I grew up in a house in Rawalpindi where a book was not a small thing.
We did not have money for many of them.
The ones we had got read twice, three times, passed to a cousin, read again.
A book was slow proof that something was worth keeping.
So when a story went around today about rare books being pulled apart to feed a scanner, then shredded once the pages were digitized, I did not read it as a tech story.
I read it as a story about what a fast system decides is disposable once it has extracted the part it wanted.
Here is the question underneath it, and it is not really about books.
How well is your company actually adopting AI right now.
Not the pilot. Not the demo that got applause in the all-hands.
The real rollout, the one touching real workflows.
Is it moving fast because it finally figured something out, or is it moving fast because nobody stopped to ask what gets thrown away to hit the date.
I have sat inside that rollout more times than I can count, on the vendor side, helping DACH enterprises wire agents into workflows that used to run on people who had been doing the job for a decade.
BMW. Fresenius. Public sector work through the roles I held before I went independent.
And the pattern is close to identical every time.
The fastest AI adoption I have seen was also the one that quietly stopped asking the people who understood the process why it worked the way it did.
Not maliciously. Nobody sits in a room and decides to discard institutional knowledge.
It stops being the thing anyone has time to protect once the deadline for the automation demo is three weeks out.
That is the shredder.
Not a machine, a calendar.
The scanning-then-shredding story works as a mirror because it is honest about the trade in a way most rollouts are not.
Somebody, somewhere, decided the physical book had already given up its value the moment the text existed as data.
The book was the vessel. The words were the product. Once you have the product, why keep the vessel.
Enterprises treat the person who understands the process the same way, without ever saying it out loud.
Once the workflow is mapped, once the automation ships, the person who carried that knowledge for years starts looking like the book after the scan.
The information got extracted. The keeper feels disposable.
I do not think that is inevitable. I think it is a choice made by speed, and speed rarely announces itself as a choice.
Here is where I will be direct instead of diplomatic about it, because a post that does not commit to an opinion is not worth your five minutes.
A rollout that cannot tell you what it kept, only what it automated, is not actually finished.
It shipped the easy half.
The harder half is deciding, on purpose, what stays human, what stays slow, what stays owned by the person who has done it long enough to know why the exceptions exist.
That decision does not show up in a demo.
It shows up eighteen months later, when the automation hits an edge case nobody documented because the person who would have caught it left, and nobody thought to ask why the shredder ran that fast in the first place.
I still keep books I will probably never read twice.
Not because I am sentimental about paper.
Because I know what it costs to grow up without enough of them, and I refuse to build a habit, personal or professional, that treats the thing that took years to build as worth less than the five minutes it takes to extract from it.
That is the standard I hold client work to now.
Not "can we automate this." Almost everything can be automated.
The real question is what you are willing to protect on the way there, and whether you decided that on purpose or let the calendar decide for you.
If your company shipped an AI rollout this year, somebody made that decision, whether or not they noticed they were making it. What did your company throw away to move faster on AI, and did anyone notice before it was gone?
I work through this in public, the wins and the freezes both, mostly on LinkedIn and YouTube. If the real version of building in the open is useful to you, that is where it lives. Find me on X, GitHub, and the work at next8n.com.