But if I look past that momentary frustration, it has been a major enabler. An enabler, not a magic bullet.

And that friction is the point. The back and forth is where the thinking happens.

I sense another pattern emerging, though, and it is far more troubling, because it affects the foundation of a knowledge economy.

An email arrives, polished and well structured, every point carefully qualified. It reads like a lawyer wrote it. Sometimes that is the intent. Say many things without saying anything. Is the sender worried, or just being careful?

A strategy document takes an afternoon. Having a plan used to say something about how much thinking had gone into it. It says less now. The skill is in how well you can make it your own.

Ask for ten ideas and you get ten, ready to present. Where does originality stand in that? Many of them start to look alike. The one new idea in the room still has to compete with nine that sound just as good. I can look at a slide now and often guess which model created it, and then wonder what level of thinking went into it.

Vibe coding has made it easy to build something that runs. It also means a lot more things now look like products. The distance between something that runs and something that can be owned, supported and trusted has not shrunk much. It has just become easier to overlook.

I am calling out four easy places, but you might notice it in many others. The same paradox sits underneath: as producing good-looking work gets easier, judging what is actually good gets harder.

The finished thing used to carry some evidence of the thinking behind it. That premium is rapidly reducing. The thinking is still the hard part. It has just stopped being visible.

I have been on that side of it myself. I have had a slide made that certainly carried my conviction, but not my vocabulary, and then failed to articulate it well in my own language when presenting.

And the collateral debt shows up later. When the emails going back and forth are that hedged, the decision is the casualty. A plan nobody made their own gets executed anyway. Originality is lost in a barrage of sophisticated arguments. And the case for a well designed product gets less compelling when you can simply prototype with intent.

I do not think the answer is to slow any of this down. In fact, I would like it to accelerate, and how to do that well is something I am still internalizing.

What does it mean to put your name on something that took five minutes? When is polish a courtesy, and when is it a hedge?

The bar for producing came down quickly. The bar for judgment has to come up just as fast.

As I reflect on such inflection points, now and even earlier in my career, my mindspace has always been to stay curious, ride the wave, and shape it in your capacity and around you rather than wait for it to disrupt you.

Of the three lanes of AI adoption, enterprise and team need coordination with others. The personal lane is uniquely ours. It can be the most open ended, unhinged and creative of the three, and it stays with us wherever we go.

Personal here means you decide what to build and why. It can run through your day job or well outside it.

Here is a thinking model for it. Treat it as an investment and pay attention to the dividend.

The key is to recognize that building AI skills means different things for different people. In other words, what is your need and imagination as you look to embed AI in your personal rhythm. It is possible for some of you it could be more influenced by your work lane and that is ok.

For some of you it might mean AI augmented technical writing, an SLM based personal AI space, a research companion for a field you wanted to learn, an agent that helps your parents or your kid, or your own agentic home management system.

Once you have identified a work stream, then take your tasks and decompose them into logical units. Look at these tasks objectively. Some of these will stay with you. Some an agent can augment or replace. Some, over time, become an agentic flow you don't really touch anymore.

I would start small here and let trust and expertise build before expanding, since trust has many moving parts to it.

Next is synthesizing these agents into your own rhythm. This is where you become the confluence. The flows bring everything back to you, and you are the one adding the context, resolving what does not agree, deciding which risks actually matter and owning the recommendation.

In other words, think like a CEO, where judgement takes centrestage and not just task execution. Jobs of tomorrow will carry far more weight on the judgement side, and I suspect that is what separates folks who flourish in an AI native world.

As you iterate on various approaches, it is also important that you try and identify any differentiation which you can build on. I think of it as the elusive Super Power, always good to aspire for one.

Eventually these skills will start showing relevance in your work lane. When something works, keep it. These skills also help you stay close to, or take part in, conversations where you least expected to.

And then, with the time left, start building the next level of skills. That is the dividend. Building all this takes time and that is the investment, but when the next piece of work starts from what you already built instead of a blank page, some capacity comes back to you. Left alone it quietly disappears into more of the same. Directed, it can go into learning, into contributing at the team or enterprise level, and into the skills an agentic era will actually value.

The rhythm is yours to find. Some will build slowly and keep most of the work close, others will push more into the flows early. I don't think there is a right sequence here, only the question the dividend keeps asking: now that some capacity has come back, what is it for?

Stay curious. Stay hungry. Be your own frontier.

You gather context, move between tools, stitch information together, produce something, decide whether it is good enough, and own the result.

AI is not just making those motions faster. It is changing the shape of the bundle. More of the assembly can move to the machine. More of the human work shifts toward judgment.

Same title. Same work product. Different work.

I see it while drafting this post. The first draft, the summary, the structure — more of that can appear quickly. The harder part becomes deciding whether it is true, useful, and still sounds like the person who owns it.

The same pattern shows up across very different roles.

A product manager spends less time turning inputs into artifacts, and more time deciding which tradeoff to make when the inputs disagree.

An analyst spends less time pulling and formatting data, and more time deciding what the data means.

An engineer spends less time on boilerplate, and more time on the call about whether the design is right.

The work does not disappear. It moves.

And often, it moves toward the parts that were always hardest to describe in a job description:
· Judgment.
· Taste.
· Context.
· Accountability.
Knowing when something is off.
Knowing when to trust the machine enough to act.
Knowing when not to.
...

That is why I think the replacement debate misses something important.

The question is not only which jobs go away. It is how much the work inside existing jobs changes before the title admits anything changed.

This shift is not cleanly good or bad.

It is useful and disorienting — because it moves the worker closer to judgment and accountability before the job title admits anything changed.

First published on LinkedIn, May 10, 2026.

Not long ago, people went to San Francisco just to ride in a Waymo — a glimpse of the future made possible.

Then one showed up near our campus in Sunnyvale. Uninvited, but still exciting. Something shifted from "thing I heard about" to "thing that exists in my world."

Then one afternoon driving alongside me on the street. No driver. Just the road, and whatever was making the decisions. I pointed it out to my daughter. I wondered if this would feel ordinary to her by the time she grows up.

Then a moment I won't forget — a Waymo in my lane, another in the adjoining lane, and I realized I might be the only human driver in that stretch of road.

A few months pass. Seeing them regularly. The novelty fades, but a quiet curiosity lingers. Then clusters, parked outside the office. Just part of the landscape. Then one morning, parked on my street. My neighborhood.

That's normalization. Not a launch event. Not a press release. Just quiet, incremental presence. And yet, when I see one navigating an intersection, I still notice. I still evaluate. I still hesitate, just slightly.

Normalization and trust are not the same thing.

The visible part is the car. The invisible part is the discipline that made it safe enough to become ordinary. Most of us experience that shift as consumers, noticing it once it's already normal.

Somewhere else, for years, someone invested in the invisible layer that made that moment possible.

That difference is easy to miss.

First published on LinkedIn, March 7, 2026.