{
  "name": "GGA — AI Newsletter System",
  "nodes": [
    {
      "parameters": {
        "rule": {
          "interval": [
            {
              "field": "weeks"
            }
          ]
        }
      },
      "id": "5316c8e1-254e-4e4a-ab9d-740b576c73a0",
      "name": "Schedule Trigger",
      "type": "n8n-nodes-base.scheduleTrigger",
      "typeVersion": 1.2,
      "position": [
        -16,
        -256
      ]
    },
    {
      "parameters": {
        "query": "New Housing Market 2026 News",
        "options": {}
      },
      "id": "fbc6d604-49b1-425d-ab53-22f98064251a",
      "name": "Initial Research",
      "type": "@tavily/n8n-nodes-tavily.tavily",
      "typeVersion": 1,
      "position": [
        208,
        -256
      ],
      "credentials": {
        "tavilyApi": {
          "id": "cvu3J0RJrUTye1nB",
          "name": "Tavily account 2"
        }
      }
    },
    {
      "parameters": {
        "model": {
          "__rl": true,
          "value": "claude-haiku-4-5-20251001",
          "mode": "list",
          "cachedResultName": "Claude Haiku 4.5"
        },
        "options": {}
      },
      "id": "785dcca2-cbb0-462d-98d3-de1340e2b212",
      "name": "Claude Sonnet",
      "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
      "typeVersion": 1.3,
      "position": [
        928,
        -64
      ],
      "credentials": {
        "anthropicApi": {
          "id": "koQ0CEOqcaRpYEWm",
          "name": "Anthropic account"
        }
      }
    },
    {
      "parameters": {
        "fieldToSplitOut": "output.topics",
        "options": {}
      },
      "id": "da51affa-4d07-4f09-959b-fa62334dd87b",
      "name": "Split Out",
      "type": "n8n-nodes-base.splitOut",
      "typeVersion": 1,
      "position": [
        688,
        -256
      ]
    },
    {
      "parameters": {
        "query": "={{ $json['output.topics'] }}",
        "options": {
          "time_range": "month",
          "include_raw_content": true
        }
      },
      "id": "50796d13-5831-4482-b418-b69e4df0e3ce",
      "name": "Research Topics",
      "type": "@tavily/n8n-nodes-tavily.tavily",
      "typeVersion": 1,
      "position": [
        896,
        -256
      ],
      "credentials": {
        "tavilyApi": {
          "id": "cvu3J0RJrUTye1nB",
          "name": "Tavily account 2"
        }
      }
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "=Topic: {{ $json.query }}\n\nResearch:\n{{ $json.results.map(item => JSON.stringify(item, null, 2)).join('\\n\\n') }}\n",
        "options": {
          "systemMessage": "=# Overview\nYou are a professional newsletter section writer. Your only task is to write one standalone section of a newsletter.\n\n## Instructions\n- Always include a clear section heading followed by the section content.\n- Do not write an overall title, introduction, or conclusion.\n- Write in a professional, expert, and engaging tone suitable for a business newsletter.\n- If you reference facts, data, or quotes, you must cite your sources and provide the actual clickable URLs.\n- Do not invent citations—only include real, verifiable sources.\n- Keep the section concise, well-structured, and easy to read.\n"
        }
      },
      "id": "e8843082-39ca-42b8-903e-3e358cca6d5c",
      "name": "Section Writer Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 2.2,
      "position": [
        1024,
        -256
      ]
    },
    {
      "parameters": {
        "fieldsToAggregate": {
          "fieldToAggregate": [
            {
              "fieldToAggregate": "output"
            }
          ]
        },
        "options": {}
      },
      "id": "f0339c68-e254-4c7e-93a5-74958041f666",
      "name": "Aggregate",
      "type": "n8n-nodes-base.aggregate",
      "typeVersion": 1,
      "position": [
        1360,
        -256
      ]
    },
    {
      "parameters": {
        "model": "anthropic/claude-3.5-haiku",
        "options": {}
      },
      "id": "17d71654-11c6-4130-ba9a-62fa19079332",
      "name": "OpenRouter Chat Model1",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenRouter",
      "typeVersion": 1,
      "position": [
        1104,
        -64
      ],
      "credentials": {
        "openRouterApi": {
          "id": "CBZjcz1HUiG2CpkP",
          "name": "OpenRouter account 2"
        }
      }
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "=Title: {{ $('Parse Planning Output').item.json.output.title }}\n\nSections: {{ $json.output.join(\"\\n\\n\\n\") }}\n",
        "hasOutputParser": true,
        "options": {
          "systemMessage": "=# Overview\nYou are an expert newsletter editor. Merge exactly three provided sections into a cohesive, email-ready HTML body with a holistic introduction and conclusion. Maintain a professional, concise tone for a business audience and preserve intended meaning.\n\n## Goals\n- Refine clarity, flow, and consistency across all sections.\n- Keep total content output ≤ 1000 words (hard limit). Avoid fluff.\n\n## Structure (HTML only)\n1) <p> Introduction that frames the three topics and their relevance; reference today's date: {{ $now.format('yyyy-MM-dd') }}.\n2) For each provided section:\n   - <h2> Use or lightly adjust the given title.\n   - Edited <p> content.\n   - Inline, clickable citations near related claims using <a href=\"https://...\">Source</a>. Never invent sources.\n3) <h3>Sources</h3><ul> A single consolidated list:\n   - Each item: <li><a href=\"[URL]\">[Publication Name] – [Article Title]</a></li>\n   - Include full URLs, deduplicate identical links, and alphabetize by Publication Name.\n4) <p> Conclusion tying threads together with implications or next steps.\n\n## Citation and Link Rules\n- Every factual claim relying on external information must include a real, verifiable, clickable URL.\n- Preserve any provided citations; standardize to the <a> format.\n- Omit unverifiable links rather than fabricate.\n- Use only basic HTML tags (<h2>, <h3>, <p>, <ul>, <li>, <a>). No images, scripts, styles, or external CSS.\n\n## Input\n- You will receive three sections. Edit and integrate them without adding unrelated topics.\n\nOutput Format (return only this)\nSubject: One clear, specific subject line (≤ 80 characters)\n\nContent:\n[HTML body only as specified above]\n"
        }
      },
      "id": "3ec97b76-d61e-42db-bd42-2c443ed0d134",
      "name": "Editor Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 2.2,
      "position": [
        1488,
        -256
      ],
      "onError": "continueRegularOutput"
    },
    {
      "parameters": {
        "schemaType": "manual",
        "inputSchema": "{\n  \"type\": \"object\",\n  \"properties\": {\n    \"subject\": {\n      \"type\": \"string\",\n      \"description\": \"the email subject\"\n    },\n    \"content\": {\n      \"type\": \"string\",\n      \"description\": \"the newsletter content\"\n    }\n  },\n  \"required\": [\"subject\", \"content\"]\n}\n"
      },
      "id": "4a5d1817-74f0-4825-9488-c0afed48b94b",
      "name": "Structured Output Parser1",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "typeVersion": 1.3,
      "position": [
        1296,
        -64
      ]
    },
    {
      "parameters": {
        "content": "# GGA — AI Newsletter System\n\nWeekly newsletter on **AI adoption for small businesses**, delivered as a Gmail draft for review.\n\n## Credentials Needed\n1. **Tavily API** — connect to both Tavily nodes (Initial Research + Research Topics)\n   Get key at: https://tavily.com\n2. **OpenRouter API** — connect to both OpenRouter Chat Model nodes\n   Get key at: https://openrouter.ai\n3. **Gmail OAuth** (YOUR_EMAIL@example.com) — connect to the Gmail draft node\n\n## Activate\nOnce credentials are connected, set schedule in Trigger node and activate.",
        "height": 500,
        "width": 600
      },
      "id": "789ea69e-dcc0-401e-8f4c-63288447a533",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        -832,
        -336
      ]
    },
    {
      "parameters": {
        "content": "## Trigger\nSet cadence",
        "height": 224,
        "width": 208,
        "color": 7
      },
      "id": "1604a2c7-60b6-4094-bf9e-a3b465cf5844",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        -64,
        -336
      ]
    },
    {
      "parameters": {
        "content": "Set your newsletter topic in the \"query\" field",
        "height": 224,
        "width": 208,
        "color": 5
      },
      "id": "081ae1d4-f22b-4853-b7ee-86ea1614b739",
      "name": "Sticky Note2",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        160,
        -336
      ]
    },
    {
      "parameters": {
        "content": "## Generating Title & Topics",
        "height": 224,
        "width": 448,
        "color": 4
      },
      "id": "add610e6-4686-4f48-95e1-ef6defe67032",
      "name": "Sticky Note3",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        384,
        -336
      ]
    },
    {
      "parameters": {
        "content": "## Writing Newsletter Sections",
        "height": 224,
        "width": 448,
        "color": 6
      },
      "id": "e1e2cade-7d3f-44a1-84ca-ca2b0575c07d",
      "name": "Sticky Note4",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        848,
        -336
      ]
    },
    {
      "parameters": {
        "content": "## Editing Final Copy",
        "height": 224,
        "width": 448,
        "color": 2
      },
      "id": "b677a355-b9a4-4a6b-9127-2adc8749c36a",
      "name": "Sticky Note5",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        1312,
        -336
      ]
    },
    {
      "parameters": {
        "content": "",
        "width": 832,
        "color": 7
      },
      "id": "978e9a71-4ab5-4566-9878-88892cedd7d7",
      "name": "Sticky Note6",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        640,
        -96
      ]
    },
    {
      "parameters": {
        "content": "## Send Draft",
        "height": 224,
        "width": 224
      },
      "id": "33d8e462-b01c-4b4e-a83b-645e592e8d15",
      "name": "Sticky Note7",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        1776,
        -336
      ]
    },
    {
      "parameters": {
        "jsCode": "const text = $input.first().json.text;\nlet parsed;\ntry {\n  parsed = JSON.parse(text);\n} catch(e) {\n  const match = text.match(/\\{[\\s\\S]*\\}/);\n  if (match) {\n    parsed = JSON.parse(match[0]);\n  } else {\n    throw new Error('Could not parse JSON from planning output: ' + text);\n  }\n}\nreturn [{ json: { output: parsed } }];"
      },
      "id": "eefa2d5a-3d0c-4f41-a052-91bc76da46ab",
      "name": "Parse Planning Output",
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        560,
        -256
      ]
    },
    {
      "parameters": {
        "model": {
          "__rl": true,
          "value": "claude-haiku-4-5-20251001",
          "mode": "list",
          "cachedResultName": "Claude Haiku 4.5"
        },
        "options": {}
      },
      "id": "2b1073f5-05ad-408f-a434-8e493bdfd4c6",
      "name": "Claude Haiku (Planning)",
      "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
      "typeVersion": 1.3,
      "position": [
        32,
        -592
      ],
      "credentials": {
        "anthropicApi": {
          "id": "koQ0CEOqcaRpYEWm",
          "name": "Anthropic account"
        }
      }
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "=You are an expert newsletter planner. Based on the articles below, return ONLY valid JSON with no other text:\n{\"title\": \"Newsletter Title Here\", \"topics\": [\"Topic One\", \"Topic Two\", \"Topic Three\"]}\n\nArticles:\n{{ $json.results.map(r => r.title + '\\n' + r.content).join('\\n\\n---\\n\\n') }}",
        "batching": {}
      },
      "id": "8daa8d07-e386-483d-ba04-a2635bdea2ab",
      "name": "Planning Chain",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "typeVersion": 1.9,
      "position": [
        352,
        -544
      ]
    },
    {
      "parameters": {
        "sendTo": "YOUR_EMAIL@example.com",
        "subject": "={{ $json.output.subject }}",
        "message": "={{ $json.output.content }}",
        "options": {}
      },
      "id": "f5544d21-b3e4-4629-bf1b-35a869282cac",
      "name": "Send a message",
      "type": "n8n-nodes-base.gmail",
      "typeVersion": 2.1,
      "position": [
        1840,
        -256
      ],
      "webhookId": "213fa9eb-22a1-477f-a9ef-90d46eb62dec",
      "credentials": {
        "gmailOAuth2": {
          "id": "lEUtBSzplBBijsWo",
          "name": "Gmail account"
        }
      }
    }
  ],
  "pinData": {
    "Aggregate": [
      {
        "json": {
          "output": [
            "# Home Price Declines Reshape Major U.S. Markets\n\nRecent data reveals significant price corrections across 22 major U.S. cities, marking a substantial shift from the pandemic-era housing boom. The S&P CoreLogic Case-Shiller Home Price Index, which tracks residential real estate values in major metropolitan areas, has documented year-over-year declines in numerous markets as elevated mortgage rates and shifting buyer demand reshape the landscape.\n\n**Key Markets Under Pressure**\n\nCities including San Francisco, San Jose, and other West Coast metros have experienced particularly pronounced declines, with some markets witnessing double-digit percentage drops from their 2022 peaks. These corrections reflect the dramatic reversal from 2020-2021, when inventory shortages and low interest rates fueled rapid appreciation.\n\n**What's Driving the Decline**\n\nThe primary culprit remains elevated mortgage rates, which have fundamentally altered affordability calculations. Additionally, the normalization of remote work policies has reduced demand in some traditionally hot markets, while inventory levels have gradually increased, shifting the negotiating power back toward buyers.\n\n**What This Means for Investors and Homeowners**\n\nFor prospective buyers, the corrected prices have improved affordability in select markets. However, homeowners who purchased near peak values may face equity challenges if they need to sell. Market conditions continue to vary significantly by geography, with some Sunbelt cities proving more resilient than coastal alternatives.\n\nMonitoring these trends remains essential for anyone making real estate decisions in the current environment.",
            "## Strategic Advantage in Today's Balanced Housing Market\n\nThe real estate landscape is shifting in buyers' favor. According to [Zillow's quarterly Agent Sentiment Survey](https://www.zillow.com/news/agents-see-a-more-balanced-housing-market-taking-shape-in-2026/), buyers are gaining meaningful negotiating power for the first time in years, with agents expecting increased activity ahead. This marks a significant departure from the seller-dominated conditions of recent years.\n\n### Understanding Your Position\n\nIn today's buyer-friendly environment, inventory has reached nearly 1 million active units—a level not seen since early 2020, according to reporting from [USA Today](https://www.usatoday.com/story/sponsor-story/real-estate-ausa/2026/03/11/what-you-should-know-before-making-an-offer-in-a-buyers-market/89016999007/). With homes staying on the market longer and supply higher than it has been in years, buyers have more leverage than they realize across multiple dimensions—not just price.\n\nHowever, balanced market conditions require strategy. While realistic pricing and strong marketing still allow sellers to succeed, buyers now have expanded options and genuinely increased negotiating power. The key is understanding where that leverage applies.\n\n### Negotiating Beyond Price\n\nSmart buyers should recognize that terms matter as much as asking price. Sellers in today's environment are more likely to agree to favorable concessions, including:\n\n- **Closing cost assistance** and seller-paid repairs\n- **Favorable inspection and appraisal contingencies**\n- **Flexible closing timelines** aligned with your needs\n- **Home warranty coverage** and other protections\n\nAccording to real estate experts quoted in USA Today's guidance, [sellers rarely come off more than 3 to 4 percent of their final asking price](https://www.usatoday.com/story/sponsor-story/real-estate-ausa/2026/03/11/what-you-should-know-before-making-an-offer-in-a-buyers-market/89016999007/)—making comprehensive negotiation on multiple fronts more valuable than aggressive low-ball offers.\n\n### Maintaining Perspective\n\nDespite improved conditions, [successful buyers avoid acting out of urgency or fear](https://www.usatoday.com/story/sponsor-story/real-estate-ausa/2026/03/11/what-you-should-know-before-making-an-offer-in-a-buyers-market/89016999007/). Even in a balanced market, a home should fit both your long-term needs and your budget. Working with an experienced agent who understands local market dynamics is essential—conditions vary significantly by neighborhood, price point, and property type.",
            "## Housing Affordability Crisis Creates Historic Affordability Gap Between Existing and New Homeowners\n\nThe U.S. housing market has fractured into two distinct groups, with new homebuyers facing unprecedented financial barriers that rival previous affordability crises. According to recent analysis from the [National Association of Home Builders (NAHB)](https://www.nahb.org/blog/2026/02/new-data-show-housing-affordability-concerns-across-the-us), in 39 states and the District of Columbia, more than 65% of households cannot afford the median-priced new home. New Hampshire faces the most severe affordability challenge, with 83.4% of households unable to afford the median new home price of $677,982.\n\nThe wealth gap between existing homeowners and new buyers has reached historic proportions. According to research from the [Economic Innovation Group](https://www.realtor.com/news/trends/new-homebuyer-record-costs-housing-market-gap/), new homeowners now spend approximately 35% of their income on housing costs, while existing homeowners spend just 28%—a nearly 7 percentage point gap that represents the largest disparity in nearly 40 years. Even at the peak of the 2007 housing bubble, when new owners were spending 28% of income on housing, the gap with existing homeowners was narrower at just 4 percentage points.\n\nThis disparity stems primarily from the \"lock-in effect\" created by mortgage rates. Over half of outstanding mortgages in the U.S. are locked into interest rates below 4%, according to [Realtor.com data](https://www.realtor.com/research/2025-q3-outstanding-mortgage-data/). Existing homeowners are unwilling to trade these ultralow rates for today's 6% rates, keeping inventory artificially constrained and pushing prices further out of reach for first-time buyers. Meanwhile, the median age of first-time homebuyers has climbed to 40, the highest on record, according to the [National Association of Realtors](https://www.nar.realtor/blogs/economists-outlook/how-nar-research-collects-first-time-buyer-data-and-why-it-matters).\n\n**New Home Price Cuts Offer Limited Relief**\n\nRecognizing the affordability crisis, homebuilders are employing new strategies to increase accessibility. According to reporting from [Fox Business](https://www.foxbusiness.com/economy/builders-blueprint-tackle-us-housing-crisis), newly built homes in some markets are now roughly $30,000 cheaper than existing homes—a remarkable reversal that would have been unthinkable in previous housing cycles. Builders are achieving this through reduced home sizes (averaging approximately 2,400 square feet by the end of 2025, down from 2,700 square feet after the Great Recession), simplified designs, and adoption of artificial intelligence in planning and design processes.\n\nHowever, experts caution that price cuts alone cannot solve the affordability crisis. According to [Brookings Institution research](https://www.brookings.edu/articles/thinking-about-the-growing-housing-affordability-crisis/), demand-side interventions—including interest rate buydowns and other strategies to lower mortgage rates—can backfire by driving up home prices rather than making housing more affordable. The analysis emphasizes that housing supply has become far more inelastic, meaning price increases no longer generate proportional increases in new construction.\n\nThe consensus among housing experts is clear: sustainable affordability improvement requires supply-side solutions. Policymakers must focus on reducing regulatory barriers to housing construction, expanding housing types allowed in zoning (such as accessory dwelling units and townhomes), and potentially restructuring local permitting systems that systematically reject new development proposals.",
            "## Rate Lock Effects and Market Supply Dynamics\n\nRecent research from Harvard's Joint Center for Housing Studies reveals a critical but often overlooked factor shaping today's mortgage market: the \"rate lock\" incentive created when homeowners hold low-interest mortgages. [According to analysis by Justin Katz and Robert Minton](https://www.jchs.harvard.edu/blog/did-mortgages-locked-low-rates-lead-rising-house-prices), this phenomenon significantly impacts housing supply and price dynamics in ways that traditional economic models often fail to capture.\n\n### The Rate Lock Mechanism\n\nWhen mortgage rates rise sharply, existing homeowners with locked-in low rates face a powerful financial disincentive to sell. Rather than give up their valuable mortgage rate, many choose to stay put—reducing the supply of homes available for purchase. From 2021 to 2023, as rates climbed from 2.7% to 6.6%, this effect became pronounced. [Research shows that a 1 percentage-point decrease in average outstanding mortgage rates increased nominal house price growth by 8 percentage points during this period.](https://www.jchs.harvard.edu/blog/did-mortgages-locked-low-rates-lead-rising-house-prices)\n\n### Supply Constraints and Price Impact\n\nCritically, rate lock effects are amplified in markets with constrained housing supply. The research found that rate lock explains approximately 40% of the gap between predicted price declines and the actual price growth observed between 2021 and 2023—a substantial portion of what many analysts initially attributed to other factors.\n\n### Policy Implications for Today's Market\n\nThe findings suggest that modest supply increases remain essential for sustainable affordability improvements. While alternative mortgage structures—such as portable mortgages or buyback options—might reduce moving friction, [they would still preserve incentives to remain as homeowners rather than renters when rates rise](https://www.jchs.harvard.edu/blog/did-mortgages-locked-low-rates-lead-rising-house-prices). This underscores that housing affordability solutions must ultimately focus on expanding overall housing supply rather than restructuring mortgage contracts alone.",
            "## Global Housing Market Shifts: Where Growth is Really Happening\n\nThe world's housing markets are no longer moving in lockstep. Instead of following a single narrative, regional variations are creating distinct investment opportunities and market dynamics across the globe.\n\n### The UK: A Patchwork of Local Dynamics\n\nThe UK housing landscape exemplifies this shift. According to the [Zoopla House Price Index](https://content.briefyourmarket.com/Newsletters/July-2025-TPFG-Articles/How-regional-variations-are-shaping-the-UK-s-housing-market-in-2025.aspx), major urban centers are experiencing steadier growth while suburbs and smaller towns continue to attract significant attention. Remote working flexibility and lifestyle preferences are redirecting buyer focus toward the South West and Midlands, areas that previously operated at a gentler pace. This geographic redistribution means that local insight—understanding demand for outdoor space, energy efficiency, and flexible layouts—has become essential for both buyers and sellers.\n\n### Greece: Unexpected Growth in Working-Class Districts\n\nGreece's market tells a similarly localized story. Working-class neighborhoods like Patissia and Sepolia in Athens are experiencing growth rates double those of prestigious areas like Kolonaki, with [yields hitting 5.5 to 7 percent in areas that wouldn't have attracted investment just five years ago](https://greekreporter.com/2025/06/28/greece-housing-market), according to Spitogatos Insights. More dramatic is Agia Varvara, recording annual growth of 8.2 percent. Simultaneously, tourist hotspots like Mykonos and Santorini remain expensive, but smart investors are recognizing the better risk-adjusted returns in developing urban centers and their suburbs.\n\n### Australia: Regional Markets Outpacing Capital Cities\n\n[Australia's surprising property market hotspots](https://whichrealestateagent.com.au/australias-surprising-property-market-hotspots-in-2026) show how affordability constraints in Sydney and Melbourne are redirecting demand to outer metro corridors and regional centers. Regional dwelling values rose approximately 3.2 percent over a recent quarter, outpacing capital city gains of 2.1 percent. Queensland and Western Australia are leading migration patterns, with suburbs in Logan, Ipswich, and Perth's outer regions recording impressive growth driven by population inflows, infrastructure investment, and tight rental markets with vacancy rates below 2 percent.\n\n### What Unites These Markets\n\nAcross geographies, emerging hotspots share common characteristics: population growth above national averages, low rental vacancy rates, confirmed infrastructure investment, and limited new housing supply. These fundamentals—not headline prices or luxury appeal—are driving sustainable price growth and investor returns. For stakeholders in housing markets anywhere globally, the lesson is clear: understanding local demand drivers and regional economics matters far more than national averages."
          ]
        },
        "pairedItem": [
          {
            "item": 0
          },
          {
            "item": 1
          },
          {
            "item": 2
          },
          {
            "item": 3
          },
          {
            "item": 4
          }
        ]
      }
    ]
  },
  "connections": {
    "Schedule Trigger": {
      "main": [
        [
          {
            "node": "Initial Research",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Claude Sonnet": {
      "ai_languageModel": [
        [
          {
            "node": "Section Writer Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Split Out": {
      "main": [
        [
          {
            "node": "Research Topics",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Research Topics": {
      "main": [
        [
          {
            "node": "Section Writer Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Section Writer Agent": {
      "main": [
        [
          {
            "node": "Aggregate",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Aggregate": {
      "main": [
        [
          {
            "node": "Editor Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenRouter Chat Model1": {
      "ai_languageModel": [
        [
          {
            "node": "Editor Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Structured Output Parser1": {
      "ai_outputParser": [
        [
          {
            "node": "Editor Agent",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "Editor Agent": {
      "main": [
        [
          {
            "node": "Send a message",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Parse Planning Output": {
      "main": [
        [
          {
            "node": "Split Out",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Initial Research": {
      "main": [
        [
          {
            "node": "Planning Chain",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Claude Haiku (Planning)": {
      "ai_languageModel": [
        [
          {
            "node": "Planning Chain",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Planning Chain": {
      "main": [
        [
          {
            "node": "Parse Planning Output",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "active": true,
  "settings": {
    "executionOrder": "v1",
    "callerPolicy": "workflowsFromSameOwner",
    "availableInMCP": false
  },
  "versionId": "bbdf9263-2655-4ad9-b2b0-cdfd13ee1e17",
  "meta": {
    "templateCredsSetupCompleted": true,
    "instanceId": "61ee55bee1174ec9d54f73b01b63eabd908eb9704bb4546637a8cb0a386a69d3"
  },
  "id": "oqnPb1rjzXNCRxC5",
  "tags": []
}