Documentation is one of the most important parts of building automation systems. It is also one of the most tedious. In this video, I show a system that turns a walkthrough video plus a workflow screenshot into a clean, structured Google Doc. No more writing SOPs from scratch. What the system produces: - A well formatted Google Doc - Clear sections for setup, nodes, APIs, and deployment notes - Screenshot placeholders so you know exactly where visuals should go - A production checklist you can use before shipping How it works, step by step: 1. Submit a form - Video URL (YouTube or an unlisted upload) - Workflow screenshot (file upload) 2. Extract the screenshot for later use - Convert the uploaded image into a base64 string - Store it so it can be referenced further down the workflow 3. Pull the video transcript with Apify - Run the YouTube Transcript Scraper - Return the transcript data 4. Clean the transcript with a Code node - Combine all transcript segments into a single readable paragraph 5. Convert the stored screenshot back into a file - Move base64 back into a file so it can be analyzed 6. Analyze the workflow screenshot with OpenAI - Generate a structured description of what the workflow is doing 7. Generate the documentation with Claude via OpenRouter - Feed it two inputs: - Transcript text - Workflow screenshot description - Output a JSON with: - Documentation title - Full markdown documentation 8. Parse the JSON output - Split out title and documentation fields cleanly 9. Create a Google Doc from Markdown - Use a community node that supports Markdown to Google Docs formatting - Auto-create the doc in the correct Drive folder Result: You record a 10 minute walkthrough, upload one screenshot, and the system drafts the entire doc for you. If you want to build it, the blueprint and prompts are linked in the description. Subscribe for more tutorials on n8n systems, AI agents, and agency-ready automations. https://youtu.be/a7O2-axMJEg?si=dRkeaTigxgVLyzLI

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While working with a few clients, I noticed something odd: people repeat themselves way less on calls than on chat or email. On chat, they re-explain context. On email, they forward threads. On calls, they just move forward. This became obvious while testing different call setups recently and spending some time with Feather Ai. When context carried over properly between turns, calls felt… lighter. Less friction. Made me realize the real value isn’t “AI on calls” - it’s removing the back-and-forth humans hate. Curious if others have seen this too. Where do you see the most friction today: calls, chat, or email?

Google just released Gemini 3 and with it their new image model Nano Banana Pro. The results are crazy realistic and the price is surprisingly low. So I built a full image generation system in n8n that lets you create images through a simple chat interface. The bot can generate three types of images. You can create an image from text. You can use an existing image as a reference. Or you can upload multiple images and combine them into a brand new one. I walk through how the whole system works: 1. How to connect Nano Banana Pro through Kie.ai using HTTP requests 2. How to build a clean n8n form that collects prompts and file uploads 3. How to enhance prompts with AI before sending them to the model 4. How to use Google Drive as a free image host for the uploaded files 5. How to handle the async generation loop until the image is done 6. How to send the final image back through a Telegram chat The bot can make infographics, edits, memes or realistic image composites. And you can run the whole thing from your phone. If you want more builds like this, make sure you subscribe. https://youtu.be/sJsHQ3J1erI?si=8KcVFwNno7R3gFk0

As a millionaire living my best life, I'm giving $20k to the first 20 people who message me “GRACE” I understand that many people are struggling with bills, and I want to help reduce that burden.