У нас вы можете посмотреть бесплатно How to INSTANTLY Create n8n Agents Using ChatGPT (No Code) или скачать в максимальном доступном качестве, видео которое было загружено на ютуб. Для загрузки выберите вариант из формы ниже:
Если кнопки скачивания не
загрузились
НАЖМИТЕ ЗДЕСЬ или обновите страницу
Если возникают проблемы со скачиванием видео, пожалуйста напишите в поддержку по адресу внизу
страницы.
Спасибо за использование сервиса ClipSaver.ru
🚀 Gumroad Link to Assets in the Video: https://bit.ly/4gSHnZu 🤖 Apply to join the Early AI-dopters Community: https://bit.ly/3ZMWJIb 📅 Book a Meeting with Our Team: https://bit.ly/3Ml5AKW 🌐 Visit Our Website: https://bit.ly/4cD9jhG 🎬 Core Video Description In this video, I show you how to transform basic ChatGPT prompt engineering into ready-to-use n8n workflow templates. Learn two powerful techniques that convert your ideas into JSON-based templates which you can easily import into n8n. I walk you through understanding n8n’s infinite canvas, exploring JSON representations of modules, and modifying existing workflow templates to suit your use case. Whether you’re building email automations or AI agent workflows, these techniques will drastically speed up your process and reduce manual setup. This guide includes: An introduction to converting ChatGPT prompts into n8n workflow templates A quick overview of n8n’s infinite canvas and JSON representation of modules Technique #1: Generating workflow JSON from scratch via prompt engineering Technique #2: Modifying an existing n8n template to fit your use case Real-world examples and debugging tips for ensuring node validity ⏳ TIMESTAMPS 0:00 – Intro: Why converting prompts into n8n templates can save time 0:14 – Overview: Two techniques to generate ready-to-use JSON workflows 0:26 – n8n Basics: Understanding the infinite canvas and module JSON representation 0:35 – Level Setting: Quick intro to n8n and Make.com back-end mechanics 1:05 – Technique #1: Generating a workflow JSON from scratch via prompt engineering 1:19 – Exploring the Generated JSON: Opening and reviewing the JSON in an editor 2:03 – Deep Dive: Analyzing key nodes like Open Chat Model, Google Drive, and Postgres 2:29 – Importing Templates: How to copy JSON and import it into n8n 3:01 – Technique #2: Modifying an existing n8n template (e.g., swapping Google Sheet to Airtable) 3:28 – Debugging Tips: Resolving JSON errors and property name issues 3:41 – Real-World Use Case: Building an automation from Slack trigger to Calendar booking 4:08 – Comparing Outputs: Differences between GPT-4o and o3 for JSON generation 4:17 – Custom GPTs: Using my Lovable Prompt Helper for better template outputs 4:23 – Quick Fixes: Rearranging nodes and adjusting positions in n8n 4:26 – Workflow Recap: Overview of core functions and node connectivity 4:29 – Advanced Modifications: Tweaking JSON to refine your workflow 4:33 – Template Examples: Reviewing sample templates to spark inspiration 4:36 – Efficiency Boost: How these techniques reduce manual setup and save tokens 5:29 – Q&A Pause: Recap of initial techniques and viewer tips 6:01 – Debugging Deep Dive: Handling JSON parsing and inline comment issues 7:00 – Customization: Adjusting existing templates for your specific needs 8:00 – Real-World Demo: Building a Slack-to-Google Calendar automation 9:00 – Output Comparison: Evaluating GPT-4o vs. o3 generated JSON 10:01 – Custom GPT Cheat Sheet: Overview of available prompt helpers and template examples 11:00 – Live Editing: Tweaking JSON directly in n8n for optimal node alignment 12:00 – Best Practices: Tips for importing and debugging JSON templates in n8n 13:00 – Future-Proofing: Maintaining compatibility with n8n’s evolving JSON structures 14:02 – Technique Recap: Summarizing the two methods and their benefits 15:01 – Extended Q&A: Addressing common issues and troubleshooting advice 16:03 – Advanced Workflow Example: Further modifications to a complex automation 17:01 – Call-to-Action: How to access free custom GPT prompts and workflow templates 18:00 – Final Thoughts: Recap of benefits and efficiency gains 19:02 – Viewer Feedback: Encouraging comments and community engagement 20:00 – Outro: Video summary, thank you, and next steps #n8n #PromptEngineering #WorkflowAutomation #ChatGPTTemplates #AIWorkflow #JSONAutomation #n8nTemplates #AIAdoption #NoCode #AutomationTips