Feb/01/2026 - I’m documenting my learning journey in public and in private, and I’m doing it on purpose: I want a clear trail of where I started, what I understood, what confused me, and what I chose to do next.

To give this journey a “home,” I registered my domain www.myailogbbok.com and claimed my social spaces:

• LinkedIn: linkedin.com/in/myailogbook
  
  

• X: x.com/myailogbook
  
  

• Instagram: instagram.com/myailogbookus
  
  

Where this started: curiosity → information overload

I’ve always been a curious person, and suddenly I was being hit daily with headlines and conversations about something I didn’t fully understand: Artificial Intelligence. That gap—between how often I heard “AI” and how little I truly grasped it—pushed me to take it seriously. 

I started subscribing to podcasts and YouTube channels, and I began reading Nexus: A Brief History of Information Networks from the Stone Age to AI by Yuval Noah Harari. The message that stuck with me was that AI isn’t just “another technology”—it could reshape the stories and information networks that hold society together. 

Confusion and “fear” (which was really uncertainty)

Over time, my knowledge didn’t grow in a straight line. It went from “low knowledge” to something closer to confusion—and yes, even fear. But when I say fear, I mean uncertainty mixed with lack of understanding: “Wait… where am I stepping?” 

Part of the confusion came from the speed of the space and the noise—new “AI tools” appearing constantly, and sometimes it felt like “AI” was just a marketing sticker. My favorite example is the so-called “AI toothbrush.” The marketing says it analyzes your brushing and coaches you, but the reality is often sensors and simple zone-checking—no real learning, no true adaptation. That moment taught me to separate hype vs. substance. 

What I did next: stop watching—start touching the tools

Instead of staying stuck in commentary and headlines, I subscribed to the tools everyone was talking about: ChatGPT from OpenAI first, and soon after, Gemini from Google. Then I did something simple but important: I asked for guidance into the technical side—what AI is, how it works, and how to learn it step by step. 

That led me into the practice of prompting: writing a prompt, checking the result, and iterating—trial and error. And I discovered something that matters a lot: AI can help, but humans still judge the output. We evaluate, validate, and decide what is correct or useful.   

The concepts that clicked: AGI and LLMs

As I asked “where do these answers come from?”, I ran into two major ideas:

1. AGI (Artificial General Intelligence): a theoretical type of AI that could learn and apply knowledge across many tasks like a human. I don’t need to “believe” in it to recognize that many serious thinkers claim AI development is moving in that direction.
   
   

2. LLMs (Large Language Models): models trained on massive amounts of text to understand and generate language. This helped me put structure around what I was seeing in the tools—this wasn’t magic; it was model behavior.
   
   

The hardware shift: from iPad/iPhone to a real machine

Up to that point, I was doing everything on my iPad and iPhone (yes—I’m an Apple fanboy). But at some point I became obsessed with the idea of running different models locally and having more control. That wasn’t realistic on the devices I had, so I did what I needed to do: I went to an Apple Store and bought a MacBook Pro. 

After that, I downloaded tools to manage and run LLMs locally, and suddenly the amount of information and possibility exploded. 

The “chaos moment” and the return to focus

That’s when I hit the chaos: too many paths. Personal productivity. Generative AI for daily life. The impact on my job, my company, the labor market, society, geopolitics… even “life outside Earth.” My mind was leaving the planet.

And then: focus. Back to reality. 

Why I’m writing this logbook

Writing has always helped me learn—especially in school—because it forces my mind to slow down and shape ideas clearly. So I decided to do the same here: document the journey, capture where I stopped, review quickly, and then take the next step with intention. 

That is why My AI Logbook exists: it’s my diary of learning—built to organize the chaos, keep progress visible, and share the journey with others who might feel the same confusion I felt in the beginning.