How I learn big topics in 30-minute bytes

When I want to understand a new technology, the hardest part is often deciding what to learn. In this blog post, I will share the process I use to learn something new every day.

In my last blog post, I discussed how I try to stay relevant as everything is changing around us.  Today, I’ll highlight one key element of my process for choosing what to learn.

A topic like AI, cloud data warehouses, MSP strategies, or cybersecurity is simply too large to tackle. So, I start by understanding the landscape: What are the major pieces? What problems is the target technology trying to solve? What are the important concepts and terms? I’m not trying to become an expert at this stage. I’m trying to build a mental map, so I know where I am and where I could go.

Then I break that map into much smaller questions and tackle one at a time. If I’m learning about AI models, for example, one day I might focus on how a model is initially trained. That leads me to parameters and weights. Understanding weights might lead to open-weight models, which raises another question: why would a company give away its model weights, and given their product is free, how do they fund their model research and model training – which are both very expensive? Each answer creates the next set of questions. Instead of following a fixed curriculum, I let my growing understanding determine where I go next. And, as I shared in my last blog post, I try to spend no more than 30 minutes a day on each micro topic – sometimes even less, depending on what else is on my plate for the day.

I also pay attention to the points where I can repeat the terminology but can’t really explain what it means. That’s usually a signal that I need to go deeper. I’ll ask the same question in different ways, look for examples, compare competing technologies, or try to explain the concept in plain English. I’ve found that being able to explain something simply is a much better test of understanding than using all the right technical language. These questions and issues swirl around in my head during the day, and I try to come back at night for another 20 to 30 minutes to close out some of them. Or make it the topic for the next day’s learning.  I believe this is a key part of the learning process.

Over time, the process becomes a kind of learning tree (see picture above). I start with the trunk—the big idea—and follow branches as questions emerge. Some branches don’t matter, so I stop following them. Others reveal something important, so I keep going deeper. That is how I avoid getting overwhelmed by the enormous amount of information available today. I don’t try to learn everything. I try to continually figure out what I need to understand next. 

My golden rule is that learning compounds faster than your 401K investments, so every day I learn something new is a good day.