介绍编程智能体如何仅凭单条提示词即可构建完整的 CARTO + deck.gl 应用（包括仪表板、故事地图及以 AI 为先的体验），其中 CARTO 负责性能优化与治理。

How coding agents can now scaffold full CARTO + deck.gl apps (dashboards, story maps, and AI-first experiences) from a single prompt, with CARTO handling performance and governance.

在本篇博文中，我们将逐步介绍 AI 智能体如何生成空间应用（spatial apps）、可组合式扩展（composable extensions）如何将这些应用转化为故事地图（story maps），或转化为用户可与地图直接对话的智能体式体验（agentic experiences），以及支撑 CARTO 平台的安全机制——包括数据保护、凭据管理与访问控制治理。 借助 CARTO for Agents，编码智能体为构建空间应用所执行的第一步，是为其配置安全且范围受限的数据仓库访问权限。它通过 `carto credentials create token` 命令生成一个 API Token，该 Token 仅绑定至该应用实际所需的特定数据表与 API 接口。智能体生成的脚手架是一个真实可用的 CARTO + deck.gl 应用，而非固定模板；其每一层均开放供您自由扩展。 我们来看两个示例提示（prompt），以展示 CARTO CLI、`carto-develop-app` 技能与您的数据仓库凭据如何协同工作，支持编码智能体“即兴编写”（vibe-code）空间应用。 每个行业、每家企业都拥有自身独特的文化、术语与惯例。定制化应用比标准 GIS 地图更能精准反映这些特征。让我们以此理念为基础，将 CARTO 学院（CARTO Academy）中的一则教程，转化为一套完全定制化的零售门店业绩监控仪表盘。以下是所使用的提示： 智能体接收该输入后，即开始逐层拆解任务：从探索数据模式（schema）与数据源，到构建控件（widgets）与筛选器（filters）。我们尤为欣赏的是，智能体调用 `carto-develop-app` 技能自动发现 deck.gl-community/editable-layers 项目，并基于该项目实现“绘制研究区域”（draw an area of study）功能。请注意，它如何无缝融合基于字段列（column-based）与基于空间位置（spatial）的双重筛选逻辑！ 通过自动集成上述能力，智能体显著加速了开发进程，使团队得以在极短时间内——远低于传统周期——将构想转化为可运行的空间应用。 故事地图是将叙事与数据、地图有机融合的最具表现力的方式之一。让我们构建一个故事地图，讲述即将在西班牙发生的日全食（一生仅见的天文奇观！）如何与该国鲜明的人口分布格局产生空间交叠。 数十年来，构建并交付一款真正满足现实世界需求——包括可扩展性、性能与用户体验——的全定制地理空间应用，始终仅限于极少数专业开发者。入门门槛高、前期投入大、长期承诺重，大多数团队难以承担。这一天花板已然消失。当编码智能体与恰当的基础能力（primitives）结合，任何团队均可在一天之内，而非一个季度，交付定制化的地理空间体验。 应用开发正在各行各业快速而深刻地变革；而 CARTO 正是推动地理空间领域实现这一转变的关键技术层。 本文所述全部功能现已向所有 CARTO 用户开放。请安装 CARTO CLI，添加 CARTO Agent Skills，并由您选定的编码智能体驱动开发：随后，只需描述您所需的空间应用类型——仪表盘（dashboard）、单页探索界面（single-page exploration）、嵌入式分析界面（embedded analytics surface）、故事地图（story map），或配有人机对话式 AI 智能体的地图（map paired with an AI Agent that users converse with）——即可见证您的编码智能体基于您的 CARTO 工作区自动组装出完整应用。 欲了解更多信息，请查阅《CARTO for Agents 文档》与《CARTO for Developers 文档》，或联系我们预约演示。 Javier 是 CARTO 首席产品官（Chief Product Officer），在全球范围内负责 CARTO 的产品组合、客户体验及创新路线图。其职责覆盖完整的产品开发与客户体验生命周期。 将 CARTO MCP Server 接入 Microsoft Copilot Studio，让每个团队都能在 Microsoft 365 环境中，以自然语言调用地图、应用与空间分析能力。 我们邀请七款前沿 AI 模型构建 deck.gl 地图，对全部结果进行渲染，并将其中五份方案提交至苏黎世举办的 Open Visualization Summit（开放可视化峰会）。我们从中获得的洞见，以及 deck.gl 对 CARTO 至关重要的原因。

In this blog post we will walk through how AI agents can now generate spatial apps, the composable extensions that turn those apps into story maps or into agentic experiences where users converse with the map, and the CARTO platform elements underneath that keep your data, credentials, and access controls secured and governed. With CARTO for Agents, the first thing a coding agent does for a spatial app is set up secure, scoped access to your data warehouse. It uses carto credentials create token to mint an API token bound to the specific tables and APIs the app actually needs: The scaffold the agent produces is a real CARTO + deck.gl application, not a fixed template, and every layer of it is open for you to extend: Let's look at two example prompts that show how the CARTO CLI, the carto-develop-app skill, and your warehouse's credentials work together when a coding agent vibe-codes spatial apps. Every industry and every company has its own culture, terminology, and conventions. A custom app reflects those better than a standard GIS map. Let's use that idea to transform this tutorial from our CARTO Academy into a completely custom retail store performance monitoring dashboard. This is the prompt we used: The agent takes this input and starts breaking down the pieces: from exploring the schema and data sources to building the widgets and filters. Something we love is how the agent uses the carto-develop-app skill to find the deck.gl-community/editable-layers project, which it then uses to build the "draw an area of study" feature. Note how it incorporates both column-based and spatial filters seamlessly! By assembling these capabilities automatically, the agent dramatically accelerates development and allows teams to move from idea to working spatial application in a fraction of the time. Story maps are one of the most beautiful ways to weave narrative through data and maps. Let's build one to tell the story of how the upcoming total solar eclipse in Spain (a once-in-a-lifetime event!) overlaps with the country's striking population distribution. For decades, building and shipping a fully custom geospatial application that met real-world requirements for scalability, performance, and user experience was the domain of a small handful of specialized developers. Getting started required significant upfront investment and a long-term commitment that most teams could not justify. That ceiling is gone. Pair a coding agent with the right primitives and any team can deliver a custom geospatial experience in a day instead of a quarter. Application development is changing quickly and fundamentally across every industry, and CARTO is the layer making that shift possible for geospatial work. Everything in this post is available now to every CARTO user. Install the CARTO CLI, add the CARTO Agent Skills, and let your coding agent of choice drive: Then describe the spatial app you want: a dashboard, a single-page exploration, an embedded analytics surface, a story map, or a map paired with an AI Agent that users converse with — and watch your coding agent assemble it against your CARTO workspace. Check the CARTO for Agents documentation and CARTO for Developers to learn more, or reach out to us to request a demo. Javier is CARTO's Chief Product Officer and is globally responsible for CARTO’s product portfolio, customer experience, and innovation roadmap. Javier's responsibilities span the complete product development and customer experience cycle. Connect the CARTO MCP Server to Microsoft Copilot Studio and give every team maps, apps, and spatial analysis in plain language, inside Microsoft 365. We asked seven frontier AI models to build deck.gl maps, rendered every result, and took five proposals to the Open Visualization Summit in Zürich. What we learned, and why deck.gl matters so much to CARTO.