been running the new models through my automations and theyre actually snappier, not just hype. my n8n flows are faster and the outputs land way cleaner. did anyone else get surprised when a model actually changed ur workflow or am i way behind the curve lol?

I tested the same prompt in Higgsfield using Fable 5 and GPT-5.6 SOL to compare how each model handles AI video generation. While both produced impressive results, they differed in areas like motion consistency, scene composition, prompt interpretation and overall visual quality. Running the same prompt across multiple models is one of the best ways to understand their strengths and choose the right tool for different creative workflows. 💬 Which model has impressed you the most for AI video generation lately and what differences have you noticed in your own tests?

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Hey everyone! 👋 I'm Takeichi, an AI & Full-Stack Engineer based in Japan. I've spent the past 10+ years building production software, with the last several years focused on AI systems and automation. Most of my work has been around: - 🤖 AI Agents & Agentic Workflows - 🧠 LLM Applications & RAG Systems - ⚡ Workflow Automation - 🐍 Python (FastAPI, Flask), TypeScript/Node.js - ⚛️ React & Next.js - 🔗 API integrations and backend architecture - 👁️ Computer Vision & OCR I've built AI research agents, document intelligence platforms, multi-agent workflows, AI voice systems, and automation tools that integrate with third-party services and enterprise systems. I'm here to: - Learn from other builders - Share ideas and technical knowledge - Exchange AI automation workflows - Connect with people building real-world AI products Looking forward to meeting everyone! Feel free to say hi or reach out if you're working on AI agents, automation, or LLM-powered products. 🚀 Portfolio: https://contra.com/takeichi_inoue_65rexfis/about Email: inoue.takeichi@gmail.com Telegram: https://t.me/HustorAI WhatsApp: +81 80-9299-0062

finally got a chatbot live on my site but it keeps giving customers wrong info and now i'm getting complaints lol. spent hours training it on our faqs and thought that would fix it but nope, still making stuff up. how did u guys handle keeping ur chatbots actually accurate without them just hallucinating random answers?