The Jewish Decade
Learn to acquire wealth, wealth to acquire learning
Cotton Bro Studios
This week I hosted Mati Gill, CEO of AION Labs on my podcast - Life Sciences Today.
AION Labs is a venture studio backed by some of the biggest names in the business: Merck, AstraZeneca, Pfizer, Teva, and AWS. Their mission? Nothing short of shaping drug discovery and development with AI and deep tech. Stay tuned for the show - it’ll be coming soon on a podcast channel near you!
Today, I talk about why we are in The Jewish Decade.
AI makes it easier than ever to start a new business and harder than ever to accumulate wealth from it.
The key (and it's not easy) is learning how to learn.
Introduction
Modernization is about everyone becoming urban, mobile, literate, intellectually intricate, physically fastidious, and occupationally flexible.
It is about learning how to cultivate people and symbols, not fields or herds.
It is about pursuing wealth for the sake of learning, learning for the sake of wealth, and both wealth and learning for their own sake.
– Yuri Slezkine, “The Jewish Century”, 2004, Princeton University Press
It’s easy to start. It’s hard to acquire wealth
It’s easy to start
AI chats make it easy to research your idea, target market and ideal customer profile. If you’re convinced that it’s worth a try, you can spin up a splash page and a registration form and see how people like your offer. You can test demand without investing a lot of money in code development.
It’s much harder to convert a good idea into wealth.
There are 3 reasons for this:
Competition - Since AI makes it so easy to start, and so easy to build a new business; it’s likely you’ll have a lot of competition.
Failure patterns
Not understanding what business you are really in.
What sets you apart from the competition is your ability to execute.
Execution means two things: solving the failure patterns and truly understanding what business you’re in.
I’ll give examples of both.
There are anti-patterns working against you; like running out of money, like losing touch with your customers, like not selling high enough.
👉 Get my free ebook with 22 anti-patterns that will make you fail.
But that is not enough
Even if you solve all the anti-patterns, you may not correctly understand what business you are in.
You're probably in a completely different business than you think.
When I got into cyber for medical devices, I thought I was in the software security business. I wasn't. I was a concierge opening doors for companies who needed HIPAA compliance to sell their medical devices. Companies paid me a lot of money to be a concierge.
When I got into software distribution, I thought I was in the product business. I wasn't. I was in the operational systems business. Anyone can distribute software, Most cannot make money on distribution. For that - you need exceptionally efficient operational systems and that requires capital.
Once I flipped my mindset, we went from $1M to $20M in annual revenue within 2 years.
To find your real business, ask successful people in your industry: "What's the hardest part of your business?"
Look at the most successful companies in your space - what are they exceptional at?
Find your constraint - what's keeping you from doubling revenue? You may be in a comfort zone.
Entrepreneurs get comfortable solving problems they know how to solve, then wonder why they don’t grow the business.
Ask yourself what you need to do to fail and solve those problems. Identify what business you're REALLY in.
This sets you apart from the competition.
Learning how to solve problems in your business is leverage. But only if you’re learning the right thing in the right way.
Pursue learning for wealth
In the early 19th century, 32 of 52 private banks in Berlin were owned by Jewish families. The greatest German joint stock banks including Deutsche Bank were founded with the participation of Jewish financiers.
Jews tended to base social status on personal achievement, associate achievement with learning and wealth, sought learning by reading and interpreting texts, and pursued wealth by cultivating human strangers, rather than land, gods or beasts. - Yuri Slezkine, The Jewish Century, page 46
In 20th century Israel, the tradition of pursuit of learning to achieve wealth continues with outstanding examples in Israeli tech companies like Prof. Amnon Shashua and Dov Frohman, inventor of the EEPROM and founder and CEO of Intel Israel.
However, the traditional definition of wealth as an accumulation of capital is incomplete.
The Jewish book - Pirkei Avot (Ethics of the Fathers), is a compilation of ethical teachings and maxims from the Mishnaic period.
"Who is rich? He who is happy with his lot."
(Pirkei Avot 4:1)
This teaching emphasizes the idea that true wealth is not measured by material possessions or external success but by inner contentment and the ability to appreciate what one has.
It's a reminder that happiness and satisfaction come from within, and a person who finds contentment in their current circumstances is truly rich.
That sounds just like the Buddhist eightfold way.
Not the Silicon Valley way.
I wrote an essay on this here - The Symmetry of Wealth
Pursue wealth for learning
For European Jews, money was one means of advancement, education was another. The two are closely connected of course. In modern Europe, education was expected to lead to money; only among Jews was money expected to lead to education. In Germany, 51% of Jewish scientists had fathers who were businessmen.
Korea is one of the most striking modern examples of a society that has used education as a structured, collective path to social mobility—so much so that it’s often compared to the Jewish emphasis on learning.
Contrast this with the Jewish model, where learning was not just for credentials or jobs—but a lifelong cultural and religious duty. The Talmud Torah model is deeply internal, communal, and recursive. In contrast, Korean education has been more credential-focused—though both cultures show how sustained learning can lift entire populations.
For many Jews, the transition from the study of Torah to the study of chemistry, biology, physics and mathematics was especially successful.
5 out of 9 Nobel prize winners in science during the Weimar years went to Jewish scientists. In the past 20 years - approximately 20% of Nobel laureates in science are Jewish.
Learning how to learn
It is about pursuing wealth for the sake of learning, learning for the sake of wealth, and both wealth and learning for their own sake.
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.
Your memory is 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. You can 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 new to a field - like using AI to develop code.
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.
When you learn something new, 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 wealth|health|joy picture.
When you learn a new concept (like coding with AI), your brain switches between an abstract idea (programming) with concrete examples (4-5 code snippets and what they do).
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.
Spacing and repetition matters
To learn something new and get really good at it (like making big money with AI coding), you learn how to do it in a loop with breaks between each learning session. You cannot “just do it”. You are not Nike nor MJ.
Each test run of your code, helps you improve your programming skills.
Cramming for the test never worked in school and doesn’t work for any learning objective.
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.
You outsourced the learning. And when the context changes—you’ll have nothing to adapt with.
And one more thing - your brain is faster than a LLM and it only requires 26 watts of power.
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 data model design.
Experts can tell 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.
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.
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 programming, 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 for your business. Free cash flow counts. Not how many YT videos you watched on how to use Lovely.
Conclusion
“Modernization is about everyone becoming Jewish.”
—Yuri Slezkine, The Jewish Century
Slezkine wasn’t talking about religion. He was talking about survival.
About how a small group of people—forced out of land ownership and manual labor—turned to learning as their only portable asset. Not just learning facts. Learning how to learn. Across languages, markets, regimes.
In a world where AI is automating everything from copywriting to code, that playbook suddenly feels urgent again.
Because AI makes it easier than ever to launch something—and harder than ever to build lasting wealth from it.
This decade rewards people who treat learning as a lifelong, active discipline.
Not just consuming more. Rewiring faster. Recovering better.
We live in The Jewish decade.
Build portable wisdom. Cultivate symbolic capital. Learn how to learn. That’s the wealth AI can’t touch.
Life Sciences Today is my brand-new podcast
I host leaders in life sciences. We talk about their personal journey. I dive into the business model and how the company captures value - not just how shiny the tech is.
Check out my conversation with Orr Inbar of QuantHealth on the podcast.
We dive into how their predictive platform helps pharma select better drugs and optimize trials — a masterclass in turning domain expertise into value.
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