Block 1 - New content - generate research questions
- Type / Role
- @n8n/n8n-nodes-langchain.chainLlm - chainLlm
- Config choices
- Version 1.5
This workflow is provided as-is. Please review and test before using in production.
Move beyond generic AI generated content and create articles that are high quality, factually reliable, and aligned with your unique expertise. This template orchestrates a sophisticated "research ...
@n8n/n8n-nodes-langchain.chainllm, n8n-nodes-base.set, n8n-nodes-base.formtrigger, @n8n/n8n-nodes-langchain.outputparserstructured, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.splitout, n8n-nodes-base.splitinbatches, n8n-nodes-base.httprequest
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Guillaume Duvernay.
Original n8n.io sourceMove beyond generic AI-generated content and create articles that are high-quality, factually reliable, and aligned with your unique expertise. This template orchestrates a sophisticated "research-first" content creation process. Instead of simply asking an AI to write an article from scratch, it first uses an AI planner to break your topic down into logical sub-questions.
It then queries a Super assistant—which you've connected to your own trusted knowledge sources like Notion, Google Drive, or PDFs—to build a comprehensive research brief. Only then is this fact-checked brief handed to a powerful AI writer to compose the final article, complete with source links. This is the ultimate workflow for scaling expert-level content creation.
This workflow follows a sophisticated, multi-step process to ensure the highest quality output:
GPT 5 mini and GPT 5 chat).This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
| Workflow | Create fact-based articles from your knowledge sources with Super RAG and GPT-5 |
|---|---|
| Complexity | advanced |
| Nodes | 19 |
| Categories | AI RAG, Multimodal AI |
| Author | Guillaume Duvernay |
| Published | 26 Aug 2025 |
Use the JSON export at /data/workflows/7907/7907.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
Move beyond generic AI generated content and create articles that are high quality, factually reliable, and aligned with your unique expertise. This template orchestrates a sophisticated "research ...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your AI RAG, Multimodal AI use case.