There is no such thing as a “one-click automation” that makes you rich overnight. This is the raw, unedited record of my journey—from stumbling through the chaotic world of AI to successfully building a fully automated, unmanned blog system.
1. “Anyone can do it in 10 minutes” – The Sweet Lie
My first casual encounter with AI was about two years ago. When ChatGPT and Gemini first emerged, I used them simply for basic searches and light tasks, thinking, “This is a pretty neat tool.” However, less than a year ago, when the autonomous AI agent ‘OpenClaw’ created a massive global boom, it struck me differently. Thinking, “I could actually build my own AI assistant with this,” I dove headfirst into the world of automation. But reality was harsh. The open-source ecosystem updated at an unimaginable speed. While I was following a blog tutorial line by line, OpenClaw would update, and the interface would completely change. Lost, I decided to ask the AI directly for directions.
2. The AI Mix-Up: OpenClaw vs. OpenKore
Unable to keep up with the rapid updates, I asked the fast-mode (free version) Gemini for help. Believing the AI knew best, I spent all night typing in the complex terminal commands it provided. When the installation finally finished, what appeared on my screen wasn’t a cutting-edge AI assistant, but ‘OpenKore’—a notorious automated bot program for the classic game Ragnarok Online. The older AI had completely misunderstood the functionally and phonetically similar names. It was a hilarious yet devastating betrayal by an AI that could search quickly but lacked deep contextual understanding.
3. Ollama’s Silence and the Reality of Local LLMs
After recovering from the online game installation incident, I battled through endless error logs and finally managed to integrate the local LLM, ‘Ollama.’ However, my joy was short-lived. Its Korean language proficiency was disastrous. Whether it was a limitation of OpenClaw itself or the small local model, its sheer incompetence at following basic instructions shattered my illusion of local LLMs.
4. Breaking Limits: Gemini Pro and the n8n Revolution
But those desperate struggles were not in vain. I boldly abandoned the inadequate local LLMs, moved through GPT-4o-mini, and finally integrated the powerful ‘Gemini Pro’ model, which began producing results on an entirely different level. Instead of complex coding, I discovered a tool called n8n, which allowed me to connect APIs like Lego blocks. The result? A perfectly unmanned system that autonomously searches for topics, writes articles, generates images, and publishes a post every day at 2:00 PM—even while I’m out enjoying a San Miguel.
5. Kevin’s Archive: I Will Sell My “Trials and Errors”
There is no magic button in automation. In this ‘Automation’ category, I will dissect and document everything: the n8n workflows, Python listener codes, and realistic know-how on AI model optimization that I gained through my own blood, sweat, and errors. My ultimate short-term goal is to generate stable revenue through these systems so I can converse at a deep-learning level with the top-tier AI model (Ultra). I hope my fierce records here will serve as the most reliable blueprint to save your valuable time.