Tips from a chronic learner

How do you stay motivated when learning something new?

Tip #1: do it for the right reasons.

What are the right reasons to learn something new? Many.

Spending quality time with a loved one.

Exploring a possible passion.

You want to be braver.

These are all good reasons. If you can rationalize it as something useful or as something that helps you in your life, then it’s worth it.

Tip #2: be open-minded.

If you’re unsure about a new hobby, skill, etc. just start something, which ChatGPT, Claude or a locally hosted AI model can work with you to plan out.

While many people would criticize such an approach for ideation, the reality is that manual trial and error also waste precious time.

At the start, you also don’t know how to begin in the first place, that’s something you learn along the way, rather than at the beginning.

If you want to learn how to code but you’re not sure about how to start, use an AI chatbot to start a very simple project, like a web page.

If you want to learn how to draw, start simple and use your iPad or a notebook to doodle.

It’s not about faking it but, instead, about just making it happen.

Allow yourself every opportunity to improve if these opportunities are within reach.

Tip #3: dive as deep as you can.

Where I think AI really shines is that it can help you reach the deep end in a relatively short amount of time.

For instance, I never knew how to deploy an application using a specific technical stack. However, with the help of AI coding tools and chatbots, I now have numerous websites that use that stack.

No, you won’t learn every single thing about your project by building large, but gaining exposure is the first step to success.

And this is something you can do with many skills, such as art by getting a large piece of canvas, or with music by starting a song on Ableton Live.

Tip #4: be resilient.

You will fail and you must fail.

Allow yourself to fail.

Allow yourself to have fun and experience joy.

Allow yourself to live life.

This is the biggest lesson that I’m still in need of learning, considering my circumstances.

Still, it’s something I’m putting into practice from vibe coding to software engineering and physical and digital art. I choose to have fun because I know that it’s the only way for me to become resilient.

Tip #5: know when to quit.

Not all things deserve your time, effort and dedication.

Maybe it turns out that you were learning something new for the wrong reason.

Or you’re getting so frustrated that it’s no longer fun.

Unless it’s something extremely important to your survival, you can usually be happier by simply quitting something new.

At the same time, you can quit something important to your survival if it no longer serves you.

That’s how I approached my career.

While I miss many of the people I used to work with, I could no longer see myself being the person that I was at work.

The career wasn’t for me.

The job wasn’t for me.

The company wasn’t for me.

But this isn’t time wasted.

It’s experience earned.

Something to be grateful for in that specific context of learning.

Speaking of…

Tip #6: Learn to reflect

Balance is everything.

So many of your lived experiences hold keys to important life lessons.

Start meditating.

Start praying (if you’re into that).

Start thinking deeply.

Start feeling deeply.

Be more mindful.

Don’t jump to conclusions.

Being more reflective is necessary for you to learn the best and the most that you can.

Tip #7: AI is not an excuse

While I use AI every day, I’m still a fan of human creativity, I just know the difference between actual AI slop and AI as a collaborative tool.

This perspective took me a lot of trial and error, getting educated, and personal interactions but, overtime, I learned to empathize with how AI users can express their creativity with a combination of personal context and meaningful prompts.

I also learned that I don’t have to be pro-Big Tech to recognize the benefits of AI.

AI can be ethical if we demand that it be.

AI’s best work occurs when its impact is publicly invisible and in full collaboration with knowledgeable humans.

And that’s the key.

Machine learning is probabilistic but humans make judgment calls and have experiences that generative AI, at this point, cannot replicate.

In the same way that typing is not a reason to stop handwriting, AI is meant to be a complement to your learning and implementing what you learn next.

But your human judgment is still necessary to determine the value of that AI-generated result.