There Is No Universal Perfect Rule
A lesson I learned from overthinking everyday decisions
Sometimes we ask questions that sound simple:
How many apps should I have on my phone?
How many people should I follow on social media?
What is the perfect way to organize my files?
What is the best filename for a book?
Should every book have a unique ID?
What is the perfect folder structure?
What is the best productivity system?
What is the correct way to do something?
At first, these questions seem reasonable.
After all, if there is a best way to do something, why not find it?
But there is a problem:
For many everyday decisions, there is no universal perfect rule.
And realizing this can save an enormous amount of time, frustration, and mental energy.
The desire to find the "correct" answer
Human beings naturally like certainty.
When we have several choices, we often want to know:
"Which one is actually correct?"
This is useful when the answer really matters.
For example:
What is the correct mathematical formula?
What command should I use to solve a technical problem?
What are the requirements for an application?
What does a particular law say?
These questions may have relatively precise answers.
But many everyday decisions are different.
Consider:
How many apps should I install on my phone?
Is the answer 20?
30?
50?
100?
There is no universal number.
One person's 30 apps might be excessive, while another person's 80 apps might be perfectly reasonable because they use those apps for work, study, communication, banking, entertainment, and other purposes.
The answer depends on the person, purpose, device, and circumstances.
The same problem appears everywhere
I began noticing that this wasn't limited to one particular topic.
The same thinking can appear in many areas.
1. File naming
Suppose you have a PDF book.
You might name it:
Author - Title - Year.pdf
That is perfectly reasonable.
But then another question appears:
Should I include the publisher?
Perhaps:
Author - Title - Year - Publisher.pdf
Then:
What if there are two editions?
Maybe add the edition.
Then:
What if two books have the same author, title, and year?
Perhaps add an identifier.
Then:
Should the identifier be at the beginning or end?
Then:
Should it be a timestamp?
Then:
What do libraries do?
Then:
What does IEEE do?
Then:
What happens if I have millions of files?
Suddenly, a simple filename has turned into a major research project.
The original goal was simply:
"I want to be able to find my book easily."
At some point, the optimization became more complicated than the actual problem.
2. Digital library organization
The same thing can happen with a digital library.
You might have hundreds of books and think:
"I need a good folder structure."
You create one.
Then you wonder:
"Is this how professional libraries organize books?"
Then:
"Should books have IDs?"
Then:
"Should papers have different IDs?"
Then:
"Should the filename contain the ID?"
Then:
"Should the database handle the ID instead?"
These are legitimate technical questions.
But there isn't necessarily one universal architecture.
A personal collection, a university digital library, a research repository, and a commercial publishing platform have different requirements.
The correct system depends on the purpose of the system.
3. Phone and app organization
Even something as simple as a phone can become an optimization problem.
You might ask:
"How many apps should I have?"
Then:
"Which apps should be on the first page?"
Then:
"Should I use folders?"
Then:
"What is the perfect folder structure?"
But the purpose of a home screen is not to win an organization competition.
Its purpose is simply:
Help you access the things you need efficiently.
If your current arrangement works, it is already doing its job.
4. Social media
Social media can create similar questions:
"How many people should I follow?"
There is no universal perfect number.
A researcher, a student, a creator, a journalist, and someone who only uses social media for friends can have completely different needs.
The better question is:
"Does following this account provide value to me?"
That is much more useful than trying to discover a magic number.
The hidden pattern
Eventually, I realized that these weren't really separate problems.
They had something in common.
The pattern looked like this:
Question
↓
Search for the best rule
↓
Find exceptions
↓
Search for a better rule
↓
Find more exceptions
↓
Compare alternatives
↓
Ask for reassurance
↓
Still feel uncertain
↓
Search again
This can become exhausting.
And the frustrating part is that more information doesn't necessarily create more peace.
Sometimes it creates more possibilities.
Why more information can make things worse
Suppose you have two possible solutions.
You research them.
You discover five more solutions.
Now you have seven.
You research those seven.
Now you discover that each has advantages and disadvantages.
Instead of becoming certain, you become less certain.
This is sometimes called analysis paralysis.
The problem isn't lack of information.
The problem is that you're trying to use information to eliminate uncertainty completely.
And for many decisions, that's impossible.
The uncomfortable truth: every system has disadvantages
This is particularly important when designing systems.
There is rarely a system that has only advantages.
For example:
Simple filenames
Advantages:
Easy to read
Easy to type
Easy to understand
Disadvantages:
Possible duplicates
Less useful for automated systems
UID-based filenames
Advantages:
Easy to uniquely identify files
Useful for databases and automation
Disadvantages:
Less human-readable
Can make manual browsing harder
Neither system is universally superior.
They optimize for different goals.
That's the key.
A system should be judged according to what it is designed to accomplish.
The question I should have asked
Instead of asking:
"What is the perfect system?"
I should ask:
"What problem am I trying to solve?"
Then:
"What is the simplest system that solves that problem?"
This changes everything.
For example:
Problem:
"I want to find my books easily."
Possible solution:
Author - Title - Year.pdf
Done.
You don't necessarily need to design a globally scalable library identification system.
Personal system vs professional system
Another important distinction is scale.
A naming convention that works beautifully for 500 personal books may not be appropriate for millions of documents.
A university repository may need:
databases
persistent identifiers
metadata
access control
search indexes
backups
APIs
automated workflows
But that doesn't mean your personal collection needs all of those things.
Likewise, a company may need sophisticated infrastructure that would be completely unnecessary for an individual.
Don't solve a million-file problem when you have a five-hundred-file problem.
Build for the problem you actually have.
"Perfect" is often the wrong optimization target
When we say "perfect," what do we actually mean?
Perfect for:
simplicity?
speed?
scalability?
readability?
automation?
security?
storage?
searching?
aesthetics?
These goals can conflict.
For example:
Maximum simplicity and maximum scalability aren't always the same thing.
Maximum flexibility and maximum consistency aren't always the same thing.
Human readability and machine optimization aren't always the same thing.
So when someone asks:
"What's the perfect system?"
The natural response should be:
"Perfect for what?"
Good enough is not failure
There is sometimes a misconception that choosing a "good enough" solution means we are being careless.
It doesn't.
A good-enough solution can be:
intentional
consistent
practical
maintainable
appropriate for the current situation
Suppose you choose a filename format and use it consistently.
That's already valuable.
You don't need to prove that your format is the best filename format ever created.
You only need to know:
"Does this work for my purpose?"
If yes, move on.
You can always change a system later
Another important realization is that many decisions are reversible.
If you organize your apps today and dislike the arrangement next month, you can rearrange them.
If you choose a filename convention and later need something more sophisticated, you can write a script to rename the files.
If you create a folder structure and discover a better one, you can modify it.
Not every decision is permanent.
Therefore, spending hours trying to guarantee that your first decision is perfect often doesn't make sense.
The cost of optimization
Optimization itself has a cost.
Suppose you spend three hours designing the perfect organization system.
What could you have done during those three hours?
You could have:
studied
programmed
worked on a project
read a research paper
exercised
rested
spent time with family
learned something useful
So the real question becomes:
"Is improving this system worth the time I'm spending on it?"
This is a much better way to think about optimization.
The opportunity-cost test
Before spending a lot of time optimizing something, ask:
1. How important is this decision?
Is it going to significantly affect my life?
2. Is the decision reversible?
Can I change it later?
3. Will another hour of research substantially improve the result?
Or will it only give me more alternatives?
4. What am I giving up to optimize this?
This last question is particularly important.
Sometimes the biggest mistake isn't choosing the "wrong" option.
It's spending too much time choosing between options that barely matter.
A better decision-making framework
I find this simple framework much more useful:
Step 1 — Define the goal
What am I actually trying to accomplish?
Step 2 — Identify the constraints
What limitations do I have?
Examples:
time
storage
money
technical complexity
available tools
Step 3 — Find a few reasonable options
You don't need to discover every possible option.
Usually, two or three good candidates are enough.
Step 4 — Choose one
Pick the option that satisfies the goal reasonably well.
Step 5 — Use it
This step is often forgotten.
A system isn't useful because it is beautifully designed.
It is useful because you actually use it.
Step 6 — Revisit only when necessary
If the system causes a real problem, improve it.
Otherwise, leave it alone.
A new rule
Ironically, after realizing that there is no universal perfect rule, I found one principle that is much more useful:
Use the simplest rule that works for your current goal.
Not the simplest rule imaginable.
Not the most sophisticated rule.
Not the rule used by the biggest organization in the world.
Just:
The simplest rule that works for you right now.
And what about uncertainty?
This is perhaps the hardest part.
Sometimes your mind says:
"But what if there is a better option?"
There probably is.
For almost everything, there is some alternative that might be better in some way.
That's okay.
You don't need to find it.
You can tell yourself:
"Maybe there is a better option. I don't need to know it right now."
Then continue.
This is an important shift.
The goal isn't to prove that your decision is perfect.
The goal is to become comfortable enough with uncertainty that you can make a reasonable decision and continue living your life.
The principle applies far beyond organization
This isn't just about filenames or apps.
It applies to:
productivity systems
study methods
programming tools
note-taking systems
folder structures
social media strategies
exercise routines
learning resources
career decisions
software architecture
daily routines
personal organization
In each case, ask:
What am I trying to achieve?
rather than:
What is the universally correct way to do this?
The most important lesson
Perhaps the biggest lesson is this:
There is no universal perfect rule.
There are only rules that are more or less appropriate for a particular:
person + purpose + environment + constraints + scale + time.
A system that is perfect for one person may be terrible for another.
A system that works today may need to change next year.
A system designed for 500 files may not work for 5 million files.
And that's completely normal.
Stop searching for perfection. Start building for purpose.
The world doesn't require us to make every small decision perfectly.
We have limited:
time
attention
energy
knowledge
resources
Therefore, our goal shouldn't be to optimize everything.
Instead:
Understand the problem.
Choose a reasonable solution.
Use it.
Learn from experience.
Improve it when improvement is actually necessary.
And then move on to something more important.
Because sometimes the best system isn't the one that is theoretically perfect.
It is the one that stops consuming your attention and lets you get on with your life.
One sentence worth remembering
There is no universal perfect rule—there is only a suitable rule for a particular purpose.
And when a decision is small, reversible, and low-risk:
Good enough is often better than perfect.
