🧩Step-by-Step Breakdown: 🗨️Trigger: "When chat message received" --This node listens for incoming chat messages from the user, asking for a specific type of doctor on Facebook 🌐HTTP Request: "Searching from Apify" --Sends a POST request to the Apify API to search Facebook for the type of doctor mentioned by the user (e.g., “best gynecologist in Sukkur”). ⏳Wait: "Gather result" - Pauses the workflow until Apify completes the search. - Outputs 5 result items from Facebook. 🧠Code in JavaScript: "Make structured output" - Doctor’s name - Timings - Availability - Location ✏️Edit Fields: "Required output" --Get required output 📄Append row in sheet: "Saving results" --Appends the final structured data into a connected Google Sheet for record-keeping.

AI Automation Society Plus just won Q3 Skool Games, back-to-back 1st place finished and top 5 in all three quarters of 2025. This wouldn't be possible without each of you helping us make AI Automation Society a space for everyone. Truly grateful for this amazing community we're building together. Quick heads up: Plus pricing increases in Q4. If you've been thinking about joining, now's the time. We'll give everyone a full week's notice before any price changes. Check it out here. Thank you all for the incredible support. You guys are the best! Cheers, Nate

In this video, I show you three powerful hacks for using n8n’s new data tables to make your AI agents smarter and more customizable. With data tables, you can build a front-end to control your models and prompts, track and log your agents’ actions and executions, and even run evaluations to improve performance over time. These methods give you more visibility, flexibility, and control, helping you build AI systems that are smarter, more reliable, and easier to optimize. Make sure to tune in, there may be some bonus hacks included in the video ;) #n8nDataTables