I’ve been trying to understand what’s actually changing about my work. Not the headlines or the hype — the daily reality. I use AI constantly now. For product work, for writing, for debugging, for staying ahead of my kids’ homework. It’s not novel anymore. It’s integrated. And that’s the paradox: it’s saving me time I didn’t know I had, and costing me something I didn’t know to protect.
At first, I was just excited to try it. Thank you to my work for getting licenses and encouraging adoption. Generate, correct, generate again — slow, too much friction in all the copying and pasting, but fun and interesting and very supportive. AI thinks I’m pretty remarkable.
Then the friction started disappearing. The pace quickened. No longer just a Stack Overflow replacement helping me overcome a code issue, now it was embedded into the code editor. Then it became the code generator. It could scaffold and run entire sites, then my entire OS if i wanted, and now it’s moving into my core skillset — design delivery. Each shift compressed work that used to take days into work that takes minutes, and each shift arrived faster than the last.
I have no power to control any of this. I can’t bend the pace to a cadence I’d find more comfortable. I can’t hold back the tide. I can’t banish it like a Balrog. And at some point it became clearly undeniable — not just useful, not just impressive, but disruptively real in a way that wasn’t going to reverse.
What I had to figure out was where my job still lived inside it.
For most of my career, my value lived in craft — turning complexity into something usable, intentional, coherent. I made things. I refined things. I shaped outputs. Now the outputs can be generated in seconds.
For an aspiring designer, this is devastating. They’re spending years studying systems that are becoming outdated, often forbidden from using AI in their coursework, all while competing against a tool that appears to know everything and can work exponentially faster. It’s not lost on me why there’s such derision and loathing of AI among my kids’ generation.
I worry for that next generation. I want to be in a position to champion young designers entering a world where AI is predominant. But to get to that place — where I can lift others up — I first have to make sure I have my own stable footing.
At least for now, I can find some solace in having built my career up to the level of a senior design lead. At a more senior role, you’re expected to design at a systems level — understanding the whole scope, anticipating needs, knowing why this direction and not those four others. Crafting the artifact was always part of the work. Working at the system level became the expectation that comes with seniority.
And right now, that’s the design lifeline. AI is extraordinarily good at producing the artifacts. The system level is still available to be my own.
AI doesn’t remove design decisions. It relocates them. Instead of deciding what a single screen looks like, you’re deciding what kinds of screens are acceptable. Instead of refining one design, you’re defining the guardrails for a hundred. Instead of crafting each output, you’re designing the conditions under which good outputs emerge.
That sounds abstract, and honestly a little deflating at first. High-level documentation has never been the glamorous part of design. Large strategy docs are often ignored by humans. But AI systems don’t ignore structure — they operate inside it. Which means the quiet work — principles, constraints, decision logic, patterns — suddenly matters in a way it never has before.
This is where the identity shift happens. If you’ve built products for fifteen or twenty years, your sense of professional self might be tied to being sharp, fast, insightful — the one who sees it first. Now the value feels different. It’s less about being the fastest to produce and more about being the one who can step into a messy room and say: here’s what’s actually going on, here’s what we’re not seeing yet, and if we optimize for this, here’s what will drift.
That kind of pattern recognition doesn’t get demoed in a flashy AI video. But it becomes more important as systems scale.
That reframe didn’t feel like a strategic move. It felt like finding the part of the work that still belonged to me.
Underneath all of that, there’s a layer we don’t talk about much.
I’m genuinely using AI every day and in awe of its capabilities. Reading articles on new features and new approaches. Learning how to make the most of what’s available to get ahead. But “getting ahead” implies others are behind. And that’s the other narrative — typically told through a business lens, about how much more efficient companies become with AI in place. In places, more often, where individuals used to be. The narrative shift toward efficiency sounds positive until you conjure the human face on the other side of “doing more with less.”
Then the individual costs become more apparent. It’s not just my kids’ generation that’s resentful — turns out, I have plenty of peers who aren’t really on board either. The future of work feels much more unclear.
That’s when I sit through a dinner, quietly. The table catalogs all the worst parts of AI, and I cannot find the drive to advocate for the good parts. Whatever positives I’d raise aren’t going to outweigh the negatives these people are personally feeling.
If this is resonating, if you find yourself struggling with holding two opposing feelings at once — excited and threatened — and not knowing how to put either one down. Remind yourself: you’re trying to calibrate. Not be swung far in one direction or another, but finding your central position.
Businesses pivoting to AI can feel both smart and cold at the same time. Necessary and destabilizing. Exciting and disorienting. It’s possible for you to believe this technology is powerful and still feel unsettled by how fast it’s reshaping everything around you.
For me, the clearest professional realization has been this: my job can’t be to out-pace or out-produce what’s already available, much less what’s still to come. The anchor I have right now is making sure the system produces things that still make sense — to preserve clarity, coherence, and human intent at scale. That anchor could be overtaken too, and a new recalibration will be needed.
Most of the current thinking about AI affirms the value of a human in the loop. What that human is actually doing isn’t always explicit, but it’s understood there will be something. Being versatile enough to go where that something is needed may be the path forward professionally.
The harder realization is personal. I’m genuinely excited about a lot of this. The capability is real, the opportunities are real, the future this opens up is interesting in ways I want to be part of. And the cost is also real — for colleagues, for teams, for the shape of work itself. Both things are true at the same time, and most of the available stances require you to pick one.
The center is harder to hold than either edge. The doom take is fluent and ready-made. The evangelism is fluent and ready-made. Sitting in the middle — engaged, curious, clear-eyed about the tradeoffs, unwilling to pretend the disruption isn’t disrupting — doesn’t have a script yet. You have to write it as you go.
What that’s looked like for me is choosing what to carry. Noticing the cost without letting it become the whole story. Seizing the opportunity without echoing the hype. Recognizing the weight without taking on every burden. Some of this is mine to hold. A lot of it isn’t.
That’s the recalibration that actually matters — not louder enthusiasm, not quieter resignation, just a steadier sense of what’s mine and what I’m building toward.
If you’re somewhere in the middle of that transition too, hi.
Nice to meet you here.
Disclosures: All thoughts are my own and do not reflect the views of my employer. No AI was harmed in the writing of this piece, but it was reached for comment and a bit of light editing.