates from the Firebase team. ## What's new from Firebase at Cloud Next 2026 DevFeed: [What's new from Firebase at Cloud Next 2026]() Original publisher: [Read original article]() Author: Seba Gnagnarella; Arthur Thompson; Kristen Richards Published: 2026-04-22T11:30:00Z Content type: news Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Cloud](), [Firestore](), [PostgreSQL](), [SQL](), [Mobile](), [Web](), [GraphQL]() Tags: [2026](), [ai](), [ai-logic](), [ai-studio](), [app-check](), [application-design-center](), [authentication](), [cloud-functions](), [cloud-next](), [dart-on-the-server](), [firebase](), [firestore](), [flutter](), [full-text-search](), [gemini](), [geo-queries](), [graphql](), [hybrid-inference](), [mobile](), [news](), [phone-number-verification](), [postgresql](), [sql](), [sql-connect](), [updates](), [web]() ### AI overview Firebase describes announcements from Cloud Next 2026, including the evolution of Firebase Data Connect into Firebase SQL Connect with realtime syncing, offline cache, and native SQL support. The article also covers Firestore Enterprise pipeline queries moving to general availability. ### Source excerpt News, tutorials, and updates from the Firebase team. ## From prompt to production: Build full-stack apps faster with Google AI Studio and Firebase DevFeed: [From prompt to production: Build full-stack apps faster with Google AI Studio and Firebase]() Original publisher: [Read original article]() Author: Kara Yu; Sam Phillips Published: 2026-03-19T00:00:00Z Content type: release Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Google AI](), [Firestore](), [Google](), [Authentication](), [backends](), [Agent Harness]() Tags: [agent](), [agent-harness](), [ai](), [ai-studio](), [antigravity](), [authentication](), [backends](), [build](), [firebase](), [firebase-studio](), [firestore](), [google](), [security]() ### AI overview Firebase announces an integration with Google AI Studio that can provision Firebase projects, Firestore, Authentication, sign-in pages, application code, and draft Security Rules with user approval. The announcement also describes a new Google AI Studio coding agent for multi-step code edits and connections to services such as payment processors and Google Maps. ### Source excerpt Today, we're announcing that Firebase is now integrated with Google AI Studio, accelerating your path from prompt to production so you can turn your vibe-coded ideas into fully functional apps with robust backends. Read on to learn how this works and what this means for Firebase Studio. ## Gemini 3 Flash: frontier intelligence built for speed DevFeed: [Gemini 3 Flash: frontier intelligence built for speed]() Original publisher: [Read original article]() Author: Tulsee Doshi Published: 2025-12-17T11:58:17Z Content type: release Language: en Sources: [Google DeepMind News]() Topics: [Google AI](), [Artificial Intelligence](), [agentic workflows](), [multimodal](), [API](), [Code](), [Google](), [google-antigravity]() Tags: [agentic](), [agentic-workflows](), [ai](), [ai-studio](), [antigravity](), [api](), [benchmarks](), [cost](), [development](), [efficiency](), [gemini](), [google-ai](), [google-antigravity](), [latency](), [none](), [performance](), [platform](), [reasoning](), [release](), [speed](), [tokens]() ### AI overview Google announces Gemini 3 Flash, a faster and more efficient model in the Gemini 3 family. The release targets developers, consumers, and enterprises across Google's platforms, with support for reasoning, multimodal understanding, and agentic workflows. ### Source excerpt Gemini 3 Flash offers frontier intelligence built for speed at a fraction of the cost. ## Improved Gemini audio models for powerful voice experiences DevFeed: [Improved Gemini audio models for powerful voice experiences]() Original publisher: [Read original article]() Author: Bibo Xu Published: 2025-12-12T17:50:50Z Content type: article Language: en Sources: [Google DeepMind News]() Topics: [Google](), [Google AI](), [voice ai](), [speech-to-speech](), [Artificial Intelligence](), [real-time](), [Streaming](), [Google Cloud Platform (GCP)]() Tags: [ai-studio](), [audio](), [customer-service](), [enterprise](), [gemini](), [google-cloud](), [none](), [real-time](), [speech](), [speech-to-speech](), [streaming](), [vertex-ai](), [voice]() ### AI overview Google describes upgrades to Gemini 2.5 Native Audio for live voice agents, including better function calling, instruction following, and multi-turn conversations. The model is available across Google AI Studio and Vertex AI, with rollouts to Gemini Live and Search Live. The article also introduces beta live speech-to-speech translation in Google Translate. ### Source excerpt An upgraded Gemini 2.5 Native Audio model across Google products and live speech translation in the Google Translate app. ## Build with Nano Banana Pro, our Gemini 3 Pro Image model DevFeed: [Build with Nano Banana Pro, our Gemini 3 Pro Image model]() Original publisher: [Read original article]() Author: Alisa Fortin Published: 2025-11-20T15:11:14Z Content type: article Language: en Sources: [Google DeepMind News]() Topics: [Google AI](), [text-to-image](), [Artificial Intelligence](), [API](), [multimodal](), [Google Search](), [Figma]() Tags: [4k](), [ai](), [ai-studio](), [api](), [color-grading](), [demo](), [figma](), [gemini](), [generation](), [google-search](), [image](), [model](), [multimodal](), [none](), [product-design]() ### AI overview The article announces Nano Banana Pro, also called Gemini 3 Pro Image, a higher-fidelity image generation and editing model built on Gemini 3 Pro. It describes developer access through the Gemini API in Google AI Studio and Vertex AI, with multimodal capabilities, Google Search grounding, improved text rendering, precise image controls, high-resolution outputs, and support for compositing multiple reference elements. The model is also being integrated into developer and creative platforms for UI mockups and visual asset creation. ### Source excerpt Nano Banana Pro, or Gemini 3 Pro Image, is our most advanced image generation and editing model. ## Introducing Mistral AI Studio. DevFeed: [Introducing Mistral AI Studio.]() Original publisher: [Read original article]() Published: 2025-10-24T12:00:00Z Content type: release Language: en Sources: [Mistral AI Blog]() Topics: [AI Platform](), [Artificial Intelligence](), [MLOps](), [Security](), [DevOps](), [data](), [Large Language Model](), [Deployment](), [Prompt Engineering](), [on-prem](), [VPC]() Tags: [agents](), [ai](), [ai-adoption](), [ai-assistants](), [ai-platform](), [ai-studio](), [autonomous-agents](), [compliance](), [infrastructure](), [multimodal-ai](), [on-prem](), [privacy](), [provenance](), [vpc](), [workflows]() ### AI overview Mistral introduces AI Studio, an enterprise AI platform for customizing, fine-tuning, evaluating, governing, and deploying AI assistants, autonomous agents, and multimodal AI with open models. It addresses the gap between AI prototypes and production by providing evaluation, feedback and dataset workflows, provenance and versioning, governance, and flexible deployment across hybrid, VPC, and on-prem infrastructure. ### Source excerpt The most powerful AI platform for enterprises. Customize, fine-tune, and deploy AI assistants, autonomous agents, and multimodal AI with open models. ## Heroku AI Studio for Managed Inference and Agents DevFeed: [Heroku AI Studio for Managed Inference and Agents]() Original publisher: [Read original article]() Author: Anush DSouza Published: 2025-09-17T15:00:12Z Content type: release Language: en Sources: [Heroku]() Topics: [Heroku AI](), [AI Development](), [Heroku](), [Generative AI](), [Inference]() Tags: [ai](), [ai-studio](), [generative-ai](), [heroku](), [heroku-ai](), [managed-inference-and-agents](), [news](), [product-features]() ### AI overview Heroku introduces AI Studio, an interactive workspace for its Managed Inference and Agents add-on. It lets developers experiment with provisioned models and tools, refine prompts, and use code-integration guidance. ### Source excerpt Ever found yourself in the endless loop of tweaking a prompt, running your code, and waiting to see if you finally got the output you wanted? That slow, frustrating feedback cycle is a common headache for AI developers. What if you could speed that up and get back to what you do best? Let's focus on building amazing applications. We're excited to introduce Heroku AI Studio, a new set of tools designed to streamline your generative AI development from prompt to production. We've focused on creating a more intuitive and efficient workflow, so you can focus on innovation instead of wrestling with your development environment. When using the Heroku Managed Inference and Agents add-on, this new tool is about to become an essential part of your workflow. The post Heroku AI Studio is Your Workspace for Smarter, Faster AI Apps appeared first on Heroku. ## Supercharge your apps with Firebase and the Gemini API DevFeed: [Supercharge your apps with Firebase and the Gemini API]() Original publisher: [Read original article]() Author: Alexander Nohe; Frank van Puffelen Published: 2024-02-15T00:00:00Z Content type: tutorial Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [Generative AI](), [Google AI](), [Firestore](), [Chat Bot](), [Image]() Tags: [ai](), [ai-studio](), [alt-text](), [chatbots](), [extensions](), [firebase](), [firestore](), [gemini](), [generative-ai](), [how-to](), [learn](), [web]() ### AI overview This tutorial explains how Firebase Extensions can integrate the Gemini API into applications. It demonstrates building a conference-session chatbot and automatically generating accessible alt text for images, with data stored in Firestore and behavior guided by prompts. ### Source excerpt Learn how to easily integrate Google's powerful Gemini into your Firebase apps. Build conversational chatbots and auto-generate image alt text with code-free simplicity.