This is the moment a brand has been working toward. After they spent money to acquire you, you’re in.
Now they need to reinforce to you that you made a great decision. Done right, this can make the next purchase feel like your idea.
Some brands get this right. Many don’t. Instead of welcoming you, they barrage you.
One recent shoe purchase triggered daily generic offers — pitching to me as if my last purchase never happened. Signing up for a streaming service earned me four emails on day one, and four more by noon on day two — almost begging me to watch something, anything.
It’s the difference between earning your loyalty and wearing you down until you open your wallet.
The obvious move when there’s a leadership opening is to promote the top performer. The best gift officer becomes the fundraising director. The most experienced copywriter takes over the creative team.
It makes intuitive sense. They know the work.
The problem is that doing the work and leading the team require very different kinds of knowledge.
Conflating one kind of knowledge for another is an easy mistake. And a costly one.
I’ve watched this play out across fundraising teams, marketing teams, and policy teams. The pattern is consistent.
The star performer steps into leadership assuming their domain mastery covers the new role. Not out of arrogance. It just never occurs to them that there’s different knowledge required.
This is unearned confidence in a new domain: an incomplete model of what the job actually requires.
A great gift officer knows more about building relationships with major donors than anyone on the team. A great fundraising director knows who knows what, and how to use it.
Sometimes this is the same person. But that shouldn’t be assumed.
The best leaders I’ve worked with don’t pretend to have all the answers. But they know who does. They understand that knowledge is distributed across a team — that their job is to use that knowledge to inform decisions, not to supply the answers themselves.
Lots of things in life come with defaults — the tip amounts suggested at checkout, your employer’s benefits package, the school your kids attend.
They’re easy to accept. But they were designed for other people’s preferences, not yours.
Consider our phones.
The defaults organize our phones around a particular assumption: that we want to be engaged constantly. A banner notification, or a loud chime, or a little red badge counting unread messages.
It’s a reasonable assumption. For a while I accepted it. Then I realized I was responding to the phone more than using it.
One popular fix is to disengage entirely. No notifications, nothing that might interrupt. But even that wasn’t what I wanted.
Instead, I curated. Removed apps, deleted social media, pared the dock to the apps I use most. Turned off most notifications and badges.
The point wasn’t to remove notifications. It was to stop treating defaults as decisions.
I kept a few notifications that were doing something. Calendar alerts prompt me to switch contexts — which is why things are on the calendar. Texts from certain people are worth interrupting for.
Physician Helen Ouyang argues that doctors shouldn’t reject AI:
A.I. may not replace doctors, but it will change what patients expect from us. Doctors need to adapt…
The reality is that many patients are already consulting A.I. Doctors can keep fearing or condemning those interactions, or they can figure out how to support people using A.I. tools for their health care — cautiously, with clear guardrails. I would never tell patients to ask ChatGPT or Claude for a diagnosis, but perhaps I would suggest they use it to make sense of a new condition or keep up with routine screenings — or translate “diet and exercise” into steps that actually fit into their lives, as I did.
She’s right. And she’s pointing at AI’s real potential. While much of the conversation is about the technology’s potential to replace work, the real story is how it can radically expand options.
Think about what that means in medicine. Patients who would never book an appointment for a minor concern can get a useful answer. Vague advice — “diet and exercise” — gets translated into steps that actually fit someone’s life. Doctors can spend their time seeing more patients or helping the patients who need them most, not fielding questions that don’t require a physician.
This is already how AI is playing out in other industries. Axios’ Jim VandeHei explains how it’s unlocking new possibilities in journalism: “The bigger opportunity isn’t efficiency. It’s new business lines that were economically impossible before AI.”
More people solving more problems that couldn’t be solved before.
Preparing for a recent trip, I downloaded For All Mankind season five — ten episodes of high-resolution video. It took about 20 minutes.
To get that much video 30 years ago, I’d have to schlep to Blockbuster, hope they had the tapes in stock, and pay around $40 in today’s money. Then watch them on a low-res TV before returning them two days later.
Downloading from the internet certainly wasn’t an option. In the late 90s, a single MP3 — three minutes of music — took an hour to download on a good day.
Today, though, my home internet connection runs roughly 10,000x faster than the dial-up of 30 years ago, for about 3x the nominal cost.
No one person or organization planned this improvement. It came about because millions of people — customers, engineers, broadband companies — each pursued their own goals.
That’s what progress looks like when it’s working. There’s no grand announcement. Just millions of people acting on their independent plans — until one day you’re downloading a season of television in the time it takes to pack your suitcase.