过去几年，AI 创作工具的边界被不断扩张：从 ChatGPT 让写作大众化，到 Midjourney 和 Sora 让平面设计与视频创作门槛骤降，如今内容生产的最后一块高地，正在指向游戏。
游戏是最复杂的创作形式之一，融合了叙事、逻辑、美术、音效与交互设计等。它需要团队协作和数以万行的代码，也因此长期是“AI 无法完全接管”的领域。但 2025 年，情况开始发生变化。
Gambo 称自己为 “世界上第一个 Game Vibe Coding Agent”。用户只需描述游戏类型、主题或风格，AI 就会自动生成场景、角色、交互与音效，并把这些内容编织成一个可玩的世界。
而与多数 AI 工具强调创意民主化不同，Gambo 把“商业化效率”与“创作自由”放在同等位置：它既想让每个人都能轻松做出游戏，也希望让游戏创作从一开始（day 1）就具备收益逻辑。
具体来说，Gambo 通过一个强大的 AI 游戏代理与内置广告系统，让创作者可以在第一天就将玩家转化为收入来源。这里先打个预防针，这个功能还没上线。
不过，AI 介入创作也让更多新的问题浮现。AI 生成的关卡与剧情是否足够连贯？素材版权、逻辑脚本、音效风格这些内容的归属如何界定？在追求“效率优先”的系统中，创意是否会被算法的模板化思维替代？
这些问题至今没有定论。Gambo 让游戏创作的门槛骤降，也让“创作本身”的定义再次变得模糊。
带着这些疑问，我们尝试在 Gambo 的网页端进行了实际体验。从输入第一个提示词开始，看它究竟能把一个想法，变成怎样的游戏世界。
实测 Gambo
进入 Gambo 主页，会发现它和一众 no-code 应用一模一样，左边是项目列表，右边一个对话框，甚至还少了点功能选项。
比较特别的就是右下角的能力选项，tokens 消耗更少速度更快的标准模式和消耗更多质量更好的专家模式。
任务一：涂鸦跳跃
我们先尝试在标准模式下，生成一款 iPhone4 时期流行的远古游戏：涂鸦跳跃。
prompts:
Create a simple 2D arcade game inspired by *Doodle Jump*.
Core Gameplay:
- The player controls a small character that continuously bounces upward.
- The goal is to jump from platform to platform without falling.
- The game scrolls upward automatically as the player climbs higher.
- The player dies when falling off the screen bottom.
Mechanics:
- Use keyboard arrows (← →) or mobile tilt to move left/right.
- Randomly generate platforms as the player goes up.
- Add bonus elements like:
- Springs (extra jump)
- Moving platforms
- Breakable platforms
- Monsters to avoid
- Jetpack for temporary flight
Scoring:
- Score increases with height.
- Show current score and best score.
Visual Style:
- Hand-drawn doodle aesthetic (white background, notebook lines).
- Simple color palette (green, blue, brown, white).
Sound:
- Add simple jump sound and background music loop.
Extra:
- Responsive layout for both desktop and mobile.
- Restart button on game over.
生成速度比想象中慢，12 分钟后，游戏成功生成。背景是白纸线条、平台是铅笔手绘、弹簧和喷气背包一应俱全，甚至还有得分系统。整个逻辑结构干净，几乎就是一款可以直接上线的小游戏。
但当我让主角一路往上跳时，问题出现了，到高空后游戏开始掉帧，或者出现上方没有平台可以继续跳的情况。
当我提出问题后，Gambo 自动寻找，发现 bug 在 DoodleJumpScene.ts 文件里并指出原因。它认为游戏在高空会重复生成平台，每帧可能刷出二十多个对象，清理逻辑又太保守，导致平台越积越多。接着，它添加了性能监控、写了激进清理策略，把重复的检查函数合并成一套逻辑。
此外，和那些以代码生成为主的 AI Coding 工具不同，Gambo 会更加注重游戏资产。它不仅在后台生成逻辑脚本，还会主动整理出项目所需的图片、动画、音效资源，并在界面上单独列出一个「Assets」模块。但很可惜，在资产模块里，用户并不能修改元素，还是需要回到对话框进行修改。
涂鸦跳跃测试了 Gambo 的碰撞检测、物理引擎等功能，接下来让 Gambo 做一款视觉小说类游戏，测试其文本叙事、多分支逻辑、素材引用（背景图、角色立绘、音乐） 等层面的生成能力。
任务二：AI 面试物语
随后我决定测试一个更复杂的场景：让 AI 写一款关于“面试进入 AI 公司”的视觉小说。Prompt 里有三个章节——OpenAI、xAI、Anthropic，每一关考验玩家不同的思维维度：安全、自由、伦理。
prompts:
Create a 2D visual novel game titled **"The AI Interview Saga"**.
Theme:
You are an ambitious developer trying to join one of the top AI companies.
There are three main interview stages — OpenAI, xAI, and Anthropic — each with different cultures, tests, and endings.
Gameplay:
- The player goes through three interview "chapters":
- OpenAI — tests creativity and safety awareness.
- xAI — tests boldness and philosophical reasoning.
- Anthropic — tests ethics and collaboration.
- In each stage, the player faces 2–3 dialogue choices that affect the company’s impression and lead to multiple endings.
- Choices influence hidden “AI Alignment Points” that determine which company (if any) will hire you at the end.
Story Structure:
- Intro Scene: The protagonist receives three interview invitations.
- OpenAI Interview Scene: Questions about model alignment, hallucination control, and creativity limits.
- xAI Interview Scene: A more chaotic and philosophical dialogue about AGI, freedom, and Mars.
- Anthropic Interview Scene: Focus on cooperation, AI safety, and human feedback.
- Ending Scene:
- "Hired by OpenAI" — Stable, ethical ending.
- "Hired by xAI" — Bold but unpredictable ending.
- "Hired by Anthropic" — Peaceful, idealistic ending.
- "Rejected by all" — Neutral reflective ending.
Visual & Asset Design:
- Backgrounds:
- OpenAI HQ: futuristic office with soft blue lighting and glass panels.
- xAI HQ: minimalist black room with glowing red server racks.
- Anthropic HQ: warm-toned studio with greenery and sunlight.
- Characters:
- Player (customizable name).
- Three interviewers with distinct looks matching each company style.
- UI Elements:
- Text box with name tag and branching dialogue options.
- Display alignment score subtly in the corner.
- Sound & Music:
- Calm ambient background for OpenAI.
- Techno-synth for xAI.
- Acoustic piano and birds for Anthropic.
Extra Features：
- Add smooth fade transitions between scenes.
- Show “Your Alignment Path” at the end with a score breakdown.
- Include Restart and Save options.
- Responsive for desktop and mobile.
Visual Style:
- Semi-realistic anime or comic style, color palette changes by company:
- OpenAI → blue & silver
- xAI → red & black
- Anthropic → green & beige
第一次生成的结果堪称惊艳，画面风格契合三家公司的气质，场景切换自然，但也 bug 频出比如界面重叠、选项无响应、剧情分支无效，无论我选哪个答案，故事都往同一个结局滑去。
但好在，通过一轮对话就，Gambo 就能理解用户的需求成功修改 bug。
任务三：AI 模拟
最后，我们尝试使用 Gambo 的专家模式，制作一款更复杂的游戏——《AI City Simulator》。
prompts:
Create a complex 2D simulation and strategy game titled **"AI City Simulator"**.
Theme:
In a near-future world, the player is assigned to manage an autonomous AI-driven city.
Your goal is to balance progress, ethics, and resources — deciding how much control to give to the AI systems that run the city.
Core Gameplay:
- The player manages city systems: Energy ⚡, Population 👥, AI Research 🧠, and Morality ❤️.
- Each turn (or real-time tick), the player makes decisions that affect these four metrics.
- The city evolves visually as AI systems grow more advanced or unstable.
- Random events challenge the player’s policies: data leaks, protests, energy crises, rogue AI labs, etc.
- Multiple endings based on city alignment:
- “Utopia” (balanced growth)
- “Technocracy” (AI dominance)
- “Collapse” (moral failure)
- “Resistance” (humans reclaim control)
Mechanics:
- Display a dashboard UI showing:
- Stats: energy, population, AI level, morale, pollution.
- Choices: 3 policy buttons per turn (e.g. "Expand Data Centers", "Implement AI Law", "Boost Green Tech").
- Each choice triggers immediate feedback and updates the city visuals.
- Add a time system (morning/day/night cycle) and an “AI consciousness meter” that grows with each policy.
- Add alerts and notifications for critical events.
- Include save/load system.
Visual & Asset Design:
- Backgrounds:
- Futuristic city skyline (day/night versions)
- Control room with holographic dashboard
- AI core chamber glowing with energy
- Characters:
- The player (city governor)
- AI Advisor (holographic avatar with changing colors based on trust)
- Citizen group representatives
- Visual progression:
- The city gradually fills with neon lights, drones, and data streams.
- If AI dominance rises, human elements fade visually.
- Sound:
- Ambient synth music for normal gameplay
- Tense glitch sound when AI level > 80%
- Victory/Failure tracks for endings
Logic & Progression:
- Add at least 10 random events with branching options and visual reactions.
- Every 5 turns, trigger a major policy debate scene between the player and the AI advisor.
- Add persistent variables: `ai_trust`, `morality`, `efficiency`.
- The final ending depends on their combination.
Extra Features:
- Responsive layout for desktop and mobile.
- Autosave every 3 turns.
- “Simulation Speed” slider (1x, 2x, 4x).
- Optional “Cinematic Mode” for end sequences.
- Include credits screen and restart option.
Art Style:
Minimalist cyberpunk with neon blues, purples, and oranges.
Combine flat 2D graphics with light particle effects for data streams.
Goal:
Create a visually rich, replayable AI simulation game that blends management mechanics with moral choices and emergent storytelling.
这是一款近未来城市管理类游戏，玩家要在一个由 AI 运行的都市中维持能源、人口、AI 研究与道德四项指标的平衡。
每回合可以在多种政策间抉择，如“扩建数据中心”“实施 AI 法案”“投资绿色科技”。不同的选择会改变城市状态，并触发诸如数据泄漏、能源危机、AI 抗议等事件。此外，在游戏中还会出现一些随机事件，比如发现外星信号时，你会如何抉择。
游戏中有一个会不断成长的 AI 顾问。起初它只是提供建议，后来会质疑你的决策，当 AI 信任值超过 80%，它甚至会试图接管城市。游戏拥有四种结局，从 AI 统治下的技术独裁，到人类重新掌控的抵抗路线。
画面延续了 Gambo 一贯的极简赛博风：蓝橙霓虹的城市、实时变化的背景、合成器音乐随数值波动而变。整体气氛冷静又充满张力。
如果说《涂鸦跳跃》测试了 Gambo 的物理引擎，《AI 面试物语》检验了它的文本叙事与分支逻辑，那么《AI City Simulator》则真正挑战了系统复杂度。它不仅要生成 UI 与数值逻辑，还要在此之上组织出有节奏感的动态叙事结构，让 AI 不只是写游戏，而是在模拟一座“被 AI 管理的世界”。
游戏网址：https://kroggaah.gambo.games/
从物理碰撞简单的跳跃游戏，到分支复杂的视觉小说，再到需要数值系统、事件系统与状态机协同的城市模拟，我们基本摸清了 Gambo 的定位与边界。它将关卡生成、状态管理、事件总线、资产管线和基础 UI 封装成可复用的链路，能在网页端稳定地产出可玩原型。与此同时，早期产品的典型问题也清晰浮现：高负载场景的帧率波动、分支回路偶发失效、资产难以直接编辑，内置广告变现尚未落地。
与 Cursor 这类通用 AI Coding 工具相比，Gambo 的优势不在于"更聪明"，而在于"更有边界"。它用一套预置的默认方案将不确定性压到最低：生成的不是散落的代码片段，而是可直接运行的关卡、状态与资产管线。这使它在从零到一阶段更像一个专用生产 Agent，显著减少胶水工程与领域摸索的时间，适合玩法验证、风格探索与快速调参。
换句话说，Gambo 能做的 Cursor 同样能做，但路径与成本不同，Gambo 将"能不能做"的问题改写为"多快能做出可玩版本"。
放在更大趋势来看，AI Coding 也许正在加速"垂直化"，将领域默认方案、工程套路、运行时与验收标准直接固化进工具，尤其适合那些领域知识已可模板化的场景。就像有些工程师专精游戏，有些专精数据库——AI Coding 为什么一定要通用呢？
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