The Answer Is Still Cookies
A few days ago, I saw a Cookie Monster quote that made me stop:
“Me don’t know da question, but me know da answer is cookies.”
It is funny. It is childish.
And it is exactly how companies behave when they insist their problems are special.
Every company believes it is fundamentally different.
Different industry. Different technology. Different customers. Different speed.
Therefore, their problems must be new, unprecedented, uniquely complex.
Except they are not.
Strip away the buzzwords, and the underlying patterns look painfully familiar.
The Illusion of Uniqueness
Modern companies wrap their issues in modern language:
- “We’re moving too fast for standard processes.”
- “Our AI stack changes everything.”
- “Our customers behave unlike anyone else.”
- “Our growth model is unique.”
- “Our bottlenecks are special and can’t be compared.”
This might feel true from the inside, but it is almost always wrong.
The names are new.
The environment is new.
The velocity is new.
But the problems?
They are the same ones that have existed for decades, sometimes centuries.
Poor prioritization.
Misaligned incentives.
Broken workflows.
Lack of measurement.
Inconsistent execution.
Missing feedback loops.
Overconfidence instead of structure.
Nothing about these challenges is unique to cloud, AI, DevOps, or MLOps.
If you replace the vocabulary, you could be reading a manufacturing case study from the 1950s.
What Industrial Engineering Taught Me
This is exactly why I loved studying industrial engineering. It forces you to stop looking at the surface and start looking at the system underneath.
Industries change. Technologies evolve. Markets accelerate. The vocabulary shifts every decade.
But queues behave like queues. Bottlenecks behave like bottlenecks. Flow behaves like flow. Incentives behave like incentives. Feedback loops behave like feedback loops.
During my MBA, this pattern only became clearer. Different schools called it strategy, operations, organizational behavior, or finance, but it was always the same underlying mechanics. The case studies moved from factories to platforms to AI companies, yet the principles did not change.
Once you understand the physics of systems, the noise disappears. You see that software, AI, logistics, healthcare, cyber, and manufacturing all share the same backbone.
Different wrappers. Same core.
Modern Labels, Old Problems
Look at a few examples:
- AI governance is supply chain governance with new materials.
- Roadmap chaos is classic WIP overload.
- Cross-functional misalignment is incentive misalignment.
- Engineering delays are queueing and flow problems.
- GTM confusion is poor segmentation and cycle design.
- “Unique customer behavior” is often variance with no control system.
- “Unpredictable delivery” is missing feedback loops.
When leaders say “We need a new framework,” they usually do not.
They need to apply an old one correctly.
What This Means for Leaders and Product Managers
Leaders waste time searching for new answers because they believe their problem is fundamentally new.
It rarely is.
Most answers already exist:
- In operations research
- In system dynamics
- In classic management science
- In industrial engineering
- In Lean
- In queueing theory
- In incentive design
Your job is not to invent something new each time.
Your job is to figure out which existing principle explains the problem you are facing.
If you can do that, execution becomes faster.
Decisions become sharper.
And chaos turns into clarity.
The Cookie Monster Lesson
Cookie Monster had it right.
You do not always need to search for a new question.
You do not always need to reinvent the solution.
Sometimes the answer is old.
Sometimes the answer is simple.
Sometimes the answer is already known.
Sometimes, the answer is still cookies.