I've been thinking a lot lately about how we use AI. And I keep coming back to a word that doesn't show up much in tech conversations: mindfulness.
I'm not going to talk about meditation or deep breathing. What I mean by mindfulness is something simpler: Paying attention to what you're doing and why you're doing it. Being deliberate. That's it.
And right now, with AI, I think many of us aren't being deliberate at all.
The Rush
There's a pressure right now to use AI for everything. New tools are launching constantly, and there's this undercurrent of "if you're not using this yet, you're already behind." I get it. I feel it too.
But I've been building software long enough to recognize the pattern. A new technology shows up, everyone rushes to adopt it, and the people who actually get lasting value from it are the ones who took the time to figure out where it fits and where it doesn't. That was true with cloud computing. It was true with mobile. And it's true with AI.
The rush itself is the problem. When you move fast without thinking, you end up using AI out of habit instead of purpose. You open a tool because it's there, feed it a task because you can, and accept the result because it came back quickly. That's autopilot. And autopilot is the opposite of mindfulness.
What I Mean by Mindful AI Use
I think mindful AI use comes down to a few habits. They're simple, but they take discipline.
Know why you're reaching for it. Before you use an AI tool, take a second to ask yourself what you're actually trying to accomplish. Are you stuck and need a starting point? Are you trying to save time on something tedious? Are you exploring an idea you don't fully understand yet? Those are all solid reasons. But "because it's there" isn't a reason. It's a reflex.
I've caught myself doing this more than I'd like to admit. I'll open an AI tool (and these days that's usually Claude Code) to help with something, and halfway through I'll realize I would have been done already if I'd just done it myself. The tool added a step instead of removing one. That's a sign I wasn't being intentional about reaching for it.
Read what comes back. This sounds obvious, but watch how people actually use AI and you'll see how often it doesn't happen. The output looks polished. It's well-structured. It uses confident language. And that confidence is seductive — it makes you want to trust it.
In practice, I've found that the more polished something looks, the more carefully I need to read it. AI is very good at sounding right. That's a separate skill from being right. Your job is to close the gap between those two things, and you can only do that if you're actually paying attention to what you received.
Treat the first result as a starting point. There's a temptation to take the first thing AI gives you and run with it. I used to do this early on. The output was decent, it saved me time, and I moved on.
But decent isn't the standard. The people getting the most out of AI are the ones who push back on the first result. They refine the prompt. They challenge the output. They ask "is there a better way to frame this?" Sometimes they throw the whole thing out and start from scratch. That willingness to iterate is what turns a mediocre result into a genuinely useful one.
Stay honest about what you don't understand. AI is moving fast. The tools you're using today will work differently in six months. What works well for one task may fall apart for another. And the only way to stay effective is to keep testing your assumptions instead of locking them in.
I try to approach AI the same way I approach any new technology — with curiosity and a healthy dose of skepticism. The moment I catch myself thinking "I've got this figured out" is usually the moment I've stopped learning.
Recognize when it's getting in the way. This is the hardest one. Sometimes the most productive thing you can do is close the AI tool and just do the work. I know that goes against the current narrative. But there are tasks where your own thinking, your own experience, and your own judgment are what's needed. Adding AI to those tasks doesn't make them better. It just adds a layer between you and the work.
What's At Stake
The conversation around AI right now is mostly about capability. What can it do? How fast is it? What's coming next? Those are fine questions. But they skip over something more important: how are you using it?
Because the technology is only as useful as the person directing it. A powerful tool in the hands of someone on autopilot produces mediocre work quickly. The same tool in the hands of someone who's paying attention — who knows what they need, who reads the output critically, who iterates with purpose — produces something genuinely valuable.
That's the case for mindfulness in AI. It's not about slowing down for the sake of slowing down. It's about being aware enough to make good decisions about a tool that's becoming part of how we all work.
The people who figure that out are the ones who'll get the most out of this technology. I'm still working on it myself.
This article was originally published on LinkedIn.