I’ve been tracking my time for over a decade using a time-tracking tool called 'Hravest'.
So naturally, I also log the hours I spend learning about AI, and as of today, it’s over 1000 hours.
When I say AI training, I am not just talking about actively learning AI from others, but also working on AI projects. Because working on a real-life AI project is also AI training, and imho the best training you will ever get.
It will feel chaotic in the beginning.
When you first start learning AI, it can feel overwhelming.
The term “AI” is extremely broad. It includes machine learning, problem-solving, workflows, prompting, domain expertise, prompt engineering, AI agents, APIs, webhooks, Voice AI, RAG, and much more.
So if you are just getting started, it is completely normal to feel confused.
You may not know what to learn first, what to ignore, or where to focus your attention.
As a result, you may find yourself watching random YouTube videos, buying random AI courses, and trying to learn everything at once.
But even after all that effort, you may still feel like you do not know enough or know how to apply what you have learned.
At this stage, very little may make sense.
You may be experimenting without a clear direction, trying to piece together an AI puzzle that still feels incomplete.
I want you to know this is normal.
In my experience, something interesting happens around the 300-hour mark of AI training.
That is when things start to click.
You begin connecting the dots. You start to understand how the different parts of AI automation fit together. You begin to see the bigger picture.
This is also when you may start to discover your niche and area of speciality.
Before that point, it often feels like learning chaos. You may feel like you are running around in circles, trying everything but not feeling clear about anything.
The following are the key lessons I learned on my journey through more than 1,000 hours of AI training: