This is Technology Bytes, episode 168, for May 24th, 2026.
Technology Bytes is a microcast, where I share brief bites on interesting technology.
Enjoy, and here we go. This week I’m back talking about AI again, and in that I’m talking about artificial intelligence, not Apple intelligence.
And, you know, my relationship, as you may know if you listen to any of these podcasts, is with artificial intelligence is basically non-existent.
Now, I realize that’s not entirely true, because even though I do my searches on the web, and I look for things through search engines, I know that those engines are using artificial intelligence to give me answers.
Oftentimes, I will scroll past those answers, because I’m not interested in artificial intelligence, and I want to get to what I look at and deem by the search results to be what would get me further down the road the fastest.
But there are times where I can choose that first answer that artificial intelligence has given me, because I know that it’s a very simplistic question, and it can give me a good answer.
But I don’t have any artificial apps on my, artificial intelligence apps on my phone.
I don’t have any accounts that I pay for.
I don’t use it ever.
And so it’s just not part of my life or who I am or what I do, which is kind of weird, because I’m a tech person.
I listen to people talk about it all the time.
I just don’t really get it, because it doesn’t feel like it would do anything for me.
Then something happened this week that made me see some of the usefulness for artificial intelligence.
And something I’ve said in the past, I believe, in other microcasts on this channel is, maybe I just don’t get it.
I just don’t see what it can do for me.
I just don’t understand what it would offer me to make my life better.
And then this week, I found something to make that happen.
Now, it’s social, it’s centered around my work.
And so that is kind of where I thought it might happen first.
And also, my boss and others at work have been challenging me to use AI to do certain things.
And even then, I don’t quite get it.
I don’t really want to use it.
Anyway, I’ve been over that before.
And so let me explain a little bit about what happened this week at work.
One of my responsibilities at work is our inventory warehouse.
And we don’t hold a lot of inventory.
We do a lot of just-in-time production manufacturing processes.
But we do hold some.
And it’s always been a bit of a mess.
We have a really good warehouse manager who has made it much better.
But even then, my numbers are off.
Things don’t seem to work right.
All of a sudden, this number doesn’t match this number.
And it can be very frustrating.
And so I was watching these numbers and realized that I had used a given amount of inventory from these product numbers.
And yet, my count was off by eight.
And it made no sense because five days earlier, I was dead on.
The numbers were exactly right.
And so I’m trying to figure out why they’re off by eight.
I should have only used seven of these items, about 16 of them.
And yet, I had used 15.
And it made absolutely no sense to me.
And so I went to my development team because all our tools are developed in-house.
And I said, I wonder if you guys can help me with finding out why this product category always gets off every time we reduce it by using it up to fill orders.
And they said, well, let’s see what Claude can do for us.
And I’m a little bit of a skeptic.
But they went in and asked Claude to look at this number and see why it was off by eight.
And so it went into the system because it has access to all of our data.
And it says, OK, you’re right.
We’ve only used seven.
So it should not be off by eight as if we had used 15.
And so then it says, well, maybe we had orders that used two.
And we only recorded it as having used one.
And then it came back and said, nope, that’s not true either.
Every line that we’ve used for that product is for one and for one only.
So then it says, well, maybe let me look at something else.
And so it went through another thing trying to figure out.
And then it says, nope, that’s not it either.
And then it said, well, maybe this number, which is the number we started with, was entered incorrectly.
And we started off by seven and used eight.
And now we’re off by 15.
Well, that’s the only conclusion it could come to.
I knew that wasn’t true.
I knew that my warehouse inventory manager had put in the correct number.
And so Claude could not figure it out.
But I was very fascinated in the conversation that it really had with itself until it came back and said, I can’t figure it out.
And smart people say, I don’t know sometimes.
Then I thought, well, I wonder what else it can do for me.
And so I went back with another question about another item.
And so they pushed it through Claude.
And then they’re saying, we probably should give Joel access to this so he can do this stuff by himself.
And I’m like, yeah, I’m willing now that I have a little glimpse.
Because now it has data that’s useful to me that I don’t have to go in and write my own queries and look at all the data myself and try to figure things out.
I can have an assistant help me with that.
And so we did that in about two minutes or something like that.
It came back with great answer.
It was exactly what we wanted.
And then later in the week, I said, OK, I’ve got another Claude question for you.
In this particular instance, I’ve got thousands of T-shirts that I have to send through a given process in my world.
And we don’t have the data available to the QC person that we generally would because of the way these T-shirts get to us.
And so I went to the dev team and I said, look, for every one of these T-shirt part numbers, I need the line ID number for every open order with a barcode.
And so they gave Claude the three part numbers that I needed.
And they said, I need them for only orders that are open.
And I need the data for the line ID associated with each one of these part numbers.
And I also need a barcode that the person can scan with that.
So it came back and gave it to us.
It was very quickly done.
And it was, yeah, took very little time.
And then it was formatted in such a way that would print on our labels, which is what we generally use.
And they’re like, do you need labels?
Because this is like 400 labels.
And I’m like, nope, I don’t need labels.
I just need a page full of barcodes.
And so they went back and told Claude, hey, format this on an eight and a half by 11 piece of paper and a PDF and put the barcodes as many as you can in a readable format on a page.
And so, you know, it did it.
And then they sent me the PDF and, you know, five minutes later, I have all of the barcodes on, I think it ended up being 48 double-sided pages.
I don’t remember how many barcodes per page, a lot of barcodes, but it did it in such a quick manner.
And it’s going to make all of the work that my QC people have to do for this particular project so much easier.
So useful.
And I thought, okay, now I’m getting to understand.
And again, they said, we probably need to give you access so you can do this stuff by yourself.
Now I’m like, okay, I will use AI.
So a little bit of a change.
I’m still not sure how it applies to me in my personal life, but I can definitely see the advantage for using it once we’ve given it all our work data to get answers back very quickly without having to know SQL, without having to write queries, all things that I know how to do, but it’s complicated.
And I would take a lot more time to write those than I saw Claude do in a very short period of time.
So I’m really looking forward to the opportunity to use it.
I don’t know if that will then spread to my personal life, but we shall see.
And if it does, I will report back on this very microcast.
That is all I have for today.
If you have comments, suggestions, or questions, you can send them to technologybytesatmaragfamily.com.
As always, I want to thank you for listening to the Technology Bytes microcast, and I look forward to the next time we are together taking another bite of technology.
