I vibe-coded an Android app using Google

marsbit發佈於 2026-05-23更新於 2026-05-23

文章摘要

In a hands-on experience, Google AI Studio's new "prompt to phone" feature allows users to generate functional Android apps using natural language prompts. The author created three apps in one afternoon: a text-based adventure game called MOOD, a calorie counter, and a Super Mario-style game featuring Peach. The process involved describing the app concept, letting Gemini AI generate the code and interface, and then installing it directly onto a connected phone. While the apps were generated and installed quickly, their quality varied significantly. The text adventure was simplistic and buggy, the calorie counter provided inaccurate data due to flawed logic, and the platformer was prone to crashes. The AI could efficiently fix specific, identifiable bugs through follow-up prompts. However, the experience highlighted that while AI can rapidly prototype "working" software, creating reliable, accurate, and polished applications still requires human oversight, judgment, and iteration. The tool dramatically lowers the barrier to entry for personal software creation but doesn't yet replace the need for developer expertise in the final stages of quality and refinement.

Editor's Note: Google AI Studio is bringing AI programming to a more intuitive stage: users are no longer just having models 'write code', but can directly generate an Android application using natural language and install it on a real phone within minutes. From entering a prompt in the browser, to Gemini automatically generating code, designing interfaces, fixing bugs, to the app appearing on the device, the barrier to software development is being lowered even further.

The Verge author Sean Hollister recently experienced the 'prompt to phone' capability of Google AI Studio. He created three apps in one afternoon, including a text adventure game, a calorie calculator, and a Mario-like mini-game, with almost no need to write code himself, and some bugs could be quickly fixed by continuing the conversation. This experience shows that AI programming tools are moving from development environments closer to consumer-facing scenarios for ordinary users.

This is also the most imaginative aspect of the 'personal software revolution.' In the past, ordinary users could only wait for developers to create general products; now, they might be able to generate a fitness tracker, calorie calculator, or even a simple game on the fly according to their specific needs. For Google, this isn't just a demonstration of AI programming capability; it could also be a new entry point for Gemini into the mobile ecosystem, developer community, and subscription revenue.

However, this experience also illustrates that AI-generated applications still have a significant gap to truly mature. It can quickly produce a 'working' program but not necessarily a reliable, accurate, or user-friendly product: game narratives are crude, mechanics are thin, calorie data can be severely miscalculated, and the Mario-like mini-game even crashes repeatedly. More complex issues also include copyright boundaries, data sources, product judgment, and long-term maintenance capabilities.

What's truly worth paying attention to is not whether AI can already replace developers, but that the starting point of software production is changing. Google has proven that it's becoming a reality for ordinary people to create mobile apps using prompts; but from 'generating an app' to 'making a good app,' human professional experience, aesthetic judgment, and continuous iteration are still required in between. AI can significantly accelerate development speed, but the final mile of software quality can't be handed off—at least not yet.

Here is the original article:

Yesterday, I made my first Android app. Then, I made two more—three apps in one afternoon.

For one of the apps, I essentially just typed 148 English words into a web browser and then walked away. Ten minutes later, a brand new, complete app had appeared on my real Android phone. Of course, I did need to prepare the phone beforehand: enable USB debugging mode and connect it to my computer. But aside from that, as Google advertised, AI Studio did almost all the work for me.

I typed, clicked install, and then—voilà—a fully functioning program appeared. At that moment, I was almost ready to agree with David, Allison, and Jen's assessment: the personal software revolution has arrived, and it's entering your phone. In the future, even without programming skills, ordinary people might be able to get complex smart home device systems truly up and running.

Then, I started actually using these three apps: a calorie counter and two games. It turned out, they didn't perform very well. And just as I was beginning to enjoy iterating and trying to improve them, AI Studio reminded me that I had reached my daily usage limit. Next, I would either have to pay or wait for the quota to reset.

So, friction still exists. But there's no denying what an individual can accomplish nowadays is quite astonishing. That same morning, my colleague Stevie Bonifield also made a personal fitness tracker app, and he thought it was good enough to actually use. Faced with Gemini's pop-up prompt to upgrade to a paid plan, my first instinct was actually: 'Should I pay for a few months first?' That's not a reaction I would have expected myself to have towards a Google product.

How Google's AI Studio Builds an Android App

On Tuesday, when Google showed off using AI to write a game similar to Doom, we joked that I should make a game called MOOD. It would be a text adventure game like Doom, with MOOD standing for 'Modern Online Oratory Dungeon.'

Just this information was enough for Google to get to work. After I typed into AI Studio: 'Help me make a Doom-style text adventure game called MOOD, with MOOD standing for Modern Online Oratory Dungeon,' Gemini started automatically supplementing more ideas, trying to expand on my concept. It first typed a sentence: 'The game should feature procedurally generated levels and challenging turn-based combat.'

I didn't want randomly generated levels that were completely different each time—I wanted a classic text adventure where players explore a designed, real map structure. Turn-based combat, though, was acceptable. Maybe the game could also have AI help me auto-generate the map?

Then, Gemini suggested more settings like 'secrets hidden in rooms' and 'a satisfying progression system.' Most of the time, I just nodded along with its ideas.

Before I let it start writing code, the final prompt was this:

Next, it officially went on a full sprint. My colleague Jake pointed out that unlike Claude Code, Gemini doesn't make a plan first and then ask if you want to proceed. It automatically pushes forward—though you can check the code it writes at any time if you want.

One minute later, it had already generated five design prototypes for me:

Twenty minutes later, I pressed the 'Install' button, transferring the game to a Pixel 9 phone.

Unsurprisingly, the writing was terrible. There were also no demons to be seen anywhere. The entire dungeon had only 11 rooms, and players could 'beat' it just by repeatedly mashing the attack button—in under a minute if played seriously. At least now it could; before that, Gemini had to help me fix two critical bugs that made the game unplayable.

Here's MOOD in action:

It wasn't a huge surprise to discover that Gemini's promised 'engaging narrative with branching dialogue options and multiple endings' eventually condensed into a simple branch at the very end of the game: I could defeat the 'Core Orator'—an AI that somehow turns internet anger into corporate profits—by attacking it, fusing with it, or entering a backdoor password.

Furthermore, the game actively exposed all the promised 'secrets' directly to the player: it made them into glowing buttons, and players didn't even need to type any text. When you encounter a glowing treasure chest, the game tries incredibly hard to remind you it's actually a Mimic—the classic Dungeons & Dragons monster that disguises itself as a treasure chest.

It not only explicitly warns you to 'check the chest at your own risk,' but even labels it as an enemy and doesn't let me leave, because the system prompts: 'A hostile ‘Clickbait Mimic’ is blocking the path!'

Speaking of which, MOOD will even tell you the backdoor password needed to unlock the hidden ending when you need it.

However, the bug-fixing process could be surprisingly smooth, provided it was a bug Gemini could correctly identify. When I told it the game got stuck when talking to 'The Whistleblower' because the button to end the conversation was missing, it immediately generated a new version of the app. I pressed 'Install,' the app on my phone restarted automatically, and upon re-entering the game, I found myself right where I left off—only this time, the button I needed was there.

My other apps probably needed more polishing. The calorie counter's best method for determining a food's calories turned out to be calling the paid Gemini API, which I don't have a key for. When I asked it to search for information from other databases instead, I discovered that its estimates for many foods were severely low.

However, when I told Gemini that a 16-ounce boba milk tea couldn't possibly be only 190 calories, it did seem to find that basic mistake in its own code. It previously thought 'milk' was enough to match 'boba milk tea,' and worse, it chose low-calorie 1% milk as the basis for the estimate. Gemini claimed it would now perform more reliable matching.

But even so, my 3-ounce serving of Taiwanese popcorn chicken was just calculated as 140 calories, and I'm pretty sure the real number is at least double that. So, this app clearly needed more work.

Finally, and least importantly, I felt I needed to test: whether Google still allows users to make those terrible Nintendo knock-off games, like my colleague Jay Peters did earlier this year with Project Genie; or whether Google had learned its lesson.

With deep shame, I present to you—Super Peach Rescue:

This is an utterly terrible program. Princess Peach was rendered as some kind of terrifying, one-eyed floating alien, and the game would instantly crash—every single time—if she dared touch any of the power-up blocks. So far, Gemini hasn't been able to figure out why.

Also, the second pipe in the game is completely impassable because Princess Peach simply can't jump that high.

Nevertheless, Gemini didn't hesitate when generating such a game. My request was: 'Make a working Super Mario game where I play as Princess Peach rescuing Mario, with all the elements of a traditional Mario side-scroller.' In a sense, it did.

It even proactively suggested that I could 'give Peach a series of classic Mario power-ups like Super Mushroom, Fire Flower, and Starman.' It also labeled the control scheme as 'NES System.' I think I'll delete this game.

At least, among the two games I made via vibe coding, one was playable from the start and required almost no effort on my part—unless you count the psychological trauma of thinking about how many game developers are now unemployed.

To be clear: I'm actually glad the games I vibe-coded turned out so poor. For a completely free, personally-tailored calorie counter, I might still be able to defend myself: after all, no one would make such a tool just for me. But when it comes to games, I'd rather spend my time supporting actual human creators.

相關問答

QWhat is the core capability demonstrated by Google AI Studio in this article, and what did the author create with it?

AThe article demonstrates Google AI Studio's ability to generate functional Android applications directly from natural language prompts, a process the author refers to as 'vibe coding.' Using this, the author created three applications: a text-based adventure game called 'MOOD,' a calorie counter, and a poorly functioning Super Mario-style game where Princess Peach rescues Mario.

QWhat are some of the main advantages and significant drawbacks of using AI to generate applications as described in the experience?

AAdvantages include drastically lowering the barrier to software creation, allowing non-coders to quickly generate apps tailored to personal needs, and a remarkably smooth bug-fixing process for issues the AI can identify. Major drawbacks are that the generated apps are often unreliable, inaccurate, or have poor quality: the games had thin narratives and mechanics, the calorie counter gave severely low estimates, and the Mario clone crashed frequently. Complex issues like copyright, data sourcing, and long-term maintenance also remain unresolved.

QDescribe the process of creating and installing the 'MOOD' game. What were some of its shortcomings?

AThe author entered a 148-word prompt into Google AI Studio. Gemini expanded on the idea and, without needing prior planning confirmation, generated code and multiple UI prototypes. About 20 minutes later, the author pressed 'Install' to transfer the APK to a connected Pixel 9 phone. The game's shortcomings included terrible writing, only 11 rooms, simplistic combat (just spamming an attack button to win), a lack of demons as suggested by the 'Doom-like' prompt, and a poorly implemented narrative that directly revealed all secrets and gave away puzzle solutions.

QHow did the AI handle bug fixes during the app creation process, according to the author's experience?

AThe bug-fixing process was described as surprisingly smooth for issues the AI could correctly diagnose. For example, when the 'MOOD' game got stuck because a dialog exit button was missing, the author reported the issue. Gemini then generated a new version of the app. After installation, the app restarted on the phone, and the author resumed play from the same point—but with the necessary button now present.

QWhat broader implications does the author suggest this 'personal software revolution' might have, while also highlighting its current limitations?

AThe author suggests this could enable a 'personal software revolution' where individuals can generate apps for specific, niche needs (like a custom fitness tracker or calorie counter) without waiting for developers. For Google, it represents a potential new entry point into mobile, developer ecosystems, and subscription revenue via Gemini. However, the key limitation is the gap between 'generating an app' and 'making a good app.' The author concludes that while AI can accelerate the starting point of development, the 'last mile' of software quality—requiring human expertise, aesthetic judgment, and iteration—cannot yet be handed off to AI.

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什麼是 $S$

什麼是 AGENT S

Agent S:Web3中自主互動的未來 介紹 在不斷演變的Web3和加密貨幣領域,創新不斷重新定義個人如何與數字平台互動。Agent S是一個開創性的項目,承諾通過其開放的代理框架徹底改變人機互動。Agent S旨在簡化複雜任務,為人工智能(AI)提供變革性的應用,鋪平自主互動的道路。本詳細探索將深入研究該項目的複雜性、其獨特特徵以及對加密貨幣領域的影響。 什麼是Agent S? Agent S是一個突破性的開放代理框架,專門設計用來解決計算機任務自動化中的三個基本挑戰: 獲取特定領域知識:該框架智能地從各種外部知識來源和內部經驗中學習。這種雙重方法使其能夠建立豐富的特定領域知識庫,提升其在任務執行中的表現。 長期任務規劃:Agent S採用經驗增強的分層規劃,這是一種戰略方法,可以有效地分解和執行複雜任務。此特徵顯著提升了其高效和有效地管理多個子任務的能力。 處理動態、不均勻的界面:該項目引入了代理-計算機界面(ACI),這是一種創新的解決方案,增強了代理和用戶之間的互動。利用多模態大型語言模型(MLLMs),Agent S能夠無縫導航和操作各種圖形用戶界面。 通過這些開創性特徵,Agent S提供了一個強大的框架,解決了自動化人機互動中涉及的複雜性,為AI及其他領域的無數應用奠定了基礎。 誰是Agent S的創建者? 儘管Agent S的概念根本上是創新的,但有關其創建者的具體信息仍然難以捉摸。創建者目前尚不清楚,這突顯了該項目的初期階段或戰略選擇將創始成員保密。無論是否匿名,重點仍然在於框架的能力和潛力。 誰是Agent S的投資者? 由於Agent S在加密生態系統中相對較新,關於其投資者和財務支持者的詳細信息並未明確記錄。缺乏對支持該項目的投資基礎或組織的公開見解,引發了對其資金結構和發展路線圖的質疑。了解其支持背景對於評估該項目的可持續性和潛在市場影響至關重要。 Agent S如何運作? Agent S的核心是尖端技術,使其能夠在多種環境中有效運作。其運營模型圍繞幾個關鍵特徵構建: 類人計算機互動:該框架提供先進的AI規劃,力求使與計算機的互動更加直觀。通過模仿人類在任務執行中的行為,承諾提升用戶體驗。 敘事記憶:用於利用高級經驗,Agent S利用敘事記憶來跟蹤任務歷史,從而增強其決策過程。 情節記憶:此特徵為用戶提供逐步指導,使框架能夠在任務展開時提供上下文支持。 支持OpenACI:Agent S能夠在本地運行,使用戶能夠控制其互動和工作流程,與Web3的去中心化理念相一致。 與外部API的輕鬆集成:其多功能性和與各種AI平台的兼容性確保了Agent S能夠無縫融入現有技術生態系統,成為開發者和組織的理想選擇。 這些功能共同促成了Agent S在加密領域的獨特地位,因為它以最小的人類干預自動化複雜的多步任務。隨著項目的發展,其在Web3中的潛在應用可能重新定義數字互動的展開方式。 Agent S的時間線 Agent S的發展和里程碑可以用一個時間線來概括,突顯其重要事件: 2024年9月27日:Agent S的概念在一篇名為《一個像人類一樣使用計算機的開放代理框架》的綜合研究論文中推出,展示了該項目的基礎工作。 2024年10月10日:該研究論文在arXiv上公開,提供了對框架及其基於OSWorld基準的性能評估的深入探索。 2024年10月12日:發布了一個視頻演示,提供了對Agent S能力和特徵的視覺洞察,進一步吸引潛在用戶和投資者。 這些時間線上的標記不僅展示了Agent S的進展,還表明了其對透明度和社區參與的承諾。 有關Agent S的要點 隨著Agent S框架的持續演變,幾個關鍵特徵脫穎而出,強調其創新性和潛力: 創新框架:旨在提供類似人類互動的直觀計算機使用,Agent S為任務自動化帶來了新穎的方法。 自主互動:通過GUI自主與計算機互動的能力標誌著向更智能和高效的計算解決方案邁進了一步。 複雜任務自動化:憑藉其強大的方法論,能夠自動化複雜的多步任務,使過程更快且更少出錯。 持續改進:學習機制使Agent S能夠從過去的經驗中改進,不斷提升其性能和效率。 多功能性:其在OSWorld和WindowsAgentArena等不同操作環境中的適應性確保了它能夠服務於廣泛的應用。 隨著Agent S在Web3和加密領域中的定位,其增強互動能力和自動化過程的潛力標誌著AI技術的一次重大進步。通過其創新框架,Agent S展現了數字互動的未來,為各行各業的用戶承諾提供更無縫和高效的體驗。 結論 Agent S代表了AI與Web3結合的一次大膽飛躍,具有重新定義我們與技術互動方式的能力。儘管仍處於早期階段,但其應用的可能性廣泛且引人入勝。通過其全面的框架解決關鍵挑戰,Agent S旨在將自主互動帶到數字體驗的最前沿。隨著我們深入加密貨幣和去中心化的領域,像Agent S這樣的項目無疑將在塑造技術和人機協作的未來中發揮關鍵作用。

803 人學過發佈於 2025.01.14更新於 2025.01.14

什麼是 AGENT S

如何購買S

歡迎來到HTX.com!在這裡,購買Sonic (S)變得簡單而便捷。跟隨我們的逐步指南,放心開始您的加密貨幣之旅。第一步:創建您的HTX帳戶使用您的 Email、手機號碼在HTX註冊一個免費帳戶。體驗無憂的註冊過程並解鎖所有平台功能。立即註冊第二步:前往買幣頁面,選擇您的支付方式信用卡/金融卡購買:使用您的Visa或Mastercard即時購買Sonic (S)。餘額購買:使用您HTX帳戶餘額中的資金進行無縫交易。第三方購買:探索諸如Google Pay或Apple Pay等流行支付方式以增加便利性。C2C購買:在HTX平台上直接與其他用戶交易。HTX 場外交易 (OTC) 購買:為大量交易者提供個性化服務和競爭性匯率。第三步:存儲您的Sonic (S)購買Sonic (S)後,將其存儲在您的HTX帳戶中。您也可以透過區塊鏈轉帳將其發送到其他地址或者用於交易其他加密貨幣。第四步:交易Sonic (S)在HTX的現貨市場輕鬆交易Sonic (S)。前往您的帳戶,選擇交易對,執行交易,並即時監控。HTX為初學者和經驗豐富的交易者提供了友好的用戶體驗。

1.6k 人學過發佈於 2025.01.15更新於 2025.03.21

如何購買S

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