I just built a new type of RAG (Retrieval-Augmented Generation) AI agent using n8n’s new Data Tables feature, and it’s been super fun to experiment with. Basically, the agent can: - Pull relevant info from structured tables inside n8n. - Answer user questions accurately based on the stored knowledge. - Log interactions for learning and future improvements. This setup makes it feel like the AI has a “memory” tailored to the data you provide — all without leaving n8n! Would love to hear what you think and any ideas for expanding it further. 🙌

I was looking into Apify and noticed there don’t seem to be any Apollo scrapers available there. 🤔 Is it just me not finding them, or are they really not listed at all? Would love to hear if anyone has come across one or found a workaround.

Luma AI - This is Ray3, exciting times! Ray3 is an intelligent video model designed to tell stories. Ray3 is capable of thinking and reasoning in visuals and offers state of the art physics and consistency. In a world's first, Ray3 generates videos in 16-bit High Dynamic Range color bringing generative video to pro studio pipelines. The all-new Draft Mode enables you to explore many more ideas, much faster and tell better stories than ever before. https://lumalabs.ai/ray

Client's "automation expert" took 8 months to build broken workflows. I fixed everything in 14 minutes and tripled their conversion rate. This is why agencies are losing deals to solo operators: THE DISASTER HANDOFF Digital course creator, Michelle: "My automation guy disappeared after 8 months" Me: "What did he deliver?" Michelle: "Broken funnels, duplicate emails, missing sequences" Me: "How much did you pay?" Michelle: "$28,000 so far" 🚩 Red flag: 8 months with no working automation THE INHERITED MESS What the "expert" left behind: - 47 different Zapier workflows (most broken) - 12 landing pages that didn't connect properly - Email sequences firing randomly - Students getting charged twice - Refund requests daily - Course access failing 60% of the time Michelle: "I'm losing $15k/month in failed conversions" Her business was bleeding out. THE FORENSIC ANALYSIS I spent 30 minutes auditing the disaster: - Webhook endpoints pointing to deleted pages - Email triggers set up backwards - Payment processing had 3 different failure points - Course delivery broken in 8 different places - Analytics tracking completely missing The "expert" had basically connected random tools hoping something would work. THE 14-MINUTE REBUILD Opened Skada.ai and described what actually needed to happen: "Build complete course sales funnel: landing page visit → email capture → nurture sequence → sales page → payment processing → course delivery → student onboarding" 14 minutes later: ✅ Clean funnel architecture ✅ Proper email sequences ✅ Seamless payment processing ✅ Automatic course access ✅ Student progress tracking ✅ Completion certificates ✅ Upsell automation THE TESTING PHASE Michelle: "Should we test this slowly?" Me: "Let's run a live purchase right now" She bought her own course with a test card: - Landing page loaded instantly - Email capture worked perfectly - Welcome sequence triggered - Payment processed smoothly - Course access granted immediately - Student dashboard populated

ChatGPT and most AI tools answer using public internet data. But what if you want answers only from your own business or personal data? That’s where ✨ RAG Agents (Retrieval-Augmented Generation) step in. Here’s how I built one with n8n: - Trigger (Chat Message Received) → Listens for customer queries. - AI Agent (Google Gemini) → Core brain of the agent. - Vector Database (Pinecone) → Stores and retrieves your private data. - Embeddings (Google Gemini) → Converts data into searchable vectors. - Memory → Keeps chat context for natural conversations. ⚡ Outcome: Customer asks a question. RAG Agent fetches the most relevant info from your data. AI generates a precise, context-aware answer. If no private data is needed → it works like a normal chatbot. 💡 In short: RAG = Your Data + AI Power