Commoditized vs. Customized: Which Side of the AI Divide Are You On?

These founders aren’t failing.
They’re just building on the wrong side of the AI divide.

This divide is simple.
If your work can be done by a clean prompt, it is becoming cheap.
If your work needs context, judgment, or care, it is still valuable.

Your skills are your safety.
Your differentiation is your leverage.

Let us make this practical.

AI is great at repeatable tasks.
Think summaries, basic copy, simple analysis.

These tasks are now commodities.
A commodity is something many people can get easily and cheaply.

What AI struggles with is context.
Context means understanding the full situation, not just the words.

Context includes
• History
• Culture
• Emotion
• Tradeoffs
• What is not being said

AI can sound confident.
It can even sound kind.
But it does not live the problem.

That gap is where you win.

Ask yourself one question.

If my laptop disappeared today, could a client replace me with a prompt?

Be honest.

If the answer is yes, you are on the risky side.
If the answer is no, you are closer to the safe side.

Here is a clearer way to see it.

Draw two columns on paper.

Column one
Tasks a generic AI can do with generic data.

Column two
Tasks that need my judgment, taste, or understanding of this user.

Most founders discover something painful.
Their product leans too much on column one.

That is not a failure.
It is a signal.

Customers do not want more output.
They want meaning.

Meaning is when someone helps them decide what matters.

That is why personalization works.
People expect it now.

As of November 03, 2025, McKinsey reported that 71 percent of consumers expect personalized interactions and 76 percent feel frustrated without them.

Customization does not mean complex tech.
It often means small human choices.

Using their context.
Remembering their goal.
Explaining why, not just what.

Do not rebuild everything.
Run small moves.

Step One. Audit One Workflow
Time needed: 30 minutes.
KPI: One clear list with ten tasks.

Mark which steps are AI friendly.
Mark which steps need human judgment.

Your goal is not to remove humans.
Your goal is to move humans to the moments that matter.

Step Two. Add One Layer of Context
Time needed: One week experiment.
KPI: Engagement or satisfaction score.

Example.
If you send reports, add a short section at the top.

What this means for you.
What I would do next if this were my business.

That paragraph is hard to automate well.
Clients notice.

Step Three. Use AI as a Force Multiplier
Time needed: One setup session.
KPI: Time saved per task.

Let AI do the first draft.
You do the final judgment.

This keeps speed high and quality human.

If you are an immigrant founder, you have lived context within the immigrant experience.

You understand confusion.
You understand risk.
You understand stakes.

Turn that into a product feature.

Example.
If you serve international students, add a mentor note.
Two lines.
Written by a human.
Grounded in real experience.

Track usage.
If people return for that, you found something AI cannot replace.

Domain expertise will always hold its value.

The world does not need more content.
It needs filters.

A strong position today is interpreter.

You do not just generate output.
You help users decide.

If you offer analytics, add a human summary.
If you offer research, add a recommendation.

Test it.

Accounts with human context usually trust more.
Trust drives growth.

Do not race AI on price.
You will lose.

Sell what AI cannot.

Try a simple two tier test.

Basic
AI generated output.

Premium
AI output plus human insight and a short call.

Offer the premium free to a few users.
Then ask if they would pay next time.

Research from Medallia on February 15, 2024 showed that 61 percent of consumers are willing to pay more for personalized experiences.

People now pay for feeling understood.

Commodities destroy margins.
Customization protects them.

Track your time.

If a custom add on takes 30 minutes and clients value it at 200 dollars, that is strong. If it takes five hours, adjust.

Use AI in prep.
Save human energy for judgment.

Over automation breaks trust.
People feel it.

Keep a human fallback.
Be clear when AI is speaking.

Accuracy matters.
Never ship high risk answers without review.

Data privacy matters.
Know where data goes.

Skill atrophy is real.
Do not outsource your thinking.

AI should sharpen you, not replace you.

Average is.

Knowledge is becoming cheap.
Judgment is becoming rare.

Your job is to move up the stack.

From output to insight.
From answers to decisions.
From generic to personal.

That is the safe side of the divide.

Here are a few of my other courses that you may find useful:

Antifragility goes beyond resilience. It is not just about surviving stress or chaos.

It is about using it as fuel. When pressure shows up, you adapt, learn, and come back stronger than before.

Instead of avoiding discomfort, antifragile people lean into it with curiosity.

They treat setbacks as information.

Each failure sharpens judgment. Each challenge builds capacity.

Over time, what once felt overwhelming becomes manageable, even empowering.

Life will always apply stress.

Antifragility teaches you to design your habits, work, and mindset so that stress makes you better, not bitter.

Time Offline

I’m currently off the grid for the next 10 days for a silent retreat.

The one I’m doing is called “vipassana” which means “inner vision.”

This is a structured period where you step away from speaking, notifications, news, and decision making.

No meetings. No content. No reactive thinking.

The goal is to reduce external noise so you can observe how your mind actually works when it is not constantly stimulated.

For me, this feels like a rare chance to reset and see what I’m attached to and what I do on autopilot.

Wishing everyone happy holidays and an early Happy New Year!

See you on the other side.