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Curated by: Islam Laloui (175 videos)


Currently Playing: How to EASILY Convert Make Automations to n8n (No Code)

🚀 Gumroad Link to Assets in the Video: https://bit.ly/4gR77Fm 👉🏼Join the Early AI-dopters Community: https://bit.ly/3ZMWJIb Work With Us: https://www.promptadvisers.com/ 🎬 Core Video Description In this video, I demonstrate how to transform your Make.com automations into ready-to-use n8n workflow templates in seconds. Watch as I break down the inner workings of Make.com’s JSON blueprints and reveal a custom-built, drag-and-drop conversion tool that seamlessly translates them for use in n8n. I cover everything from understanding the unique JSON structures behind each platform to leveraging advanced techniques—using GPT-03 and Perplexity—for error checking and mapping modules correctly. This guide includes: An introduction to the fundamentals of Make.com automation and its JSON representation A detailed walkthrough of the conversion tool: setting up file triggers, re-encoding binary data, and mapping nodes A deep dive into crafting precise prompts to convert JSON while handling unsupported integrations Real-world examples (like the Cleo and Social Media Content Planner workflows) and troubleshooting tips A discussion on when to stick with Make.com versus scaling up with n8n for cost and flexibility benefits ⏳ TIMESTAMPS 0:00 – Intro: Transforming Make.com Automations into n8n Templates 0:14 – Overview: The promise of converting JSON workflows in seconds 0:26 – Make.com Fundamentals: Exploring the JSON blueprint behind your automations 0:35 – Demo Setup: Exporting a Make.com blueprint and examining its module structure 1:05 – The Challenge: Why Make.com JSON can’t be directly imported into n8n 1:19 – Custom Conversion Tool: Drag & drop JSON files for instant transformation 2:03 – Google Drive Trigger: Setting up file monitoring for incoming JSON files 2:29 – Binary to JSON: Converting downloaded file data into proper JSON format 3:01 – Mad Scientist Mode: Leveraging Perplexity to map Make.com modules to n8n nodes 3:28 – Prompt Breakdown: Crafting detailed instructions for accurate JSON translation 3:41 – Validation: Using GPT-03 to verify syntax and correct JSON errors 4:08 – Compatibility Check: Removing inline comments and ensuring node connectivity 4:17 – Batch Processing: Converting multiple automations simultaneously 4:23 – Real-World Example: Converting a Cleo automation with unsupported integrations 4:26 – Additional Conversion: Demonstrating a Social Media Content Planner workflow 4:29 – Node Mapping: Handling iterators, aggregators, and property naming issues 4:33 – Error Handling: Troubleshooting JSON parsing hiccups and validation errors 4:36 – Efficiency Boost: Comparing Make.com’s per-node operations to n8n’s single-operation model 5:29 – Troubleshooting Tips: Resolving common conversion challenges 6:01 – Advanced Debugging: Adding extra GPT-03 steps for deeper validation 7:00 – Customization: Tailoring templates for bespoke workflow requirements 8:00 – Cost Insights: When to choose Make.com vs. n8n based on operation volume 9:00 – Live Demo: Importing the converted JSON into n8n and testing functionality 10:01 – Recap: Summarizing the conversion process and key takeaways 11:00 – Final Thoughts: Future-proofing your automation workflows 12:00 – Q&A: Addressing viewer questions and common troubleshooting tips 13:00 – Community Call: Join our Early AI-dopters for exclusive insights 14:02 – Technique Recap: Reviewing the conversion methods and their benefits 15:01 – Extended Q&A: Further discussion on optimization and error fixes 16:03 – Advanced Workflow Example: Deep dive into complex automation modifications 17:01 – Call-to-Action: How to access free custom GPT prompts and workflow templates 18:00 – Efficiency Gains: Final thoughts on streamlining your automation process 19:02 – Viewer Feedback: Encouraging comments and community engagement 20:00 – Outro: Video summary, thank you, and next steps #n8n #MakeToN8n #WorkflowAutomation #JSONConversion #AutomationTools #MakeDotCom #n8nTemplates #NoCode #GPT #Perplexity


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