Learning how to learn in this new world is a foundational skill and prerequisite for embracing being a “continuous learner”. Without it, the pace of change and the volume of information can throw us into an unproductive spiral. Without the right foundation, we can get trapped spending enormous amounts of time “learning” yet reap few results. Time is the largest cost we all share, and effective learning strategies are key to reducing that cost.
I’d like to share 4 principles of effective learning that I have developed through trial, error, more error, and the pursuit of continuous improvement. These principles can be applied to you own natural rhythms to drive efficient knowledge acquisition. They have transformed how I approach new topics and I hope they’ll provide the same benefit for you.
Principle 1: Be Selective About Your Sources
With millions of new videos being uploaded to YouTube daily, and countless blogs, articles, and social media posts being published, it’s easy to get overwhelmed in the torrent of new content.
This excess is why deliberately choosing what to spend your time on, and the sources that you’ll leverage during that time, is so important. Here are a few tactics to help you make the best of your sources:
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Quality over quantity: Choose sources known for depth and accuracy over those optimized for clicks and ad-based revenue
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Relevance filtering: Ask yourself, “How does this connect to my current projects or goals?” (more on this later)
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Source diversity: While being selective, ensure you’re not creating an echo chamber. If you’re finding a lot of “benefits of X” deliberately search for the “harms” or “downsides of X”.
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Time-boxing: Set limits on discovery time to prevent endless browsing.
Principle 2: Mental Energy Has Highs and Lows
I’m now thoughtful about when I learn. I used to attempt to learn things very late at night after a long stressful day. Now, I prefer to unwind with reading or some mindless video gaming that late, and leave the deliberate & focused study sessions to the morning when I’m fresh. I used to believe that I could still learn during late night study sessions, and while yes, I did learn, it wasn’t effective and efficient use of my time.
My learning schedule now looks like this:
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Weekday Morning Focused Sessions: This is when I focus on quick concepts and reviewing the latest advancements or conduct research for that day’s tasks.
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Evening Wind-Down: I prefer light reading and/or mindless video games to unwind when my energy is low.
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Weekend Deep Dives: This is when I find time to really dig in and experiment hands-on with the technology I’m learning about.
The key across all of these is matching your energy with what you’re trying to accomplish.
Principle 3: Build on Existing Knowledge
Information without connection is trivia. Truly powerful learning occurs when you’re able to connect the information to other concepts and uses that you already know. This is beneficial to expand a known truth that may be outdated, to challenge existing assumptions about what’s possible, and enables you to understand it through analogy.
Questions to consider when encountering such new information:
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How does this challenge or support my current understanding of the topic?
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Where can this information influence or apply directly to a current project?
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What other concepts are connected to this?
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If I was trying to “Explain It Like I’m 5”, how would I do so?
By actively engaging with information rather than passively consuming it, you transform data into actionable knowledge.
Principle 4: Get Your Hands Dirty
Reading about something and actually doing it are completely different experiences. Theory gives you the maps, but practice makes you familiar with the territory. Whenever possible, I look for ways to dig in and apply new concepts quickly and tangibly.
As mentioned in my first post, that principle is a key part of this year’s blogging effort. When I wanted to better understand development with AI tools, I didn’t limit myself to reading articles, pouring through official documentation, and consuming YouTube videos; I built real applications that provide benefit to me.
The application I use to brainstorm, draft, refine, and publish my writings is one such personal application. It has revealed differences in Google’s Gemini CLI and Anthropic’s Claude Code that didn’t come up in my research.
For instance, I know that Gemini needed its GEMINI.md file updated to instruct it to make changes only to the source code and then rebuild and redeploy the containers. I didn’t want it directly modifying the running containers as we would then have drift from the source files. Claude didn’t need this coaching, it intuitively knew that was a better way of doing things, and always rebuilt my containers from source without being instructed.
These are the types of insights that come from direct experience, not documentation.
The Continuous Learning Mindset
Learning how to learn is a continuous refinement process. Your optimal methods will evolve as your circumstances change, but these foundational principles provide a reliable framework for adaptation for experienced learners and a starting point for novices.
In a world where information is abundant but wisdom is scarce, the ability to learn effectively becomes your greatest competitive advantage. How do you learn? More importantly, how could you learn better?
🤖 AIL LEVELS: This content’s AI Influence Levels are AIL1 for the writing, and AIL4 for the images. AI Influence Level (AIL) framework