Even if you try 10,000 times, the probability won't increase if you use the same method

“Just keep trying until you succeed.”

This is a common saying.
Of course, if you increase the number of attempts, the likelihood of succeeding by chance at some point increases. However, simply repeating the same method will not increase the probability of success per attempt.

Even if you try 10,000 times, if you are failing under the exact same conditions, with the same mindset, and using the same method every time, it might not be a challenge so much as repeating the same failure 10,000 times.

In this article, I will write about the difference between the number of attempts and the probability of success, and about a way of thinking that allows you to gradually turn 'luck' into something you can manage.

Life cannot be explained by probabilities like a lottery

In a lottery, the winning probability per ticket is basically fixed.

The probability per ticket does not change significantly based on the buyer's knowledge or experience, and the probability of the lottery itself does not change even if you grow as a person.

On the other hand, life and work are different.
You are not the same person in your first attempt as you are in your 100th attempt.

You see the conditions that led to failure and why things didn't go well.
You come to understand the other party's reactions.
You can gradually understand your own strengths and weaknesses.

If you increase your decision-making data and change your methods each time you try, the probability of success in life and work will also change.

The probabilities in life can be changed through your own actions and improvements.

This is the major difference from a lottery.

With the same method, the probability of success in life will not increase either

For example, suppose you are pitching a new service to companies.

You give generative AI an abstract instruction like,
“Please create a sales DM for companies. Make it a message that conveys the appeal of the service and leads to inquiries,”
and send the finished text to 100 companies with almost no revisions.

However, it is quite possible that the result will be no response from all 100 companies.

Even then, you might think,
“Maybe I just haven't sent enough,”
and generate a similar DM to send to another 100 companies.

The number of attempts increases, but if the following remain vague:
・What kind of problems the other party is facing
・Why this service is needed now
・How it differs from other services
・What benefits it offers the other party
the probability of success per message will hardly increase at all.

What is needed is not to send a large number of the same DMs, but to think about why there was no response and to change the content and delivery method to suit the recipient's challenges.

Sending the same message to 100 companies is not 100 trials and errors.
It is just repeating the same hypothesis to 100 companies.

Generative AI has increased 'easy effort'

Generative AI has made it possible to create large amounts of text, images, and project proposals.
What used to take a whole day to create can now be generated in 10 or 100 variations in just a few minutes.
In terms of increasing the number of trials, this is a very significant step forward.

However, there is a pitfall here.

It is easy to mistake having generated a lot for having gone through a lot of trial and error.

If you only use generative AI for mass production, what increases is the number of outputs. The number of outputs and the number of learning cycles are not the same.

When you generate in large quantities, it is easy to feel that 'I have made this much, so I have put in the effort.' However, if you do not check why it didn't work and generate under the same conditions again, it becomes an easy effort.

That is precisely why what you learned and what you changed next, rather than how much you created,becomes more important.

Data only has meaning when compared

If you repeat the process, the data will increase. However, even if you collect results from the same conditions, you won't see what you should change next. What is necessary to increase the probability of success is to change the conditions little by little and compare the results.

For example, with note, you can:
・Change only the title
・Change the target audience
・Change the opening sentence
・Change the price
・Change the posting time
・Change the order of the explanation

Then, compare the results.
By doing so, things will gradually become clear.

'This element tends to lead to failure'
'This condition gets a good response'
'I have plenty of material for this theme'

Of course, once or twice might just be a coincidence.
However, if you try while changing conditions and record the results, you will see trends that are difficult to explain by coincidence alone.

Only here does data become material to increase the probability of success. Instead of just repeating the number of times,

① Formulate a hypothesis
② Try it
③ Verify
④ Revise

It is important to cycle through this process.

Increase the number of learning cycles rather than the number of attempts

If you learned during the process of trying 10,000 times and kept changing your approach, that has great value. However, the important thing is not the number 10,000.

What did you learn from each attempt?

Rather than repeating the same method 10,000 times,
it is better to try 10 times, look at the results of each, change the conditions,
and reduce the factors that lead to failure.

That will increase your probability of success.

Generative AI has made it easy to increase the number of attempts.
That is precisely why, from now on, rather than those who can "create in bulk,"

・People who can decide what to verify
・People who can notice differences in results
・People who can articulate the causes of failure
・People who can change the next set of conditions

I believe the value of these people will increase.

It is not just the number of attempts that increases the probability of success in life.
It is the learning ability to change your approach each time you try.

Luck is an uncertain factor if left as is.

However, if you change your approach, record, reflect, and experiment, you will begin to see parts of what you thought was luck that you can actually influence.

Life cannot be described by fixed probabilities like a lottery.

That is why I want to take on challenges that change the probability itself, rather than just increasing the number of attempts.

For those who want to think a little more about how to handle "luck"

In this article, I wrote about the mindset of increasing the probability of success by reflecting on results and changing conditions and approaches, rather than repeating the same challenge.

However, it is not just actions and improvements that determine the results of life and work.

・Where you put your effort
・Who evaluates you
・When you decide to act
・What you continue and what you stop
・How you recover when things don't go well

These factors also have a significant impact.

I have compiled 15 articles I have written so far regarding "luck, effort, environment, evaluation, action, and recovery" here.

I hope this will be read by those who want to gradually increase what they can do themselves, rather than ending things by saying "I was just unlucky."