feat(wiki): ingest nexus-spatial-discovery — 8-agent product discovery exercise
Ingest raw/Agent/agency-agents/examples/nexus-spatial-discovery.md Source: 8 The Agency agents parallel discovery exercise for Nexus Spatial Products: AI spatial command center (SpatialAIOps category) Key findings: 2D-first/WebXR strategy, debugging as killer use case Entities created: Nexus-Spatial, CrewAI Concepts created: SpatialAIOps, Command-Theater-Interface, Debugging-Visualization, Semantic-Zoom, Growth-Loop
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wiki/concepts/Command-Theater-Interface.md
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wiki/concepts/Command-Theater-Interface.md
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---
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title: "Command Theater Interface"
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type: concept
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tags: [spatial-computing, xr, interface-design, ux]
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last_updated: 2026-03-05
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---
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## Definition
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命令剧院（Command Theater）——以用户为中心的空间界面布局范式，以弧形剧场形式围绕用户组织内容。源自 [[nexus-spatial-discovery]] 中 [[XR-Interface-Architect]] 的设计。
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## Architecture
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```
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OVERVIEW CANOPY
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(pipeline topology)
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~~~~~~~~~~~~~~~~~~~~~~~~
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/ \
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/ FOCUS ARC (120 deg) \
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/ primary node graph work \
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/________________________________\
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| |
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LEFT | USER POSITION | RIGHT
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UTILITY | (origin 0,0,0) | UTILITY
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RAIL | | RAIL
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|__________________________________|
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\ /
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\ SHELF (below sightline) /
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\ agent status, quick tools/
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\_________________________ /
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```
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## Four Zones
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| Zone | Position | Content |
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|------|----------|---------|
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| Focus Arc | 120°, 1.2-2.0m | Primary node graph workspace |
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| Overview Canopy | above, 2.5-4.0m | Miniature pipeline topology + health heatmap |
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| Utility Rails | left/right flanks | Agent library, monitoring, logs |
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| Shelf | below sightline, 0.8-1.0m | Run/stop, undo/redo, quick tools |
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## Three-Layer Depth System
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| Layer | Depth | Content | Opacity |
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|-------|-------|---------|---------|
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| Foreground | 0.8-1.2m | Active panels, inspectors, modals | 100% |
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| Midground | 1.2-2.5m | Node graph, connections, workspace | 100% |
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| Background | 2.5-5.0m | Overview map, ambient status | 40-70% |
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## Design Rationale
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- 用户处于中心，信息按重要性和使用频率分层
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- z-axis（深度）对应执行顺序：input nodes 最远，output nodes 最近
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- 减少晕动症：所有交互发生在 0.8-2.5m 范围
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- 与 [[Semantic-Zoom]] 配合实现渐进式空间复杂度
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## Related Concepts
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- [[Semantic-Zoom]]：与 Command Theater 配合的导航范式
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- [[SpatialAIOps]]：Command Theater 的应用场景
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- [[Nexus-Spatial]]：Command Theater 的产品实现
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wiki/concepts/Debugging-Visualization.md
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wiki/concepts/Debugging-Visualization.md
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---
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title: "Debugging Visualization"
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type: concept
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tags: [spatial-computing, debugging, ux, multi-agent]
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last_updated: 2026-03-05
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---
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## Definition
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调试可视化（Debugging Visualization）——通过空间叠加将运行时追踪信息直接叠加在工作流结构之上，提供 3D 可视化的调试体验。
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由 [[nexus-spatial-discovery]] 中 [[UX-Researcher]] 识别为 **杀手级用例（Killer Use Case）**。
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## Why It's the Killer Use Case
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1. **Real quantified pain point**：用户花费 40% 时间通过日志检查调试 Agent 失败（[[nexus-spatial-discovery]] 用户画像数据）
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2. **2D tools handle it poorly**：现有 2D 工具无法有效可视化复杂的 Agent 执行追踪
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3. **3D uniquely suited**：工作流结构（节点+连接）+ 运行时数据（时间序列/调用栈/token消耗）天然适合 3D 叠加
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## UX Research Finding
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> "Debugging Is the Killer Use Case. Spatial overlay of runtime traces on workflow structure solves a real, quantified pain point that no 2D tool handles well." — [[UX-Researcher]]
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[[Product-Trend-Researcher]] 和 [[XR-Interface-Architect]] 均独立得出相同结论。
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## Implementation in Nexus Spatial
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- 7 种 Agent 状态可视化：Idle / Queued / Running / Streaming / Completed / Error / Paused
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- 状态通过边缘光晕、内饰动画、声音、粒子系统区分
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- LOD 节点系统：hover 显示最近 I/O，selected 显示完整追踪
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## Key Design Insight
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空间计算对**结构性**任务（放置、连接、重排节点）增加价值，但对**参数性**任务（文本输入、配置）制造摩擦。界面必须无缝混合空间和 2D 模式——2D 面板锚定在空间位置。
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## Related Concepts
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- [[Command-Theater-Interface]]：调试可视化的界面容器
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- [[Semantic-Zoom]]：调试视图的导航模式
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- [[SpatialAIOps]]：调试可视化是 SpatialAIOps 的核心差异化
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- [[Nexus-Spatial]]：调试可视化作为核心功能
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wiki/concepts/Growth-Loop.md
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wiki/concepts/Growth-Loop.md
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---
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title: "Growth Loop"
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type: concept
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tags: [growth, product, go-to-market, viral]
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last_updated: 2026-03-05
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---
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## Definition
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增长飞轮（Growth Loop）——产品内生的自我强化增长机制，用户行为直接产生新用户的引入，而非依赖外部广告或营销渠道。
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由 [[nexus-spatial-discovery]] 中 [[Growth-Hacker]] 设计 4 大增长飞轮。
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## The 4 Nexus Spatial Growth Loops
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### 1. "Wow Factor" Demo Loop
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**机制**：空间演示天然可分享。一键"Share Spatial Preview"生成 WebXR 链接或视频。
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**目标 K-factor**：0.3-0.5
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**核心洞察**：空间计算的分享性（immersive demos are inherently shareable）
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### 2. Template Marketplace
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**机制**：高级用户发布管道模板，可通过搜索发现，引流新注册
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**核心洞察**：用户既是消费者也是创造者，内容自增长
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### 3. Collaboration Seat Expansion
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**机制**：一个工程师采用 → 分享给队友 → 团队扩展到付费计划（Slack/Figma 增长模式）
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**核心洞察**：协作工具的网络效应
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### 4. Integration-Driven Discovery
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**机制**：在 LangChain、n8n、OpenAI/Anthropic 合作伙伴目录中列出
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**核心洞察**：嵌入用户已有工作流，成为默认选择
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## Growth Loop vs Traditional Acquisition
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| | Growth Loop | Traditional Acquisition |
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|--|------------|----------------------|
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| 依赖 | 产品内生 | 外部渠道 |
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| 规模效应 | 越用越强 | 边际递减 |
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| 成本 | 递减 | 递增 |
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| 可持续性 | 高 | 低 |
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## Related Concepts
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- [[Nexus-Spatial]]：Growth Loop 的应用场景
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- [[SpatialAIOps]]：空间分享性是"Wow Factor"飞轮的基础
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wiki/concepts/Semantic-Zoom.md
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wiki/concepts/Semantic-Zoom.md
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---
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title: "Semantic Zoom"
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type: concept
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tags: [spatial-computing, navigation, ux, xr]
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last_updated: 2026-03-05
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---
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## Definition
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语义缩放（Semantic Zoom）——4 级导航范式，随用户缩放层级揭示不同粒度的信息，类似 iPad/iOS 地图的缩放交互但应用于工作流导航。
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由 [[nexus-spatial-discovery]] 中 [[XR-Interface-Architect]] 定义。
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## Four Levels
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| Level | What You See | Use Case |
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|-------|-------------|---------|
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| Fleet View | All workflows as abstract shapes, color-coded by status | Overview, portfolio management |
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| Workflow View | Node graph with labels and connections | Building, editing workflows |
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| Node View | Expanded configuration, recent I/O, status metrics | Inspection, configuration |
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| Trace View | Full execution trace with data inspection | Debugging, root cause analysis |
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## Design Principles
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1. **Glanceable Before Inspectable**：关键信息在 2 秒内通过颜色/大小/运动/位置感知
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2. **Progressive Spatial Complexity**：新用户从接近 2D 开始，空间能力随信心增长逐步揭示
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3. **Smooth transitions**：Overview → Focus 600ms，Focus → Detail 500ms，最大 600ms
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## Relation to Command Theater
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- Fleet View 对应 Overview Canopy（大范围，高空俯瞰）
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- Workflow/Node View 对应 Focus Arc（主要工作区）
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- Trace View 对应 Utility Rails（详细日志/追踪面板）
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## Related Concepts
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- [[Command-Theater-Interface]]：Semantic Zoom 的空间容器
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- [[Debugging-Visualization]]：Trace View 层级的主要应用
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- [[SpatialAIOps]]：Semantic Zoom 是 SpatialAIOps 导航的核心模式
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- [[Nexus-Spatial]]：Semantic Zoom 作为核心导航范式
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wiki/concepts/SpatialAIOps.md
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wiki/concepts/SpatialAIOps.md
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---
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title: "SpatialAIOps"
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type: concept
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tags: [spatial-computing, ai-operations, product-strategy, spatial-ai]
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last_updated: 2026-03-05
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---
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## Definition
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Spatial AI Operations（空间AI运营）——将空间计算引入 AI Agent 编排和监控的全新产品品类。Nexus Spatial 创造性定义了此品类，而非在已有的 AI 可观测性仪表板赛道竞争。
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核心价值主张：将监控从"阅读仪表板"转变为"身临其境你的基础设施"。
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## Core Characteristics
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- **Immersive monitoring**：通过空间界面实时监控 AI Agent 执行，而非 2D 图表/日志
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- **3D orchestration**：通过 3D 节点图构建和编排 Agent 工作流
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- **Spatial collaboration**：团队进入共享 3D 空间协作进行事故响应
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- **Debugging overlay**：运行时追踪叠加于工作流结构的 3D 可视化调试
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## Market Context
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由 [[nexus-spatial-discovery]] 中的 [[Product-Trend-Researcher]] 和 [[Brand-Guardian]] 共同验证：
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- AI 编排工具市场：$13.5B（22.3% CAGR）
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- 空间计算市场：$170-220B
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- **gap**：现有产品要么是空间型但非 AI，要么是 AI 型但仅 2D
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## Canonical Use Case
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Nexus Spatial 的产品定位：AI Agent 沉浸式 3D 命令中心
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- 3D 节点图可视化 Agent 管道
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- 实时监控空间面板
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- 3D 空间拖放构建工作流
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- 共享空间协作
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## Related Concepts
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- [[Spatial-Computing]]：底层空间计算技术基础
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- [[WebXR]]：SpatialAIOps 的主要分发平台
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- [[Command-Theater-Interface]]：SpatialAIOps 的核心界面模式
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- [[Debugging-Visualization]]：SpatialAIOps 的杀手级用例
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- [[Semantic-Zoom]]：SpatialAIOps 的导航范式
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## Contradictions
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- 与传统 [[Multi-Agent-System-Reliability]] 的监控方法：后者依赖日志/追踪面板，前者通过空间叠加提供直观可穿戴的监控体验
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