DEV Community: Shubham Thakur

what mindset do most of the successful People have ?

Shubham Thakur — Wed, 11 Mar 2026 17:17:37 +0000

Q. Why Becoming Rich Often Means Breaking the “Normal” Rules

Most of us grow up hearing the same advice.

Study hard.
Get good grades.
Find a stable job.
Work for 30–40 years.
Save money and retire.

It sounds logical. And for many people, it works well enough to live a stable life.

But here is something rarely discussed:

This system is designed for stability, not wealth.

If your goal is only security, the traditional path works perfectly. But if your goal is financial freedom or significant wealth, you often have to think and act differently from what society teaches.

Let’s talk about why.

The System Trains You to Be an Employee

From school to college, most of our education system prepares us for one role: being a good employee.

You are rewarded for:

Following instructions

Memorizing information

Avoiding mistakes

Staying within the rules

But the real world of wealth works differently.

Entrepreneurs, investors, and creators often succeed because they question rules instead of following them blindly.

They experiment.
They fail.
They try again.

These are things traditional education rarely encourages.

Hard Work Alone Doesn’t Create Wealth

One of the biggest beliefs we grow up with is:

“Work harder and you will earn more.”

But in reality, many of the hardest-working people in the world are not wealthy.

Construction workers, farmers, delivery drivers, and factory workers work extremely hard every day.

So what is the difference?

The difference is leverage.

Leverage means using tools that allow your effort to multiply.

Examples of leverage today include:

Technology and software

The internet

Businesses

Investments

Digital products

A developer who builds an app can earn money from thousands of users.
A YouTuber can reach millions of people with one video.
A startup founder can create a product used worldwide.

Their income is not limited by hours alone.

Employees Trade Time for Money

Most jobs follow a simple formula:

You give time → you receive money.

The problem with this model is simple.

There are only 24 hours in a day.

No matter how talented you are, you cannot keep increasing your income if it depends entirely on your time.

Wealthy people usually try to separate income from time.

They build assets such as:

Businesses

Software products

Investments

Intellectual property

Online platforms

These assets can generate income even when they are not actively working.

Society Rewards Safety

Another invisible rule society teaches is:

Play safe.

Avoid risk.
Don’t fail.
Don’t try unusual things.

But almost every major innovation came from someone who ignored this rule.

People who built companies like Apple, Amazon, or Tesla were not simply following safe career paths.

They were taking risks.

Of course, risk should be calculated, not reckless. But avoiding risk completely often means avoiding opportunity as well.

The Fear of Being Different

Sometimes the biggest barrier to success is not skill or intelligence.

It is social pressure.

People worry about questions like:

“What will others think?”

“What if I fail?”

“What if I look foolish?”

Because of this, many people stay in paths that feel safe even when they are not fulfilling.

The truth is, doing something extraordinary often requires being comfortable with standing out.

Breaking the Rules Doesn’t Mean Being Irresponsible

Breaking the “rules” does not mean ignoring responsibilities or acting carelessly.

It means questioning default assumptions, such as:

Only relying on a salary

Believing job security is guaranteed

Avoiding ownership opportunities

Never exploring side projects or businesses

Many successful people still work hard, but they focus on building ownership and long-term value.

The Real Path to Wealth

While there is no guaranteed formula for wealth, many successful individuals share common principles:

They focus on ownership rather than only employment.

They use technology and leverage to scale their work.

They think in long-term horizons, not quick wins.

They continuously learn and adapt.

Most importantly, they do not automatically accept the idea that there is only one correct path in life.

Final Thoughts

The traditional path of education and employment is not wrong. It has helped millions of people build stable and meaningful lives.

But if someone wants to create extraordinary wealth or impact, they often need to think beyond conventional rules.

Sometimes the biggest step toward a different future is simple:

Stop assuming that the default path is the only path.

Question it.
Understand it.
And then decide your own direction.

source : https://youtu.be/ZR4jX6L1kCM?si=SZX71Dtydzmw66YN

what mindset do most of the successful People have ?

Shubham Thakur — Wed, 11 Mar 2026 17:17:37 +0000

Q. Why Becoming Rich Often Means Breaking the “Normal” Rules

Most of us grow up hearing the same advice.

Study hard.
Get good grades.
Find a stable job.
Work for 30–40 years.
Save money and retire.

It sounds logical. And for many people, it works well enough to live a stable life.

But here is something rarely discussed:

This system is designed for stability, not wealth.

Let’s talk about why.

The System Trains You to Be an Employee

From school to college, most of our education system prepares us for one role: being a good employee.

You are rewarded for:

Following instructions

Memorizing information

Avoiding mistakes

Staying within the rules

But the real world of wealth works differently.

Entrepreneurs, investors, and creators often succeed because they question rules instead of following them blindly.

They experiment.
They fail.
They try again.

These are things traditional education rarely encourages.

Hard Work Alone Doesn’t Create Wealth

One of the biggest beliefs we grow up with is:

“Work harder and you will earn more.”

But in reality, many of the hardest-working people in the world are not wealthy.

Construction workers, farmers, delivery drivers, and factory workers work extremely hard every day.

So what is the difference?

The difference is leverage.

Leverage means using tools that allow your effort to multiply.

Examples of leverage today include:

Technology and software

The internet

Businesses

Investments

Digital products

A developer who builds an app can earn money from thousands of users.
A YouTuber can reach millions of people with one video.
A startup founder can create a product used worldwide.

Their income is not limited by hours alone.

Employees Trade Time for Money

Most jobs follow a simple formula:

You give time → you receive money.

The problem with this model is simple.

There are only 24 hours in a day.

No matter how talented you are, you cannot keep increasing your income if it depends entirely on your time.

Wealthy people usually try to separate income from time.

They build assets such as:

Businesses

Software products

Investments

Intellectual property

Online platforms

These assets can generate income even when they are not actively working.

Society Rewards Safety

Another invisible rule society teaches is:

Play safe.

Avoid risk.
Don’t fail.
Don’t try unusual things.

But almost every major innovation came from someone who ignored this rule.

People who built companies like Apple, Amazon, or Tesla were not simply following safe career paths.

They were taking risks.

Of course, risk should be calculated, not reckless. But avoiding risk completely often means avoiding opportunity as well.

The Fear of Being Different

Sometimes the biggest barrier to success is not skill or intelligence.

It is social pressure.

People worry about questions like:

“What will others think?”

“What if I fail?”

“What if I look foolish?”

Because of this, many people stay in paths that feel safe even when they are not fulfilling.

The truth is, doing something extraordinary often requires being comfortable with standing out.

Breaking the Rules Doesn’t Mean Being Irresponsible

Breaking the “rules” does not mean ignoring responsibilities or acting carelessly.

It means questioning default assumptions, such as:

Only relying on a salary

Believing job security is guaranteed

Avoiding ownership opportunities

Never exploring side projects or businesses

Many successful people still work hard, but they focus on building ownership and long-term value.

The Real Path to Wealth

While there is no guaranteed formula for wealth, many successful individuals share common principles:

They focus on ownership rather than only employment.

They use technology and leverage to scale their work.

They think in long-term horizons, not quick wins.

They continuously learn and adapt.

Most importantly, they do not automatically accept the idea that there is only one correct path in life.

Final Thoughts

The traditional path of education and employment is not wrong. It has helped millions of people build stable and meaningful lives.

But if someone wants to create extraordinary wealth or impact, they often need to think beyond conventional rules.

Sometimes the biggest step toward a different future is simple:

Stop assuming that the default path is the only path.

Question it.
Understand it.
And then decide your own direction.

source : https://youtu.be/ZR4jX6L1kCM?si=SZX71Dtydzmw66YN

“What Chapter 1 of a Hundred pages of Machine Learning Book Taught Me"

Shubham Thakur — Thu, 26 Feb 2026 22:40:03 +0000

Introduction

I recently finished Chapter 1 of a machine learning book. This chapter wasn’t about building models or writing code. Instead, it focused on something more important: building the right mental model of what machine learning actually is.

Here’s what I learned from just the first chapter.

What Machine Learning Really Means

At its core, machine learning is a simple process:

a) Gather data

b) Build a statistical model from that data

c) Use the model to solve a real-world problem

The “learning” part means we don’t hard-code rules. We let the algorithm find patterns from examples.

Types of Learning

Supervised learning: Data comes with labels (x, y).

Unsupervised learning: Data has no labels, only inputs x.

Semi-supervised learning: A mix of a few labeled examples and many unlabeled ones.

Reinforcement learning: An agent interacts with an environment and learns from rewards.

In practice, supervised learning is the most commonly used, so the chapter focuses mainly on that.

Features and Labels

In supervised learning, each example is represented as a feature vector.
Each feature is just a number describing some aspect of the object (for example, an email, an image, or a person).

The label is what we want to predict: a class (like spam / not spam) or a number.

So the learning problem becomes:
Learn a function that maps feature vectors to labels and works well on new data.

Decision Boundaries and SVM

To explain classification, the chapter introduces Support Vector Machines (SVM).

SVM views each example as a point in a high-dimensional space and tries to separate classes using a decision boundary, defined by:

wx − b = 0

Prediction is done using:

sign(wx − b)

In simple terms, the model checks which side of the boundary a point lies on.

Why Margin Matters

SVM doesn’t just look for any separating boundary.
It looks for the one with the largest margin — the maximum distance from the closest points of both classes.

Why?
Because a larger margin usually means better generalization, i.e., better performance on unseen data.

This leads to an optimization problem:

Minimize ||w||
Subject to: yᵢ(wxᵢ − b) ≥ 1

Training, in this view, is simply solving this optimization problem.

Why Models Work on New Data

The chapter also explains why machine learning models can work on new examples.
If training data and future data come from the same distribution, new examples are likely to appear near old ones. A well-chosen decision boundary will still separate them correctly most of the time.

More data usually means a better approximation of reality — and fewer surprises.

Your Biggest Mistake Isn’t Failing — It’s Overthinking and Never Executing

Shubham Thakur — Sun, 08 Feb 2026 05:41:18 +0000

"Your Biggest mistake is not doing mistakes"
Few years ago I always found myself in Analysing Paralysis loop.
*Main problem: *
I always try to get the best learning resources , make things perfect, perfect environment so that I do not make a mistake because I think it will waste time.
In order to save my time I used to research a lot about things and not able to implement things on ground level.
This basically happens because there are a lot of free learning resources available ,With this entire loop of making a perfection I was not able to complete a task.
This analysis paralysis loop drain energy.
I always disrespect my word of mouth
I used to say I will do this thing but later i am not able to finish the job then I question myself if i do not respect my word of mouth how will others do ? Always question yourself !
Solution to this problem:
Stick to one resource at a time , finish it then move to other
Even if that resources of learning is not worth it let mistake happen
Do not over analyse things
If you again overthink then put your mind into execution phase
If you keep on learning and executing things then fear will automatically gone .
Now I put my majority time in execution instead of what things to do what not to do .
In analysing paralysis loop you feel like you're doing something beneficial but actually you are not learning.