I've been building chatbot with n8n for my education platform. The biggest pain was monitoring — clicking through execution logs, messages mixed together, no way to jump in when the bot said something wrong. So I built a community node for n8n that solves this. You install it like any other community node: Settings → Community Nodes → Install → n8n-nodes-trilox You get 3 actions and 1 trigger: - Record Message — logs every conversation into a proper inbox - Check Handler — checks if a human is handling it so the bot stays quiet (no double replies) - Escalate to Human — flags conversations that need human attention - On Agent Message (trigger) — fires when you reply from the inbox If anyone's building chatbots with n8n and needs help with monitoring or human takeover — happy to help

Someone posted today that "I built a SaaS in 5 hours." No. You built a demo in 5 hours. A product means you've thought about what happens when things go wrong. You chose a tech stack — did you choose it because it fits, or because it's trending? You have users — did you think about what their experience actually feels like, or just what it looks like? Someone trusted you with their data — did you think about security before or after they signed up? A good product isn't something that looks impressive in a demo. It's something you'd trust with your own data. Something you'd actually want to use every day. Testing one of my projects took over 2 months. Not building. Testing. The stuff that matters in production never shows up in a screenshot. AI can write code faster than ever. But the hard part was never typing the code. It was caring about what you're building and who you're building it for. Build fast. But don't skip the part that matters. #software #buildinpublic #saas #automation #ai

AI tools get you building fast. But at some point you'll hit a wall. Not because the AI failed. Because you don't understand what it built for you. How does this server actually handle requests. Why did it choose this database structure. What happens when I deploy this. Where is this data going. You don't need to become a software engineer. But you need to know enough to understand what the AI is doing behind the scenes. Without that — you're copying code you can't debug, deploying things you can't fix, and storing data you can't protect. With it — you go from a cool prototype on your laptop to something real people can actually trust and use. Learn the basics. Then let AI make you faster. Not the other way around. #software #ai #buildinpublic #n8n

Hot take: The worst thing that happened to n8n beginners is AI. Not because AI is bad. Because everyone skips the basics now. First workflow? AI agent. Second workflow? RAG chatbot. Third workflow? Multi-agent system. Nobody builds a simple webhook → filter → send email anymore. But that simple workflow? It saves businesses hours every week. Zero tokens. Zero API costs. Runs forever. I've been automating things since before LLMs were cool. PLCs, SCADA systems, Node-RED, n8n, industrial stuff. No AI needed. The best automation is the one that just works. Quietly. Cheaply. Master the basics. Then add AI where it actually adds value. Not the other way around.

I was monitoring my chatbot late one night. A customer asked a question. I saw the bot preparing to respond. And I knew - instantly - the information was wrong. But I had no way to jump in. No way to correct it. Just had to sit there and watch it happen. That feeling of helplessness - seeing the mistake unfold, knowing it's wrong, unable to do anything - stays with you. Now I make sure I can always step in when automation fails. Because even the best systems need human oversight for edge cases.