Walk into almost any office today and you’ll see the same thing.
People come in, sit down a few feet from each other, and stare at their screens. More than ever before, I think.
There are fewer collaboration meetings. When we do meet, we’re likely to do it over Teams, even when we’re in the same building. And there’s a growing push not to come in at all. Why would you? With AI agents writing code alongside you, you can produce a lot of work, very efficiently, from your kitchen table.
All of that is true. And all of it makes us a little more alone.
This is the fourth article in a series about the human side of the AI shift. If you missed the first one, start with The Computer Works for Us.
This didn’t start with AI
To be fair, AI didn’t start this. Technology has been nudging us apart for a long time.
Email made it easier not to walk down the hall. Chat made it easier not to call. Video calls made it easier not to come in. Every one of them made us more efficient and a little less connected to the people we work with.
AI is the next step down that road, and it’s a big one. Before, you still needed a person to answer your question. You just reached them through a screen. Now you often don’t need the person at all. You ask the machine.
I don’t think we stopped talking to each other. What happened is that we stopped needing each other to get an answer, and so, little by little, we stopped asking.
What we lose when we stop asking
When you ask a coworker a question, you get a lot more than the answer.
You get their tone of voice. You get the story behind it, the “here’s what happened last time we tried that.” You get a little of their judgment, and over time you start to absorb it. You walk away with a relationship that’s a bit stronger than it was before you asked. And every so often they ask you something back, and now you’re the one helping.
When you ask a machine, you get the answer, and that’s about it.
I’ve said it before in this series and I’ll probably keep saying it: the inefficiency is the good part. The extra five minutes of conversation, the detour, the lunch that runs long. That’s where a group of people turns into a team.
How I learned my craft
I learned to do my work three ways: from people, from books, and by trial and error.
People taught me good techniques, and a lot of them had picked those up from books or from their own mistakes. But trial and error built most of my bag of tricks. You learn a lot from the things that break on your watch.
The encouraging part is that I’m still learning the same way now.
I’m learning to lead AI by trial and error, mostly. Some books and articles. And the people around me, especially the ones who are figuring it out at the same time I am.
That goes way beyond software. AI is showing up in every line of work, whether it’s accounting, marketing, healthcare, education or the trades, and everybody is going to learn it the way people have always learned. From one another, from books, or by trying it and messing it up.
So the way we learn hasn’t changed. We’ve just got something new to learn: how to use AI well without losing our humanity. That’s really what this whole series is about.
Notice that two of those three ways of learning need another person. If we stop asking each other questions, we’ll get lonelier, and we’ll get worse at learning, too.
Two are better than one
There’s a passage I come back to a lot:
“Two are better than one, because they have a good reward for their toil. For if they fall, one will lift up his fellow. But woe to him who is alone when he falls and has not another to lift him up!” (Ecclesiastes 4:9–10)
That was written thousands of years before anybody imagined a machine you could talk to, and it still describes exactly what’s at stake. Work done together has “a good reward.” And the person who is alone when he falls, at work or anywhere else, is in real trouble.
A machine can give you an answer. I’ve never had one pick me up off the floor.
You don’t have to share my faith to know this is true. Everybody has had a day when a coworker’s kindness meant more than anything they actually told you.
What we’re doing about it
My teams haven’t solved this yet. But here are a few simple things we do on purpose:
When we’re in the office, we meet in person. If we’re in the same building, we don’t default to a video call. We get in the same room.
We eat together. We make a point of going out to lunch instead of eating at our desks staring at a screen.
We get together after work. Sometimes it’s an after-work happy hour. Nothing fancy, no agenda, just people.
We turn the screens off together. That might be the most important one. Being in the same room doesn’t help much if everybody’s still looking at a laptop.
None of this is complicated. It just doesn’t happen by accident anymore. Left alone, work drifts toward efficient and alone, so if you want connection you’re going to have to choose it.
What to do this week
Ask a person before you ask the machine. Pick one question this week that you’d normally type into an AI, and walk it over to a coworker instead. See what else you get besides the answer.
Eat lunch with someone. Away from your desk, screens down.
If you’re in the same building, meet in the same room. Skip the video call.
Learn the new tools together. Find one or two people who are figuring out AI too, and compare notes. You’ll both learn faster, and you won’t be doing it by yourself.
The machine will always be there with an answer. Make sure the people are still there, too.
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