Episode #1: The Problem Behind the Problem
Introduction
Every day we encounter problems.
Some are small.
Some are large.
Some are personal.
Some are professional.
We struggle with deadlines, productivity, communication, career decisions, business challenges, learning obstacles, family concerns, financial choices, and countless other issues.
Traditionally, we try to solve these problems alone.
We think.
We analyze.
We worry.
We discuss them with a few people.
Then we make a decision.
But something remarkable is changing.
For the first time in human history, we can think alongside an intelligence that can instantly examine a problem from dozens of perspectives.
This is not about replacing human thinking.
It is about expanding human thinking.
Welcome to Co-Thinking with AI.
And it begins with a simple realization:
The first version of a problem is rarely the real problem.
The Trap of Surface Problems
When a problem appears, we usually focus on the symptom.
AI helps us explore the cause.
Consider a manager who says:
"My team is not productive."
That sounds like the problem.
But is it?
A co-thinking session with AI might uncover several possibilities:
Unclear goals
Too many meetings
Poor communication
Lack of motivation
Skill gaps
Process inefficiencies
Resource shortages
Leadership challenges
The original problem was productivity.
The real problem might be clarity.
Or communication.
Or leadership.
Or something else entirely.
Without understanding the true problem, every solution becomes a guess.
Example 1: The Student
The Problem
A student says:
"I am not performing well in my exams."
Most students stop there.
A co-thinker does not.
Human + AI Exploration
Ask AI:
What could cause poor exam performance?
What assumptions am I making?
What evidence would distinguish different causes?
AI might identify:
Weak understanding
Poor study methods
Lack of revision
Test anxiety
Time management issues
Sleep deprivation
Information overload
Now the student investigates.
The result?
The real issue is discovered:
The student understands the material but practices too few problems.
The problem was not knowledge.
The problem was application.
A completely different solution emerges.
Example 2: The Business Owner
The Problem
A business owner says:
"Sales are declining."
That sounds straightforward.
But AI can help expand the thinking.
Co-Thinking Questions
Ask AI:
What are all possible reasons sales could decline?
Categorize them into internal and external causes.
What data should I examine first?
The exploration reveals possibilities:
Internal:
Pricing
Product quality
Customer service
Marketing effectiveness
External:
Competition
Economic changes
Market shifts
Customer behavior changes
After analysis, the owner discovers:
Traffic is healthy.
Interest is healthy.
Conversions are poor.
The issue is not sales.
The issue is trust.
Customers are abandoning purchases because the website appears outdated.
The solution is not more advertising.
The solution is improving credibility.
Example 3: Career Growth
The Problem
An employee says:
"I am not getting promoted."
Many people immediately blame management.
AI encourages broader thinking.
Ask:
What factors influence promotion decisions?
What evidence exists for each factor?
What perspectives might my manager have?
Possible findings:
Visibility problem
Skill gap
Leadership gap
Communication issue
Organizational constraints
Timing issues
The employee discovers that strong work is largely invisible outside their immediate team.
The challenge is not performance.
It is visibility.
Again, a different problem.
Again, a different solution.
The Five Co-Thinking Questions
Whenever you face a problem, ask AI these five questions:
1. What problem am I actually trying to solve?
This separates symptoms from causes.
2. What assumptions am I making?
Many problems survive because assumptions remain hidden.
3. What perspectives am I missing?
Customers, managers, competitors, experts, beginners, and stakeholders often see different realities.
4. What would an expert investigate first?
Experts rarely start where beginners start.
5. What if the opposite were true?
This question often exposes blind spots.
The Co-Thinking Mindset
Most people use AI like a search engine.
They ask:
"Give me the answer."
Co-thinkers ask:
"Help me understand the problem."
That shift changes everything.
Answers solve today's problem.
Understanding solves tomorrow's problem too.
The goal is not merely to solve one issue.
The goal is to become a better thinker.
A Simple Exercise
Take one real problem from your life.
Then ask AI:
"I have this problem: [describe it].
Help me:
Define the problem.
Identify possible root causes.
List assumptions I may be making.
Suggest perspectives I have not considered.
Recommend what information I need before deciding on a solution."
Do not ask for solutions immediately.
Spend time understanding.
You may discover that the problem you started with is not the problem you need to solve.
Key Insight
Most failed solutions are not failures of execution.
They are failures of understanding.
The better you understand a problem, the easier it becomes to solve.
AI's greatest value may not be generating answers.
It may be helping humans ask better questions.
And better questions lead to better thinking.
Better thinking leads to better decisions.
Better decisions lead to better outcomes.
That is the power of co-thinking.
Coming Next
Co-Thinking with AI | 1001 Problems – Episode #2
The Problem Definition Machine: Turning Confusion into Clarity
Learn how to transform vague concerns, frustrations, and uncertainties into clearly defined problems that can actually be solved.
AIYING – Think Better. Ask Better. Accomplish More.
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