Routine. Hiding in Plain Sight.
You walk into a grocery store you’ve visited dozens of times.
You probably don’t stop at the entrance to figure out what to do next.
✅ You know where the trolleys are.
✅ How the aisles work.
✅ Where checkout tends to be.
✅ What to do when it’s your turn.
It’s all very familiar and routine. Maybe you barely notice any of it.
You simply do your shopping and exit.
➖
Something similar happens on your phone.
- You open an app
- Tap
- Swipe
- Scroll
- Repeat
- Move somewhere else
You don’t inspect the interface each time.
You already know what to do.
➖
The store is still there, along with all the systems inside it: the floorplan, the aisles, how products are grouped and positioned, how the deli, bakery, seafood, meat, and ready-to-eat areas operate, and how checkout and payment work.
Systems within systems, within systems.
You are moving through all of them as you shop. You just may not need to keep noticing them.
The app on your phone is still there, but it too isn’t operating alone. The phone itself is a system, as is the network that connects it. The app is another system nested inside those systems, with systems of its own — menus and navigation, defaults, recommendations, notifications, permissions, account rules, payments, and whatever logic determines what appears next or makes one action easier or more likely than another.
And you are participating in all of them at once, while your interior system is interpreting what it encounters and influencing what you do next.
Familiarity simply means you no longer need to notice most of that machinery.
The rules, signals, pathways, and choices haven’t disappeared.
But much of the system has. At least from your attention.
And that may be one of routine’s stranger effects:
The more naturally we learn to participate in a system, the less of the system we may need to notice.
That creates an interesting relationship.
Routine can make things easier for you. Not just because participation becomes familiar, but because familiarity can allow much of the system to hide in plain sight.
But your increasingly familiar participation can also become useful to the systems around you.
Systems Benefit From Routine Too
This is where routine becomes especially interesting for MNKY Math.
Your interior system isn’t the only system that benefits from repetition.
Routine can make your participation more predictable to the systems around you.
→ Your arrival is more patterned than you think
→ You follow roughly this sequence
→ You react to this and not that
→ You click here and not there
Repeated often enough, participation begins producing something a system can work with.
And increasingly, like digital systems, physical systems can also observe, record, and trace far more of our movements and participation than we might assume. Cameras, sensors, and computer vision can measure paths through a store, dwell time, queues, where someone stops, what areas attract attention, and even some interactions with products. Some systems can even follow the same anonymous shopper across multiple camera views or estimate broad demographic characteristics.
The system doesn’t necessarily have to know who you are to learn something about how you behave in a physical space.
Because what once disappeared when you walked away can increasingly leave a trace.
And your trace, combined with many others, can help make “normal” legible as a baseline — making deviation easier to notice, accommodate, or correct and enabling highly practical and meaningful outcomes:
➡️ A manufacturing line repeats a sequence so deviation becomes visible.
➡️ A pharmacy employs dynamic precision workflows so something outside the expected flow is immediately noticeable.
➡️ Software presents familiar controls in familiar places so users don’t have to relearn the interface every time.
➡️ A store organizes products so returning customers learn where things belong.
➡️ Loyalty programs could just as easily be called repetition systems.
As traces become richer and more connectable, what a system can optimize for can change too. A system that once saw only the outcome may eventually see the path. Once the path becomes legible the system may begin seeing more discrete human actions, where people pause, deviate, return, or respond differently. More trace doesn’t simply mean more data. It can change what the system is capable of noticing — and therefore what it is capable of shaping.
In short, repeated exposure teaches something about how you move through the system.
And as participation becomes more predictable to the system, the system and how you participate can become less demanding for you.
- You know where to go.
- What to click.
- What comes next.
- Where things belong.
Your routine begins to feel instinctive… but isn’t entirely inside you.
And it isn’t entirely outside you.
Both sides are learning and using the pattern.
→ Your interior system can use routine to reduce what it has to figure out.
→ The surrounding system can use routine to establish what it expects. Or sometimes, what it wants.
And those expectations can create new opportunities.
In Why Some Things Pull You In, we explored how systems can learn what tends to get through your interior filtering and tilt conditions accordingly.
When successful tilts repeat, they can reveal doorways the system learns it can use again.
A notification gets through.
You open the app.
It happens again.
The timing becomes familiar.
The icon becomes familiar.
The gesture becomes familiar.
The sequence becomes familiar.
What began as a doorway can become part of the routine. And once it does, the routine itself can reveal new doorways.
Because once a system has learned what usually happens, it can notice when something else happens instead… and act.
And with it, what correction may mean.
When Deviation Becomes Something to Correct — or Direct
A baseline doesn’t only help a system see what is happening. It can also give the system something to steer toward.
In manufacturing or in a workflow, that can be exactly what we want: A process moves outside its expected range, the deviation becomes visible, and something gets corrected.
Something went wrong.
Correction restores the expected pattern.
But what happens when the baseline isn’t describing a production process?
What happens when the baseline describes your participation?
You usually open an app in the morning. Today you don’t.
You usually complete the streak. Today you’re about to miss it.
You usually respond to an offer. This time you hesitate.
Nothing necessarily went wrong. You simply deviated from what you usually do.
And now correction becomes less straightforward. The system may be trying to restore participation toward an established pattern. Or it may be using what it has learned about that pattern to direct you toward something it prefers.
The mechanics can look remarkably similar.
You respond.
The response works.
The signal appears again.
Repeated often enough, these interactions can begin strengthening the familiarity already present inside the routine.
And this is where routine and habit begin touching one another.
Routine describes the recurring structure.
Habit describes what can happen when familiar cues inside that structure increasingly call up a learned response with less conscious deliberation.
➖
Routine and habit can coexist.
One can help create conditions for the other.
They are not the same thing. But both can make participation ask less of your conscious attention.
➡️ Routine can do it through familiar structure.
➡️ Habit can do it through familiar response.
And that can make both useful to a system trying to maintain, restore, or influence your participation.
Which brings us back to correction.
- Sometimes a deviation really does represent an error worth correcting.
- Sometimes the deviation is simply you doing something different.
- Sometimes your deviation becomes the signal that prompts the system to steer you…
- back toward the baseline…
- or toward a new baseline it has inferred from what you did instead.
The mechanics may be similar.
What changes is the baseline being protected — and who benefits from restoring or directing it.
The steering to hang with
In You Are a System, we began with a simple premise: you are not a neutral participant to the systems around you. They encounter you — an interior system already interpreting, learning, remembering, and responding.
Then in The Feeling Before the Thought, we explored how some of that interpretation can happen before you have consciously explained it to yourself.
In Why Some Things Pull You In, the lens turned outward. Systems can learn what tends to get through and tilt conditions accordingly.
And in When Repeating Becomes Routine, repetition gave both familiarity and expectation somewhere to accumulate.
Which brings us here.
Because once your participation becomes patterned enough for a surrounding system to recognize, routine is no longer only helping you navigate the system.
It may also be helping the system navigate you.
The system can begin to recognize what usually happens.
What you tend to do next.
And when you do something different.
Your deviation can become information.
Information can become a signal.
And a signal can become an opportunity to respond, correct…
None of this requires the system to control you.
Sometimes it only needs a baseline.
A doorway.
And enough repetition to learn when something has changed.
So perhaps the thing to hang with isn’t simply whether routine makes life easier.
Maybe it’s this:
When your routine becomes legible to a system, whose routine is it becoming?
And when the system responds because you deviated…
who or what exactly is being corrected?
Continue the publishing sequence
When your routine becomes legible to a system, the system can begin shaping what happens around it. And sometimes that shaping doesn't feel like pressure at all. It may simply change what seems worth doing, delaying, avoiding, or choosing. That's where pressure becomes more interesting than it first appears.
Sources:
- NVIDIA. Multi-Camera Tracking. NVIDIA AI Workflows.
- Sensormatic Solutions. Computer Vision.
- RetailNext. Aurora | Product Brief.
- Pantano, E., et al. (2019). “A business application of RTLS technology in Intelligent Retail Environment: Defining the shopper’s preferred path and its segmentation.” Journal of Retailing and Consumer Services, 47, 184–194.