90 lines
4.8 KiB
Markdown
90 lines
4.8 KiB
Markdown
---
|
||
title: "Nexus Spatial: Full Agency Discovery Exercise"
|
||
type: source
|
||
tags: [multi-agent, spatial-computing, product-discovery, agency]
|
||
date: 2026-03-05
|
||
---
|
||
|
||
## Source File
|
||
- [[raw/Agent/agency-agents/examples/nexus-spatial-discovery.md]]
|
||
|
||
## Summary
|
||
- 核心主题:Nexus Spatial 产品发现演练,AI Agent 指挥中心在空间计算中的应用
|
||
- 问题域:AI 工作流可视化、Agent 编排监控、空间计算企业应用
|
||
- 方法/机制:8个专业 Agent 并行部署,覆盖产品、技术、品牌、GTM、UX、执行计划等全维度
|
||
- 结论/价值:验证"2D优先、空间其次"策略,WebXR 优于 VisionOS,调试是核心用例
|
||
|
||
## Key Claims
|
||
- AI 编排工具市场 2026 年达 $13.5B,22%+ CAGR
|
||
- 自主 AI Agent 市场到 2030 年将增长至 $50.3B(45.8% CAGR)
|
||
- 所有现有 AI 工作流工具都是扁平 2D 仪表盘,无产品处于"空间+AI"交叉点
|
||
- Vision Pro 全球装机量约 100 万台,销售较发布时下降 95%,不应作为首选平台
|
||
- WebXR 是分发解锁:Safari 2025 年底采用 WebXR Device API,2026 年采用率增长 40%
|
||
- 空间计算只在**结构化任务**(放置、连接、重新排列节点)上增加价值,在**参数任务**(文本输入、配置)上产生摩擦
|
||
- 调试是杀手级用例:运行时追踪的空间叠加是 3D 真正超越 2D 的场景
|
||
|
||
## Key Quotes
|
||
> "Products are either spatial-but-not-AI-focused, or AI-focused-but-flat-2D. No product sits at the intersection." — Product Trend Researcher
|
||
> "If 2D is clearer, use 2D. Every review should ask: 'Would this be better flat?'" — UX Researcher
|
||
> "Debugging is the killer use case." — 跨 Agent 一致结论
|
||
|
||
## Key Concepts
|
||
- [[Spatial AI Operations]](SpatialAIOps):Nexus Spatial 创建的新类别,AI 操作的空间化
|
||
- [[Multi-Agent Orchestration]]:多 Agent 编排,Rust 作为高性能 DAG 执行语言
|
||
- [[2D-First Spatial-Second]]:2D 优先、空间其次的产品策略
|
||
- [[WebXR Distribution]]:WebXR 作为分发解锁,浏览器沉浸式体验
|
||
- [[Progressive Disclosure]]:渐进式披露,新用户从近乎 2D 开始,逐步揭示空间能力
|
||
- [[Spatial Truthfulness]]:品牌价值观,诚实展示系统状态
|
||
|
||
## Key Entities
|
||
- [[Nexus Spatial]]:AI Agent 指挥中心,VisionOS + WebXR 应用
|
||
- [[The Agency]]:执行此次发现演练的 Agent 团队
|
||
- [[Vision Pro]]:Apple 空间计算设备,装机量约 100 万台,不作为首选平台
|
||
- [[WebXR]]:W3C 浏览器标准,用于沉浸式 VR/AR 体验
|
||
- [[LangChain/LangSmith]]:竞品,$39/月,扁平仪表盘
|
||
- [[CrewAI]]:竞品,10万+ 开发者,CLI 优先
|
||
- [[n8n]]:竞品,$20-50/月,2D 画布难以处理 Agent 关系
|
||
- [[Rust]]:编排引擎语言,选择原因:亚毫秒调度、零 GC 暂停、内存安全
|
||
|
||
## Connections
|
||
- [[Spatial AI Operations]] ← defined_by ← [[Nexus Spatial]]
|
||
- [[Nexus Spatial]] ← depends_on ← [[WebXR]]
|
||
- [[Nexus Spatial]] ← depends_on ← [[Multi-Agent Orchestration]]
|
||
- [[Multi-Agent Orchestration]] ← extends ← [[Rust]]
|
||
- [[2D-First Spatial-Second]] ← contradicts ← [[Vision Pro]] (不作为首发平台)
|
||
- [[WebXR]] ← enables ← [[Progressive Disclosure]]
|
||
|
||
## Contradictions
|
||
- 与 Vision Pro 预期冲突:
|
||
- 冲突点:Apple 押注 Vision Pro,但装机量不足以支撑业务
|
||
- 当前观点:WebXR 优先,VisionOS 最后
|
||
- 对方观点:空间计算需要原生 VisionOS 体验
|
||
- 与"空间优先"品牌定位冲突:
|
||
- 冲突点:Brand Guardian 希望以空间为主打
|
||
- 当前观点:2D 演示中确保空间可见,但产品首先要是优秀的 2D 工具
|
||
- 对方观点:领先发布空间体验作为差异化
|
||
|
||
## Pricing Tiers
|
||
| Tier | Price | Target |
|
||
|------|-------|--------|
|
||
| Explorer | Free | 3 agents, WebXR viewer |
|
||
| Pro | $99/user/month | 25 agents, collaboration |
|
||
| Team | $249/user/month | Unlimited agents, analytics |
|
||
| Enterprise | $2K-10K/month | SSO, RBAC, on-prem, SLA |
|
||
|
||
## Technical Architecture
|
||
- 8-service 架构:Auth, Workspace, Workflow, Orchestration (Rust), Collaboration (Yjs CRDT), Streaming (WS), Plugin, Billing
|
||
- 数据层:PostgreSQL 16, Redis 7 Cluster, S3, ClickHouse, NATS
|
||
- AI Provider Tier:OpenAI, Anthropic, Google, Local Models, Custom Plugins
|
||
|
||
## Phased Strategy
|
||
1. **Months 1-6:** 2D web dashboard + Three.js 2.5D,50 付费团队,$60K MRR
|
||
2. **Months 6-12:** WebXR 空间模式,200 团队,$300K MRR
|
||
3. **Months 12-18:** Native VisionOS(仅在空间需求验证后),500 团队,$1M+ MRR
|
||
|
||
## Cross-Agent Synthesis Insights
|
||
- 8 个专业 Agent 并行工作,各自在领域内深度研究
|
||
- 所有 Agent 独立得出相同结论:"2D 优先,空间其次"
|
||
- Product Trend Researcher 发现了 Vision Pro 严峻销售数据
|
||
- Backend Architect 选择了 Rust 编排引擎
|
||
- Brand Guardian 创建了" SpatialAIOps"类别 |