I’ve been thinking about how my relationship with AI will change over the next decade.

Not in the abstract “AI is the future” way, but in the way that matters in the hospital, like when do I reach for it, what do I trust it with, and what happens when I’m no longer a trainee who can say, “I’m still learning”?

Right now, I use AI for two things: learning medicine faster and getting the administrative stuff out of my way. This mix feels good for training, but I don’t think it holds as I become an attending.

There are tasks I do today that are technically “doctor work,” but functionally clerical.

These tasks require accuracy and attention, but they don’t require my best thinking.

When I use AI well, it doesn’t replace me, but it gives me a first draft so I can spend my attention on things that matter like patients at the bedside, my team, and the fun, nuanced decisions that aren’t obvious.

The other way I use AI right now is the part people love to debate: clinical knowledge and reasoning.

As a resident, I’m still building my internal library. AI helps me search faster, synthesize faster, and test myself in ways I can’t always get in real time.

I’ll take a case and ask the model to function like an attending and poke holes in my assessment and plan. I’ll have it turn patient presentations into board-style questions. I’ll use it to walk me through PFT interpretation and force me to explain each step.

The question is what happens when I’ve seen enough patients that I’m not asking “what is this” nearly as often? Because the goal of training is that the fundamentals become automatic.

I think the kinds of questions I ask will shift, not disappear. As I move into pulmonary and critical care medicine on July 1st, and get more specialized, the bread-and-butter gets boring. The edge cases get interesting.

My future AI use is probably less “teach me pneumonia” and more “help me think through the weird drug interaction I haven’t seen in two years,” or “what’s the nuance in the guideline footnote that matters for this exact patient.” Fewer questions but higher-level questions.

There’s another factor that changes as you become an attending: responsibility.

As a resident, I’m the frontline clinician. I see the patient more than anyone else on the team (including the attending). As an attending, though, the buck stops with me—no matter what. I’m responsible for what the residents do, what the interns do, what the notes say, what the plan is, and how it all connects. That responsibility changes how you think about tools.

I don’t want AI to be the thing that does my thinking for me. I want it to be the thing that makes my thinking sharper.

And there’s a kind of clinical intuition that comes from repetition that AI can’t replicate.

I’m thinking about the patient with severe right ventricular dysfunction who’s now hypotensive. The room has a feel to it. You’re weighing physiology, trajectory, what’s about to happen next, and what you’re willing to try in the next five minutes (actually, probably seconds).

You can ask an AI model for a differential and management options. That can help. It can also distract you if it’s noisy, overconfident, or generic. The seasoned physician’s job is pattern recognition plus judgment.

AI has the pattern library. It doesn’t have the judgment that comes from owning outcomes. (Feel free to quote this).

Here’s what I suspect will separate “useful AI” from “annoying AI” as I get more experienced: how quickly it gets to the point.

Early in training, more context feels helpful. I want the explainer and I want the background. Later, I’ll want the answer, the caveat, and the one thing that would change my plan.

Some tools will keep producing long, fluffy, “nice-to-know” responses. Seasoned clinicians won’t have patience for that (let me know if I’m wrong, seasoned physicians).

In summary, what I want from AI is simple. I want AI to take the low-value work off my plate and make my high-value work better. I want it to help me learn faster now, and help me practice cleaner later. And I want it to free up enough attention that I can become the kind of doctor I’m trying to become: present, dec