When Micro Becomes Macro (agents, errors and bugs)

When Micro Becomes Macro.

It started with pink fuzzy bunny slippers.
As these things often do in Wonderland.

A reader had securely fastened his before entering this week’s AI rabbit hole and left me with a rather uncomfortable thought.

We are watching AI expand. Into browsers. Into websites. Into our homes. Into devices. Into agents that don’t just answer questions, but go somewhere, find something, decide something and bring it back.

And eventually, act on it.
We keep asking how far this can scale.
There is another question hiding underneath:
What happens to the errors when it does?

A Very Small Mistake

Imagine an AI agent visits a website for you.
It reads a page. Mostly correctly. But it misunderstands one small thing.
A nuance. A condition. A number. A relationship between two ideas.
A tiny error.

Micro.

It brings that information back. Another agent uses it. A system makes a decision based on it. That decision produces new information. Perhaps another AI encounters that information later and treats it as evidence.

And suddenly our tiny misunderstanding has acquired friends.

We Used to Call That a Mistake

When one human misunderstands something, the error has fairly short legs.
I misunderstand you. You correct me. Or perhaps you don’t. I wander around being wrong for a while.

Humans are remarkably accomplished at this.
Yet our mistakes are constrained by something useful:
us.

Our reach. Our speed. Our memory. Our ability to tell twelve people something before getting distracted by lunch.

Machines have rather fewer lunch breaks.
An agent can pass information to another agent almost instantly. Systems can operate continuously.
Networks can repeat, transform and distribute information at a scale no individual human could manage.
Which means the interesting unit may no longer be the size of the original error.

It may be its ability to travel.

Micro × Micro × Micro

We tend to imagine scale as enlargement.

Something good works? Make more of it.
Something efficient works? Automate it.
Something intelligent works? Connect it.

But scale does not only enlarge capability.
It can enlarge assumptions. Bias. Misclassification. Missing context. Outdated information.

Confident little misunderstandings wearing very respectable shoes.

One error may be trivial.
A million perfectly repeated versions of it are not.
And an error that changes slightly each time it passes through another system may be stranger still.

The micro hasn’t disappeared.
It has become infrastructure.

The New Macro

This may become particularly interesting when AI agents begin navigating the web on our behalf.

Until now, much of the internet has been designed around humans finding information.

Then search engines joined us. So we learned SEO.
Then answer engines appeared. AEO. GEO.
And now perhaps agents arrive at the gate.

They may not admire the colours. They may not appreciate our beautifully positioned button.

They may simply want to know:
What is this?
Can I access it?
Can I trust it?
Is it relevant?
What should I take back?

And if the agent gets one of those answers slightly wrong… who notices?

The human who never visited the page? The website owner who never met the agent? The next agent downstream? The system making the decision?

Or nobody?

That is where micro starts looking suspiciously macro.

Local Doesn’t Make It Smaller

There is another curious movement happening at the same time.
After years of pushing computing outward into enormous clouds, some AI is moving closer again.
Onto our computers. Our phones. Our devices. Our homes.

Small networks of intelligence operating locally.

I rather like that idea.

Yet distributed intelligence creates an interesting illusion.
When intelligence becomes smaller and more local, it can feel less consequential.

One little model. One little agent. One little decision. One little error.
Except there may be millions of them.

The macro no longer needs to sit inside one enormous machine.
It can emerge from countless tiny ones.

Who Has the Key?

And now we are back at the fence.
Of course we are.

🐑

If agents can cross boundaries, retrieve information and act for us, someone has to decide which gates they may open.

Who gives permission?
Who sets the boundaries?
Who decides what counts as trustworthy?
Who checks what comes back?

And perhaps most importantly:
who notices when something tiny went wrong three gates ago?

We may become very good at controlling what AI is allowed to do.
We may need to become equally good at seeing how it arrived at what it thinks it knows.
Because control without traceability is a rather impressive lock on a gate whose fence may already have moved.

Pink Slippers Recommended

None of this means the agents are coming to destroy Wonderland.

Quite the opposite.

There is enormous possibility here: agents that navigate complexity for us, local AI that gives us more control, systems that cooperate, knowledge moving faster, tasks becoming easier.

Perhaps even fewer subscriptions.
One can dream.

😏

... expansion changes the nature of small things.

A tiny improvement can multiply.
So can a tiny mistake.

And that is one of the habits we will need in an increasingly agentic world:
Not merely asking, How intelligent is this?
But occasionally looking down and asking, What tiny thing are we standing on?

Because once intelligence spreads far enough…
the micro may not sit inside the macro anymore.

The micro may become the macro.

Pink fuzzy bunny slippers securely fastened.
There appears to be another tunnel ahead.
🐇 Fleeky

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