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제품 팀과 협력하는 CPO 대리자

고급

이것은Project Management, AI Chatbot분야의자동화 워크플로우로, 18개의 노드를 포함합니다.주로 Agent, AgentTool, ToolThink, ChatTrigger, LmChatOpenAi 등의 노드를 사용하며. 사용법 OpenAI O3와 GPT-4.1-mini 대리인을 통해 CPO 주도의 AI 팀을 사용하여 제품 구축

사전 요구사항
  • OpenAI API Key
워크플로우 미리보기
노드 연결 관계를 시각적으로 표시하며, 확대/축소 및 이동을 지원합니다
워크플로우 내보내기
다음 JSON 구성을 복사하여 n8n에 가져오면 이 워크플로우를 사용할 수 있습니다
{
  "meta": {
    "instanceId": "12e6f290a974a1eee154f8d915aade185e90e826260e6aeab8a087ba7386a1bc",
    "templateCredsSetupCompleted": true
  },
  "name": "CPO Agent with Product Team",
  "nodes": [
    {
      "id": "product-chat-trigger",
      "name": "채팅 메시지 수신 시",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
        -2864,
        -576
      ],
      "webhookId": "product-webhook-id",
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.1
    },
    {
      "id": "cpo-agent",
      "name": "CPO 에이전트",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        -2640,
        -816
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 2.1
    },
    {
      "id": "product-think",
      "name": "사고",
      "type": "@n8n/n8n-nodes-langchain.toolThink",
      "position": [
        -2512,
        -496
      ],
      "parameters": {},
      "typeVersion": 1.1
    },
    {
      "id": "pm-agent",
      "name": "제품 매니저",
      "type": "@n8n/n8n-nodes-langchain.agentTool",
      "position": [
        -2240,
        -96
      ],
      "parameters": {
        "text": "={{ $fromAI('Prompt__User_Message_', ``, 'string') }}",
        "options": {},
        "toolDescription": "call this AI Agent that specializes in product roadmaps, feature specifications, user stories, and product planning"
      },
      "typeVersion": 2.2
    },
    {
      "id": "ux-agent",
      "name": "UX/UI 디자이너",
      "type": "@n8n/n8n-nodes-langchain.agentTool",
      "position": [
        -1280,
        -704
      ],
      "parameters": {
        "text": "={{ $fromAI('Prompt__User_Message_', ``, 'string') }}",
        "options": {},
        "toolDescription": "call this AI Agent that specializes in user experience design, wireframes, user flows, and interface specifications"
      },
      "typeVersion": 2.2
    },
    {
      "id": "research-agent",
      "name": "사용자 연구 전문가",
      "type": "@n8n/n8n-nodes-langchain.agentTool",
      "position": [
        -1840,
        -304
      ],
      "parameters": {
        "text": "={{ $fromAI('Prompt__User_Message_', ``, 'string') }}",
        "options": {},
        "toolDescription": "call this AI Agent that specializes in user research, surveys, interviews, persona creation, and market analysis"
      },
      "typeVersion": 2.2
    },
    {
      "id": "analytics-agent",
      "name": "제품 분석 전문가",
      "type": "@n8n/n8n-nodes-langchain.agentTool",
      "position": [
        -1328,
        -80
      ],
      "parameters": {
        "text": "={{ $fromAI('Prompt__User_Message_', ``, 'string') }}",
        "options": {},
        "toolDescription": "call this AI Agent that specializes in product metrics, KPI tracking, A/B testing, and data-driven insights"
      },
      "typeVersion": 2.2
    },
    {
      "id": "tech-writer-agent",
      "name": "기술 문서 작성자",
      "type": "@n8n/n8n-nodes-langchain.agentTool",
      "position": [
        -1744,
        -1024
      ],
      "parameters": {
        "text": "={{ $fromAI('Prompt__User_Message_', ``, 'string') }}",
        "options": {},
        "toolDescription": "call this AI Agent that specializes in product documentation, API docs, user guides, and technical specifications"
      },
      "typeVersion": 2.2
    },
    {
      "id": "strategy-agent",
      "name": "제품 전략 분석가",
      "type": "@n8n/n8n-nodes-langchain.agentTool",
      "position": [
        -1344,
        -1264
      ],
      "parameters": {
        "text": "={{ $fromAI('Prompt__User_Message_', ``, 'string') }}",
        "options": {},
        "toolDescription": "call this AI Agent that specializes in competitive analysis, market positioning, go-to-market strategy, and product-market fit"
      },
      "typeVersion": 2.2
    },
    {
      "id": "cpo-model",
      "name": "OpenAI Chat Model CPO",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        -2672,
        -496
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "o3",
          "cachedResultName": "o3"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "YOUR_OPENAI_CREDENTIAL_ID",
          "name": "OpenAI account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "pm-model",
      "name": "OpenAI Chat Model1",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        -2208,
        368
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4.1-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "YOUR_OPENAI_CREDENTIAL_ID",
          "name": "OpenAI account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "ux-model",
      "name": "OpenAI Chat Model2",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        -1312,
        -496
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4.1-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "YOUR_OPENAI_CREDENTIAL_ID",
          "name": "OpenAI account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "research-model",
      "name": "OpenAI Chat Model3",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        -1824,
        -144
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4.1-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "YOUR_OPENAI_CREDENTIAL_ID",
          "name": "OpenAI account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "analytics-model",
      "name": "OpenAI Chat Model4",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        -1328,
        96
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4.1-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "YOUR_OPENAI_CREDENTIAL_ID",
          "name": "OpenAI account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "tech-writer-model",
      "name": "OpenAI Chat Model5",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        -1776,
        -768
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4.1-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "YOUR_OPENAI_CREDENTIAL_ID",
          "name": "OpenAI account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "strategy-model",
      "name": "OpenAI Chat Model6",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        -1312,
        -944
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4.1-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "YOUR_OPENAI_CREDENTIAL_ID",
          "name": "OpenAI account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "product-header-sticky",
      "name": "스티커 노트 헤더",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -3808,
        -880
      ],
      "parameters": {
        "color": 7,
        "width": 580,
        "height": 320,
        "content": "=======================================\n        CPO AGENT WITH PRODUCT TEAM\n=======================================\nFor any questions or support, please contact:\n    Yaron@nofluff.online\n\nExplore more tips and tutorials here:\n   - YouTube: https://www.youtube.com/@YaronBeen/videos\n   - LinkedIn: https://www.linkedin.com/in/yaronbeen/\n======================================="
      },
      "typeVersion": 1
    },
    {
      "id": "product-main-sticky",
      "name": "스티커 노트 본문",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -3808,
        -544
      ],
      "parameters": {
        "color": 7,
        "width": 740,
        "height": 2500,
        "content": "## 🚀 **CPO AGENT WITH PRODUCT TEAM - AI WORKFLOW**\n\n**🔥 Powered by OpenAI O3 & GPT-4.1-mini Multi-Agent System**\n\n#ProductManagement #ProductOps #n8nWorkflows #OpenAI #ProductStrategy\n\n---\n\n### 📝 **Overview**\n\nThis multi-agent n8n automation creates a comprehensive product development team. A strategic CPO agent receives your input, analyzes product opportunities, and coordinates specialized agents for product management, UX design, user research, analytics, documentation, and strategy—delivering end-to-end product development support with AI efficiency.\n\n---\n\n### ⚙️ **How It Works**\n\n1. **Chat trigger** receives product requests (e.g., \"Design a new mobile app feature for user onboarding\")\n2. **CPO Agent** (O3) analyzes requirements and creates product strategy\n3. Delegates to specialist agents:\n   - Product Manager\n   - UX/UI Designer\n   - User Research Specialist\n   - Product Analytics Specialist\n   - Technical Writer\n   - Product Strategy Analyst\n4. Each agent uses **GPT-4.1-mini** for specialized execution\n5. Results compiled into comprehensive product deliverables\n\n---\n\n### 👥 **Meet Your AI Product Team**\n\n| Agent | Purpose | Model | Output |\n|-------|---------|-------|--------|\n| 🚀 **CPO Agent** | Product vision & strategy coordination | O3 | Strategic oversight |\n| 📋 **Product Manager** | Roadmaps, specs, user stories | GPT-4.1-mini | Product requirements |\n| 🎨 **UX/UI Designer** | User flows, wireframes, interfaces | GPT-4.1-mini | Design specifications |\n| 🔍 **User Research** | Research plans, personas, insights | GPT-4.1-mini | User understanding |\n| 📊 **Analytics Specialist** | Metrics, KPIs, A/B tests | GPT-4.1-mini | Data-driven insights |\n| 📝 **Technical Writer** | Documentation, guides, specs | GPT-4.1-mini | Clear documentation |\n| 🎯 **Strategy Analyst** | Market analysis, positioning | GPT-4.1-mini | Strategic insights |\n\n---\n\n### 💡 **Use Cases**\n\n- **Feature Development**: Concept → Research → Design → Specs → Metrics\n- **Product Launch**: Strategy → Documentation → Analytics → Go-to-market\n- **User Experience**: Research → Personas → Flows → Testing → Optimization\n- **Competitive Analysis**: Market research → Positioning → Differentiation\n- **Product Roadmaps**: Vision → Priorities → Timeline → Resource planning\n- **Documentation Suite**: User guides → API docs → Technical specs\n\n---\n\n### 💸 **Cost Optimization**\n\n- **O3 for CPO**: Strategic product decisions only\n- **GPT-4.1-mini for execution**: 90% cost reduction\n- **Parallel processing**: All specialists work simultaneously\n- **Template reuse**: Leverage proven product frameworks\n\n---\n\n### 🏷️ **Tags**\n\n#ProductManagement #UXDesign #UserResearch #ProductStrategy #ProductOps\n#ProductAnalytics #TechnicalWriting #ProductDevelopment #FeatureDesign #ProductAI\n#n8n #OpenAI #MultiAgentSystem #ProductTech #ProductLeadership #Innovation"
      },
      "typeVersion": 1
    }
  ],
  "connections": {
    "product-think": {
      "ai_tool": [
        [
          {
            "node": "cpo-agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "ux-agent": {
      "ai_tool": [
        [
          {
            "node": "cpo-agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "pm-agent": {
      "ai_tool": [
        [
          {
            "node": "cpo-agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "tech-writer-agent": {
      "ai_tool": [
        [
          {
            "node": "cpo-agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "pm-model": {
      "ai_languageModel": [
        [
          {
            "node": "pm-agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "ux-model": {
      "ai_languageModel": [
        [
          {
            "node": "ux-agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "research-model": {
      "ai_languageModel": [
        [
          {
            "node": "research-agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "analytics-model": {
      "ai_languageModel": [
        [
          {
            "node": "analytics-agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "tech-writer-model": {
      "ai_languageModel": [
        [
          {
            "node": "tech-writer-agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "strategy-model": {
      "ai_languageModel": [
        [
          {
            "node": "strategy-agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "cpo-model": {
      "ai_languageModel": [
        [
          {
            "node": "cpo-agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "strategy-agent": {
      "ai_tool": [
        [
          {
            "node": "cpo-agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "research-agent": {
      "ai_tool": [
        [
          {
            "node": "cpo-agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "product-chat-trigger": {
      "main": [
        [
          {
            "node": "cpo-agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "analytics-agent": {
      "ai_tool": [
        [
          {
            "node": "cpo-agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    }
  }
}
자주 묻는 질문

이 워크플로우를 어떻게 사용하나요?

위의 JSON 구성 코드를 복사하여 n8n 인스턴스에서 새 워크플로우를 생성하고 "JSON에서 가져오기"를 선택한 후, 구성을 붙여넣고 필요에 따라 인증 설정을 수정하세요.

이 워크플로우는 어떤 시나리오에 적합한가요?

고급 - 프로젝트 관리, AI 챗봇

유료인가요?

이 워크플로우는 완전히 무료이며 직접 가져와 사용할 수 있습니다. 다만, 워크플로우에서 사용하는 타사 서비스(예: OpenAI API)는 사용자 직접 비용을 지불해야 할 수 있습니다.

워크플로우 정보
난이도
고급
노드 수18
카테고리2
노드 유형6
난이도 설명

고급 사용자를 위한 16+개 노드의 복잡한 워크플로우

저자
Yaron Been

Yaron Been

@yaron-nofluff

Building AI Agents and Automations | Growth Marketer | Entrepreneur | Book Author & Podcast Host If you need any help with Automations, feel free to reach out via linkedin: https://www.linkedin.com/in/yaronbeen/ And check out my Youtube channel: https://www.youtube.com/@YaronBeen/videos

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