Over the past year, 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. And yet something deeper has shifted.
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.
At first, I responded the way many of us probably did: I stayed tightly in the loop.
Generate, correct, generate again. Adjust tone, adjust layout, adjust structure, repeat.
It worked, but it was exhausting — in time, energy, and literal tokens. Eventually I realized something uncomfortable: I was trying to steer every artifact when the real shift wasn't about artifacts anymore.
It was about systems.
Pattern Recognition
AI doesn't remove 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 15 or 20 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.
The Emotional Toll
There’s also an emotional layer we don’t talk about much.
Watching organizations rush toward AI can feel both smart and cold at the same time. Necessary and destabilizing. Exciting and disorienting. It’s possible to believe this technology is powerful and still feel unsettled by how fast it reshapes roles.
What made it harder for me wasn’t just the change — it was the performance the change sometimes demands. In a company moving head-first into AI, being a “good team player” can quietly start to mean sounding enthusiastic enough, often enough, in the right rooms. Not because anyone explicitly says it, but because optimism becomes a signal: you’re on board, you’re current, you’re not a blocker.
And if that tone isn’t your natural voice — if hype feels forced or hollow — it can create a weird split: you’re genuinely using AI every day, while also watching how quickly the narrative shifts toward efficiency. When the conversation becomes “we can do more with less,” it can be hard not to feel the human implications in the room — even if the intent is progress, not disposability. You end up navigating two truths at once: the tools are powerful, and the transition can still be heavy.
If you’re in that space, it helps to reframe what’s happening: you’re not resisting. You’re recalibrating.
For me, the clearest realization has been this: my job can’t be to out-pace or out-produce the system. It’s to make sure the system produces things that still make sense — to preserve clarity, coherence, and human intent at scale. That doesn’t require hype. It requires judgment.
And maybe that’s the quiet opportunity in this shift: not becoming the loudest AI evangelist, and not retreating into nostalgia — but learning how to design decision environments instead of just artifacts.
If you’re somewhere in the middle of that transition too, hi. Good to meet you.
Disclosures: All thoughts are my own and do not reflect the views of my employer — though I’m pretty sure employer is also figuring this out in real time, because everyone is, but they would have their own point of view. No AI was harmed in the writing of this piece, but it was reached for comment.