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Summaries are not the original full articles. ## GenUI Beyond Chat: Designing a Grammar Book with Flutter GenUI -- Part 1 DevFeed: [GenUI Beyond Chat: Designing a Grammar Book with Flutter GenUI -- Part 1]() Original publisher: [Read original article]() Author: Cagatay Ulusoy Published: 2026-08-03T15:15:45Z Content type: article Language: en Sources: [Flutter Community - Medium]() Topics: [Flutter](), [App](), [Framework](), [personalization](), [ui](), [Learning](), [SDK]() Tags: [ai](), [app](), [article](), [feature](), [firebase](), [flutter](), [framework](), [gemini](), [generative-ui](), [genuis](), [learning](), [personalization](), [ui]() ### AI overview This article describes using Flutter GenUI to build an interactive Finnish grammar course inside a language-learning app. It focuses on generating personalized lessons from the learner's language and presenting them as Flutter pages rather than as a long Markdown response. ### Source excerpt Last year on #FlutterFlightPlans live stream, I asked the Flutter team a question that has stayed with me: Are there any use cases for Generative UI other than chat responses? Can you share some inspiration? Seth Ladd answered, "Let's see what is beyond chat together." 🚀 Since that moment, exploring GenUI beyond chat has been my primary focus. https://medium.com/media/7c53d065806a0337fcf3a8db1412ec82/href I shared my first journey with GenUI in an article series: a small GenUI framework built with Gemini structured outputs, and a migration to Flutter GenUI SDK and A2UI surfaces. Then I tried a different kind of use case: a Finnish 🇫🇮 grammar course inside my Finnish it language-learning app. In this feature, the learner browses a curriculum in their own language, opens one small grammar topic, and moves through a sequence of Flutter pages. https://medium.com/media/3ac419e10db257e4f9652bdfb9ad5165/hrefProblem Definition I had four constraints: I do not speak Finnish, and I am not a language teacher. I don't have time to manually plan and structure a grammar book's worth of micro-lessons in every language. I want interactive application UI, not a long Markdown response. Hyper-personalization is crucial. The explanation should begin from the learner's language. A Turkish learner can approach Finnish vowel harmony through Turkish vowel harmony; an English learner needs another bridge since it has no similar concept. Vowel harmony lessons in English and TurkishThe same rule does not feel equally foreign That fourth constraint is more than UI localization. Turkish speakers will find two familiar concepts in Finnish grammar: attaching grammatical markers directly to the ends of nouns, and changing suffix vowels to match the root word. For example, expressing "in" or "at" requires the exact same mental process in both languages: Turkish: ev + -de = evde (in the house) Finnish: talo + -ssa = talossa (in the house) An English speaker has a completely different starting point. ## Demystifying A2UI: How to Make AI Agents "Speak UI" in Your App DevFeed: [Demystifying A2UI: How to Make AI Agents "Speak UI" in Your App]() Original publisher: [Read original article]() Author: Devin Chasanoff Published: 2026-06-26T09:01:02Z Content type: tutorial Language: en Sources: [Angular]() Topics: [Protocol (disambiguation)](), [ui](), [Artificial Intelligence](), [Angular](), [Large Language Model](), [Web](), [web applications](), [Architecture & Design](), [Front end]() Tags: [a2a](), [a2ui](), [adk](), [agentic](), [agents](), [ai](), [ai-agents](), [angular](), [architecture](), [frontend](), [genuis](), [how-to](), [in-app-experiences](), [llm](), [protocol](), [ui](), [web](), [web-app]() ### AI overview This tutorial explains A2UI, a protocol that lets AI agents generate rich, interactive user interfaces for web, mobile, and desktop applications without executing arbitrary code. It presents a developer-oriented mental model covering the protocol's architecture, client-server communication, and rendering flexibility. ### Source excerpt I've spent a fair amount of time experimenting with A2UI, a protocol for building agentic interfaces. Why? Quite simply, because I think the idea of dynamically generating user interfaces is awesome, and despite the fact that this is a relatively new protocol (currently 1.0 RC), I wanted to answer a fundamental question: "How do I incorporate A2UI into my own app?" If you're new to working with generative UIs, it may be challenging to wrap your head around the core concepts. This post is my mental model for how everything works from a developer's implementation perspective so that you can start using it in your own applications. I'm incredibly excited about the future of web apps. So much so that last November, I hosted a livestream called Exploring the future of web apps during which I built my own framework for generating agentic web apps with Angular. A Quick Side Note: While the framework I built for that livestream isn't nearly as flexible or extensible (to use with other web frameworks, for example) as A2UI, the architectural patterns are very similar. If you're still struggling to understand the high-level concepts after reading the A2UI docs and this blog post, give that livestream a watch. The shared concepts will help make it click.What is A2UI? A2UI enables AI agents to generate rich, interactive user interfaces that render natively across web, mobile, and desktop -- without executing arbitrary code. This is exciting to me because A2UI enables: Seamless in-app experiences: Interfaces that adapt dynamically to user intent. Portable UIs: Views that can appear virtually anywhere, serving as a vital part of Gemini web app experiences. Protection: No arbitrary code execution. But to understand A2UI, you first have to understand what it isn't. It's not a framework; it's a protocol. The implications of this are massive. Because it's a protocol, using GenUI doesn't lock you into a single stack. It defines how an LLM agent and a client application communicate about ## How we built a Flutter-powered AI coffee shop DevFeed: [How we built a Flutter-powered AI coffee shop]() Original publisher: [Read original article]() Author: Craig Labenz Published: 2026-06-22T15:16:53Z Content type: article Language: en Sources: [Flutter - Medium]() Topics: [Flutter](), [Artificial Intelligence](), [Firebase](), [monorepo](), [Cloud](), [Deployment](), [Web](), [Android](), [iOS]() Tags: [a2ui](), [ai](), [android](), [app](), [apps](), [cloud](), [code](), [deployment](), [firebase](), [flutter](), [gemini](), [genuis](), [go](), [google](), [hosting](), [ios](), [monorepo](), [web]() ### AI overview The Flutter team describes building GenLatte, a coffee-shop demo that combined a Flutter app with Nano Banana for customized images and GenUI for dynamically generated, personalized questions. The system let visitors order coffee topped with an image of their happy place, and the demo was presented at Cloud Next and Google I/O. ### Source excerpt Dash sits on a coffee shop's checkout counter drinking a latte with the Flutter logo printed on top If you start giving away coffee, people will show up. The Flutter team had been trying for a while to find a way to put this principle to work with a demo that started with a Flutter app and ended with a hot, tasty beverage. The problem was how to make it more interesting, more personal than just taking orders and delivering. Coffee's cool, but it's not The One Thing You Definitely Remember from Google I/O cool. So what changed? Two new bits of tech arrived on scene. One is Nano Banana, with its ability to quickly generate customized images. The second is GenUI, with its ability to generate UX dynamically at runtime and offer attendees personally tailored questions about how they'd like to modify those images. Put the two together with Flutter and you can offer folks the chance to order coffee with an image of their happy place printed on top with an inkjet printer. Now that's pretty memorable. All we had to do was execute. Twice, as it turned out -- the demo was called "GenLatte" at Cloud Next and "Antigravity Coffee Co." at Google I/O. For simplicity and to save a few tokens for the agent summarizing this article for you, the name "GenLatte" is used below. We built a coffee shop Realizing a vision as ambitious as GenLatte involves a lot of people. Like, a lot of people. There are teams to spec out the physical space and decide how "customers" [1] will flow. There are branding and concept teams to create the aesthetic. There are of course construction teams to go to the hardware store and buy lumber. Eventually, there's also the software engineers slapping code together to build the various apps, which is where I happened to come in. This blog post will only outline the software, but that is not to minimize the incredible work that went into the many other layers required for GenLatte to eventually open its doors. [1] Are they still customers if you don't charge anyth