The Valley After AI

There is a wide valley where many animals live.

For a long time, life in the valley worked the same way for everyone.

Food required effort.
Movement required judgment.
Mistakes cost energy.

When an animal struggled and succeeded, something important happened:
the animal learned what mattered.

That learning felt different to different animals.

 

Before AI: Shared friction

A mountain goat climbed steep rock faces every day.

The climb was exhausting.
But the goat learned:

• where the stone crumbled

• where the ledge held

• how far its body could go

The effort itself taught the goat how to live.

Nearby, a house cat hunted small prey.

The cat preferred ease.
It rested often.
It chose comfort when possible.

But prey still ran.
So even the cat learned timing, patience, and restraint.

The wolf hunted in bursts.
Sometimes it failed.
Sometimes it ate.

Failure sharpened its instincts.
Success confirmed them.

Different animals.
Different preferences.
Same rule:

What you do changes what happens.

 

AI enters the valley

Then AI arrives.

AI does not hunt.
AI does not climb.
AI predicts.

AI watches patterns in the valley:

• when animals get hungry

• when they get tired

• where they usually fail

And AI begins acting early.

Food appears closer.
Paths smooth themselves.
Delays shrink.
Outcomes arrive before effort finishes.

The valley becomes easier.

But not in the same way for everyone.

 

What happens to the cat

The cat notices immediately.

Food now appears without stalking.
Warm places appear without searching.
Surprises are removed.

The cat’s system relaxes.

It still moves.
It still chooses.
But less depends on those choices.

When the cat rests, nothing bad happens.
When the cat avoids effort, nothing is lost.

The cat learns a new rule:

Ease is safe.
Smoothness means things are working.

The cat becomes calmer.
More regulated.
More stable.

 

What happens to the goat

The mountain goat also notices AI.

The path up the rock face is smoothed.
Loose stones are stabilized.
Shortcuts appear.

The climb costs less.

At first, the goat enjoys the relief.

Then something subtle happens.

The goat reaches the top…
but its body learned less.

No missteps.
No recalibration.
No sharp feedback.

The goat feels an odd flatness.

It climbs again.
Still flat.

The effort no longer teaches.

So the goat seeks steeper cliffs.
Longer climbs.
Riskier edges.

Not because it wants pain,
but because without resistance, nothing updates.

 

The wolf's problem

The wolf hunts.

AI predicts prey movement.
Prey is guided into easier capture.

The wolf eats more reliably.

But over time:

• timing dulls

• instincts soften

• judgment weakens

The wolf succeeds,
until the prey behaves unexpectedly.

Then the wolf hesitates.

Its skill looked intact.
But it did not transfer.

 

The first social misread

The cat watches the goat climb harder cliffs.

The cat thinks:

“Why make this harder than it needs to be?”

The goat watches the cat rest.

The goat thinks:

“Why avoid the part where you learn something?”

They are not judging.

They are experiencing reward from different places.

 

The zoo animal

In one corner of the valley, a zoo animal lives.

Food is guaranteed.
Space is safe.
Nothing pushes back.

The animal is healthy.
Fed.
Protected.

And inactive.

It does not struggle.
It does not explore.
It does not update.

Nothing is wrong.

Nothing is happening.

 

The widening gap

As AI improves, the valley keeps smoothing.

The cat feels better and better.
The zoo animal is perfectly regulated.
The wolf survives... until novelty appears.
The goat feels increasingly starved of meaning.

Now the animals don’t just behave differently.
They interpret life differently.

To the cat:

• difficulty looks unnecessary

• strain looks outdated

To the goat:

• ease looks empty

• comfort looks suspicious

They still share the valley.

But they no longer agree on what makes life work.

 

Society in the valley

Over time, the valley reorganizes.

Paths are built for comfort.
Shelters prioritize ease.
Training removes strain.

Most animals thrive.

A few grow restless.
They seek mountains.
Deserts.
Unsmoothed ground.

They cluster quietly.

Not because they hate the valley,
but because their systems no longer learn there.

 

What AI actually did

AI did not change the animals.

AI changed what the environment rewarded.

It made friction optional.

And once friction stopped being shared,
the valley split...
not by belief,
not by values,
but by where reward came from.

 

The end state

No collapse.
No fight.

Just animals living in the same valley
with different answers to the question:

“When does effort matter?”

And once that answer diverges,
culture doesn’t argue.

It separates.

Quietly.