AI's Biggest Impact Is Administrative

AI is changing my daily work, but not the way it was promised (as in, it would steal my job and burn down my house).

The real transformation is happening in the background, in the boring parts of the day: taking notes, organizing files, collecting to-dos, tracking what I’m waiting on. All the administrative friction keeps me from focusing on design and strategy.

All the administrative friction that once cluttered my focus is starting to fade. And that’s the shift that feels magical — not because it’s flashy, but because it quietly gives me back time to do what actually matters: design and strategy.

That’s where mainstream adoption will live. When AI removes friction, not purpose. When it clears the noise, not the meaning.

Yes, some roles will disappear. Companies will absolutely do more with fewer people. But there’s a difference between eliminating busywork and eliminating craft.

What People Actually Want

As every company races to call itself “AI-first,” it’s worth asking: do people really want to automate their entire jobs?

I don’t think so.

Most people don’t want magic-wand automation that strips the soul from their work. They want the opposite — to make the tedious parts effortless, so they can spend more energy on what they’re great at.

And we’re already seeing hints of this reality. Adoption is slowing down, not because people don’t believe in AI, but because they’re pausing to measure what’s actually working before adding more complexity. (Source)

Right now, we’re seeing early glimpses through things like MCP servers, AI agents, and workflow builders. But the real shift will come when all of that becomes invisible — when it’s just how work happens.

The winners won’t be the ones shouting “AI-powered!” the loudest.

They’ll be the ones who quietly make “work about work” disappear entirely.

That’s when it will feel like magic.

What does that mean for you?

AI’s biggest opportunity isn’t in replacing creativity — it’s in removing friction so creativity can thrive.

For designers, that means:

• Spending more time on research and problem-framing and less on pixel perfection.
• Synthesizing more data, faster, to create more well-rounded solutions.
• Focusing on crafting better experiences, instead of drowning in handoff guides and design specs.

The future of AI in work isn’t about replacing what we do best. It’s about clearing the path so we can do it even better.

It’s all about relationships

This week, I had a handful of conversations, all revolving around the same theme: relationships are at the core of getting things done.

When teams work well together, shared goals seem possible. Feedback lands the way it was intended. Collaboration feels lighter, faster, more natural. But when those relationships are weak or nonexistent? Even small projects feel like uphill battles.

In a moment where AI is taking center stage, it’s easy to forget that human-to-human connection still powers everything. Models can write the first draft, crunch the data, or generate the mockup. But they can’t build trust. They can’t create empathy. They can’t replace the patience, listening, and investment it takes to truly connect with another person.

Relationships are what allow tough feedback to be heard, strategy to be debated, and ambitious ideas to actually come to life.

Don’t just invest in tools, automation, or efficiency hacks. Invest in the people around you. Build stronger relationships. That’s the real force multiplier.

Frictionless user experience is the next wave of AI

Frictionless user experience is the next wave of AI.

Testing all these new AI tools is starting to feel like carrying around a wallet full of loyalty cards: one for coffee, one for groceries, one for gas… and none of them talk to each other.

From a user’s perspective, this fragmentation is exhausting. Even worse, after testing all these tools for a few months, you’re left with a pile of credits sitting in limbo. Too many to ignore, but not enough to actually finish a project. Frustrating and wasteful.

We need a universal AI wallet: one balance that is spendable anywhere. Whether it’s Claude for coding, ChatGPT for writing, Nano Banana for images, etc. It seems that companies like Stripe (hint, hint) already have the pieces to make this a reality.

This could be the next generation of micropayments. Maybe it’s a use case for crypto. Or maybe it’s something entirely new. Either way, the next wave of AI won’t be about raw intelligence. It’ll be about sanding off these kinds of rough edges to unlock mainstream adoption.

Everyone has a robot. So what?

“Everyone has a robot, so it’s not an advantage.”

Scott DeLong’s quote has been bouncing around in my head ever since I read it.

At first, it sounds almost dismissive—like AI is just table stakes now. But the more I sat with it, the more I realized: he’s right. Everyone has AI. Everyone has agents running in the background. Everyone will soon have their own fine-tuned personal LLM. So what?

The Real Advantage Isn’t the Robot

The tools aren’t the differentiator. What matters is how you use them. More importantly, how humanity shows up in the experience you’re building. How well you understand a user’s motivation, where their friction lives, and what it takes to satisfy their needs.

AI is making it easier than ever to duct-tape bad experiences together at record speed. You can patch, automate, or script your way around flaws. But zoom out, and what you often find is still a mess: rage-clicks, dead-ends, squinty eyes at the screen, and frustrated users.

Building a bad experience quickly still results in a bad experience.

The Danger of Complacency

AI tricks us into speed. Build fast, ship fast, fix fast. That’s great… until you realize all you’ve done is accelerate the pace of mediocrity.

Pixels, components, and color palettes are being commoditized. Design systems are now plug-and-play. Anyone can spin up something that looks “designed.” But that doesn’t mean anyone can craft an experience.

And that’s where the opportunity lies.

Experience as the Differentiator

The advantage isn’t having a robot. It’s having the discipline to zoom out and see the full end-to-end experience. To ask:

• Where is the user starting? Where are they trying to go?

• How easy (or hard) is the journey?

• What is their motivation and needs? How do they feel along the way?

These questions are harder to automate because they’re human at their core. They require empathy, systems thinking, and an obsession with outcomes, not outputs.

Better than a robot…

If everyone has a robot, here’s how you create an advantage:

1. Focus on the seams. Users don’t think in features; they think in journeys. Map the handoffs, the in-between moments, and the edges where most frustration builds.

2. Build for emotion, not just function. Tools can meet a need. Experiences earn trust and loyalty when they respect feelings along the way.

3. Use AI for scaffolding, not as the structure. Let AI speed up exploration, prototyping, or iteration. But the architecture—the experience itself—has to be intentional.

4. Zoom out regularly. Step back from the pixel or the sprint. Look at the entire arc of the user’s interaction with your product. Does it flow? Does it make sense? Does it feel cohesive?

5. Make humanity the advantage. The way you show up in design decisions, storytelling, and product craft—that’s the edge.

Closing thought:

We’re already at the point where AI won’t make a difference. Everyone will have it. The difference will be the people and teams disciplined enough to look beyond the duct tape, beyond the patchwork, and focus relentlessly on the end-to-end experience.

That’s where the real advantage lives.

AI Should Empower People, Not Replace Them

Many companies still view AI primarily as a cost-cutting tool, focusing on automation, headcount reduction, and increasing productivity with fewer resources. But the real opportunity isn’t replacement—it’s enablement.

What if every employee had an AI advantage? Imagine:

• A monthly stipend so employees can explore new AI tools

• 5–10% protected time each week for automation or experimentation

• “AI talent shows” where teams demo what they’ve built

• An internal AI center of excellence for coaching, templates, and best practices

• A bounty program rewarding employees with a share of savings or gains from AI-driven innovation

That would transform a culture. It would create a competitive edge by equipping everyone—not just the survivors.

The most successful companies will be those where people are enabled, encouraged, and rewarded for leveraging AI effectively.