10 things about learning how to learn

Experts can sell you stuff but they can’t jack into your mind

Introduction

I originally wrote this piece 2 years ago. It was the design-pattern that closed my series on substack - “Bob and Alice - Anti-Design Patterns in Life, Love and Tech”.

The last chapter in Bob and Alice, was called Hezbollah is here - which is familiar to Israelis as we go into season 3 with Iran - or is it season 5? I’m not sure.

My substack series turned into a book on Amazon - Bob and Alice - an anti-love story.

I get a check every so often from Amazon from people who buy the book. Amazing.

Hint. Hint.

I did the cover graphic with ChatGPT 3.5. I kind of like it a lot.

Happy with what you know or overloaded by work?

Life, love and tech require constant learning, yet we are often happy with what we already know or overloaded by the work we already have - and left with no energy at the end of the day to learn new things.

This 10-part design pattern was inspired by my friends and co-workers - the people who served as the role models for characters in the series and in the book - Alice, Bob, Pesya, Yasmin, Mark and the rest of the team at Giganet. The names have been changed but the people are real.

My thanks to you all for teaching me how to learn.

10 things you should learn about learning

1. Your memory is not digital
   Fetching a memory strengthens and modifies that memory.
   
   When you try to remember something, activation energy spreads to all the connected pathways in your brain, like heat from a fire.
   
   Some of the activation energy leaves related pathways primed for more activation for hours.

2. Your memory is not continuous - it’s made of chunks
   Long-term memory is limitless, like a disk with an infinite amount of storage.
   Working memory serves general intelligence. It’s limited and can be trained like professional musicians who practice 10 hours/day.
   
   The brain works on information in chunks.
   
   Reduce your cognitive load by getting rid of irrelevant data and by organizing it in an easy-to-use format - like a table instead of wordy content.
   
   When you learn new things, you can improve your performance by chunking and reorganizing the task.
   
   This is really important when you’re learning a new skill or a new language.

3. Experts recognize, beginners reason
   Experts have seen it all before.
   
   They recognize and remember the patterns that helped them succeed in the past and the anti-patterns that led them to failure.
   
   This happens in less than a second.
   
   Experts can figure things out because they memorized the pattern from experience.
   
   This pattern-matching gives you superpowers in your field of expertise - be it code, marketing or whatever.
   
   Beginners need to see examples and figure things out.
   
   It’s a process that can take hours or days and beginners usually get it wrong.

4. When you learn, the brain flips back and forth from concrete to abstract
   Experts rely on generic and abstract patterns, and don’t need to worry about details.
   
   Beginners get stuck in details and have trouble connecting to the big picture.
   
   When you learn a new concept (like AI agents), your brain switches between an abstract idea (autonomy) with concrete examples (agents reading your email and filing supplier invoices).
   
   The more examples, the better. Mistakes are good. This process in the brain is called unpacking.
   
   You learn better when you flip back to examples from the abstract pattern. This is called repacking.
   
   The more you learn abstract patterns, the more concrete they become for you.

5. Spacing and repetition matters
   To learn something new and get really good at it (like playing the flute), you need to learn how to do it with a lot of repetitions and with breaks between each learning session.
   
   You cannot “just do it”. You are not Nike nor MJ
   
   Each little learning session, each little debug session helps you get better.
   
   Cramming for the test never worked in school and doesn’t work for any learning objective.

6. AI does not obsolete learning
   We learn by making connections between stuff in our brain.
   
   This creates a deep understanding of what stuff means and how to use it.
   
   Once memorized, you can retrieve a problem and the solution in a milli-second.
   
   With AI, you need to write a prompt, try it out a few times and then modify it for your needs.
   
   You won’t remember the solution because you didn’t learn it yourself; you copied and pasted.
   
   And it’s much slower than your brain

7. Problem-solving is not a generic skill
   Almost all of our generic skills are far worse than domain-specific problem solving.
   
   Our generic understanding of selling something is almost irrelevant for a specific domain like agentic AI.

8. Experts can sell you stuff but they can’t jack into your mind

It is almost impossible for an expert to jack into your mental model if you are a beginner.

You will probably fail if you buy a course online from a large account on social media.

9. Predictors of success in any given discipline are bad
   Success of learning a new discipline like copy-writing is a mix of your aptitude and your learning process.
   Some people believe that a natural gift is enough.
   Others say that practice and systems are enough.
   
   Both groups are wrong.
   
   It’s impossible to predict who will be a good programmer|copy-writer|marketer | salesman | manager.
   
   Smart people are not always good programmers. Good programmers are not always the smartest.

10. Your mindset matters to your success but not like you think
    There are people who believe in a growth mindset. Practice long enough and believe in your success and success, wealth and happiness will come.
    
    Other people believe in a fixed mindset and aptitude. If you struggle with success in developing Agentic AI apps, it means that you are not cut out for it.
    
    Both groups are wrong.
    
    For example - anyone can learn some basic physics but only 1 person/year out of 7.8 BN people gets the Nobel Prize in Physics.
    
    Rewarding a growth mindset for effort doesn’t work either
    
    People are not stupid - they know when they are working hard and not getting results.
    
    Rewards should be focused on achieving goals.

Summary

• Improve your learning skills all the time. Work with a person who keeps you accountable.

• There are no fixed rules about who is good at something be it leadership, music or marketing

• Read a lot of code to be a better programmer. Read a lot of copy to be a better copy-writer

• Experts are bad at training beginners

• Spending time away from a problem can help solve it.

• Using AI does not make you an expert. You still need to learn and develop the deep memories and patterns in your brain.

• Believe in your ability to change your abilities

• Seeking to succeed is better than seeking to avoid failure.

About me

I’m an entrepreneur, writer, host of Life Sciences Today podcast, ex-pharmatech founder, father of 4 and founder of OpenCRO.

OpenCRO specializes in threat modeling for FDA Cyber. After working with 42 MedTech companies and 14 FDA clearances on cyber and privacy projects - I decided to create boutique offer for medical device companies who care about their patients, their clinical data and their reputation.

Fixed price. Fixed outcome.

Book a call to see if you’re a good fit for OpenCRO.

Not sure yet? Sign up for the 2026 CEO Audit — 60 minutes on your operation, unlimited access to my patterns library.