I just got off a call where someone told me:
- their clients don’t understand agile
- don’t know how to scale their code
- struggle to even debug properly
A few years ago, this would sound absurd.
Today, it’s becoming normal.
We spent years worrying about technical debt.
Now we’re entering a world of cognitive debt.
AI is making it incredibly easy to ship code, connect systems, and automate workflows.
But something subtle is happening:
- teams understand less and less of what they’re actually running
Not because they’re not smart —
but because the system grows faster than their ability to reason about it.
What used to be:
· messy architecture
· inefficient infrastructure
Is becoming:
· unclear logic
· hidden dependencies
· bloated (and expensive) systems nobody fully understands
Lately, I’ve been dealing a lot with cluttered and over engineered systems.
Some of it created by humans.
Some of it accelerated by AI.
But in both cases, the result is the same:
- too many layers
- too much noise
- not enough clarity
And that’s where things start breaking.
Because you can optimize technical debt.
But cognitive debt?
That’s when:
· decisions slow down
· debugging becomes guesswork
· scaling becomes fragile
The real work now is not just building faster –
it’s removing the clutter and restoring simplicity.
- Most of what matters is below the surface.
If you’re seeing this too – curious how you’re dealing with it.