After watching Razvan's Tribe OS video and seeing how he chains Claude Code + Remotion + Blotato, I went down the rabbit hole and built my own version - but for a Romanian AI blog that runs completely on autopilot. The blog publishes 3 times a week (Mon/Wed/Fri at 07:03 EEST). No human in the loop. Here's what happens every cycle: Article pipeline: - Scouts trending topics in Romania (cross-references 5+ sources) - Checks the last 4 published articles to avoid duplicates - Writes a 1400-1600 word article with full SEO optimization (RankMath meta, keyword density, internal linking) - Generates a cover image with AI - Publishes to WordPress as a scheduled post - Pings Google/Bing/Yandex via IndexNow Video pipeline (this is where Razvan's work helped): - v1 was directly inspired by what Razvan showed - image slideshow style with TTS voiceover. Worked, but felt generic - v2 is where it gets interesting - switched to Veo 3.1 for actual AI-generated video with built-in Romanian narration. No separate TTS needed. The AI generates cinematic scenes related to the article topic with voice already baked in. Pipeline: article published in the morning → extract key points → generate Veo 3.1 video (9:16, ~30s) → transcribe with HappyScribe → auto-correct Romanian subtitles → burn subs with ffmpeg → publish to TikTok at 18:00 (peak hours Romania) Cost: ~$0.50 per full cycle (article + cover image + video + subtitles + posting) Bonus automations: - AI auto-replies to blog comments (contextual, matches the blog's personality) - Slack notifications for every new comment - Self-hosted analytics (no cookies, GDPR-clean) - Newsletter capture on autopilot The whole thing was built in about 58 hours from zero to fully autonomous. Stack: Claude Code + n8n + WordPress + Veo 3.1 + HappyScribe + ffmpeg. Blog is live at botescu.robomarketing.ro if you want to see the output - but is romanian language...sry for that :( @Razvan Sava - thank you for the Tribe OS video and this community. v1 of my video pipeline wouldn't exist without your work here.

I just dropped a new video where I show exactly how I built my own fully automated content system using Claude Code and Remotion. This setup can take a simple URL and turn it into a complete video with script, voiceover, visuals, and automatic posting. Inside the video, I walk step by step through: • Setting up Claude Code inside Antigravity • Generating scripts and voiceovers automatically • Creating AI images with Nano Banana 2 • Rendering videos using Remotion • Automatically publishing content to Social Networks This is the exact system I’m using to scale content without doing everything manually. Watch the full video here: https://youtu.be/H-qYkMJRIHg If you want to test auto-posting and distribution, you can use Blotato here: https://dub.sh/blotato

Fal.ai and n8n are now officially integrated, and this is a game-changer for anyone getting into AI automation. I've used fal heavily throughout my tutorials, and now you have a much easier way to plug it into your workflows without writing a single line of code. https://www.youtube.com/@automation-tribe Here's the quick breakdown: - 🎯 Combine fal workflows + n8n workflows together - 🤖 No-code generative AI automation — beginner friendly - 🗄️ Access 1,000+ generative media models directly in n8n, powered by fal If you're just starting out, this is honestly one of the best setups you can learn right now. It's powerful, flexible, and way more accessible than it used to be.

If you’re building advanced AI automations in n8n, this new feature changes everything. With the latest update, you can now dynamically choose your AI model mid-workflow using the new Model Selector node. ✅ Example: Message comes in → your AI Agent is triggered → n8n automatically routes the task to OpenRouter, Google Gemini, or any other LLM depending on speed, cost, or task type. This means: - You can use faster or cheaper models for simple tasks - Or route complex tasks to more powerful LLMs - All within the same flow — no hardcoding Perfect for: - AI Assistants - Chatbots - Hybrid agent workflows - Cost-efficient automation at scale Have you tried this yet? Drop your ideas and example

Just created an AI assistant template for WhatsApp that REMEMBERS CONVERSATIONS and accesses a knowledge base! 🧠✨ Apps used: 🔹 WAMM.pro - WhatsApp connection (proprietary API) 🔹 Google Gemini - natural AI conversations 🔹 Pinecone - vector memory for conversations 🔹 OpenAI - embeddings for semantic search Why WAMM.pro is perfect for this: ✅ FREE account - 50 messages/month to test ✅ Quick setup - scan QR, you're ready! ✅ Native webhooks - perfect n8n integration ✅ Reliable platform - consistent performance Template benefits: 🎯 Persistent memory - remembers names, preferences, past conversations 🎯 Custom knowledge base - answers business-specific questions 🎯 Natural conversations - doesn't sound robotic, never says "searching history" 🎯 Multi-user - each person gets their own memory space 🎯 Zero maintenance - runs automatically 📎 Attached the complete JSON with ALL setup instructions step-by-step! Link for template: https://n8n.io/workflows/6170-conversational-whatsapp-assistant-with-gemini-ai-and-pinecone-memory/ If you implement this for clients or business, it's a HUGE difference from simple chatbots that remember nothing! 🚀 Drop your questions in the comments - curious to see what adaptations you make and how you use it! 💭 p.s. If you need a template for Make, just let me know. #n8n #WhatsApp #AI #WAMM #Automation #Memory #Chatbot