Ted TschoppOver the last couple of years, I have built a growing set of AI agents and prompts to help me with different parts of my job. Over the last few months, something changed. Those agents became useful enough that coworkers started asking me for copies.
I gave them out. I published some on my website and on internal company sites. In the process, I got to watch something up close that I think matters a lot.
Once people get access to an AI agent that actually helps, one that remembers context, works around the clock, and can guide them through real tasks in real life, they do not want to go back.
Not because it is flashy. Not because it is hype. Because it is useful in a way that feels almost unfair.
It starts to feel less like software and more like an extra pair of hands.
That has clarified something for me about where all of this is headed. It has also clarified something else: for all the noise, churn, and panic around AI, there really is one skill that matters more than most of the others.
I am going to save that for the end.
Because to see why it matters, you first have to understand why so many people are still stuck.
Why So Many People Still Feel Behind
I have been tracking AI closely for a long time, and the rate of progress has been staggering. For years, it was hard to tell people where to begin.
Do you need to learn to code? Do you need to understand machine learning? Do you need a class? Do you need to master prompt engineering? Do you need to keep up with every new model release?
When ChatGPT launched, a lot of people assumed prompting itself was going to be the defining skill of the future. Clear instructions do matter. Prompting well helps. But I do not think that is the center of gravity.
What I see instead is a lot of people feeling scared, confused, and already behind.
And I see another group too: people who are willing to use AI only as long as it behaves like the software they already understand.
That second group is fascinating to me.
They want AI, but they want it to stay in its lane. They want it to feel like a better search engine, or a better dashboard, or a better help menu. Maybe a new feature tucked neatly into the corner of a program they already know.
They do not want a new paradigm. They want the old paradigm with AI sprinkled on top.
And I get it. Most of us do this when the future shows up early. We ask it to wear familiar clothes. We ask it to speak in accents we already trust. We ask it to sit down and behave like the tools that came before it.
But that is exactly why so many people are missing what is happening.
They are not just resisting AI. They are insisting that AI conform to their expectations of what software is supposed to be.
That is like standing in front of the ocean and demanding that the tide behave like a swimming pool.
Why AI Feels So Overwhelming Right Now
Of course it feels overwhelming.
For most of the history of personal computing, the number of interfaces we had to learn just kept going up. First there was desktop software. Then websites. Then mobile apps. Then portals, dashboards, subscriptions, notifications, and logins for everything under the sun.
Every service had its own little kingdom. Its own buttons. Its own menus. Its own vocabulary. Its own way of making you feel slightly dumb until you learned the layout.
Over time, the number of user interfaces you needed to function in the modern world just kept climbing.
More tools. More tabs. More context switching. More digital clutter.
Then AI showed up, and at first it looked like one more thing on the pile.
But I think that reading misses the deeper pattern.
For a while now, some people in the AI world have been predicting a final destination for all of this: that AI would become the operating system. Or, said another way, that AI agents would become the main user interface through which you reach everything else.
That sounded abstract a few years ago.
It does not sound abstract to me anymore.
What I think is beginning to happen is that the long trend line of modern software, the one that kept moving in the direction of more interfaces, is finally starting to bend the other way.
Not to zero.
To one.
My World Has Already Collapsed Toward One Interface
For me, a lot of the apps and websites I used to live inside have now collapsed into one place.
That place happens to be VS Code, because that is where I talk to a lot of my agents. But the exact app does not matter. The pattern matters.
Through that one conversational channel, those agents help me rebuild my website, gather and rank AI news, maintain benchmark lists, research articles, write drafts, and think through work problems. They also spill into more personal lanes: health, fitness, life admin, and all the little forms of friction that used to require opening five different windows and carrying my mind from one tiny digital room to another.
That is the shift I keep trying to explain to people.
Less clicking. Less hunting. Less interface management.
More conversation. More direction. More execution.
And that shift is precisely what some people still do not want to accept.
They want AI to stay boxed inside the old shape of software. They want it to remain a feature rather than becoming the front door. They want the machine to wait politely at the edge of the workflow instead of stepping into the middle of it.
But once you experience the middle of it, the old way starts to feel strangely clunky.
The Car Story
Earlier this year, I used agents to help me buy a car.
That still sounds a little ridiculous when I say it out loud, but it is true.
I was trying to figure out what I actually wanted, what the best financing options were, what negotiations made sense, and which dealership I should work with. The agents helped me sort through the tradeoffs, compare financing, think through negotiation strategy, and narrow the field.
In the end, it pointed me to Toyota of Redlands.
Now pause and compare that to the old way.
The old way would have meant bouncing between review sites, dealership pages, financing calculators, browser tabs full of conflicting opinions, and ad-saturated articles pretending to help while mostly trying to sell me something unrelated. I would have had to assemble the picture myself from fragments and noise.
Instead, I had a system that could help synthesize, compare, and guide. It did that part better than I could.
That is when something clicked for me.
A lot of the old software experience was never actually the valuable part. The valuable part was always the understanding. The software was just the toll booth you had to pass through to get there.
Once you start using agents that can help carry understanding across multiple domains, some of those old experiences begin to feel laughably inefficient.
Not because websites are evil. Not because every app disappears tomorrow. But because so much of what we called using software was really just us doing the integration work by hand.
AI changes that.
And some people still do not want to let that be true.
Do Not Let Resistance Dress Up as Research
This is also the moment when resistance gets clever.
It starts sounding wise. Responsible, even.
I need one more course. I need to understand everything first. The tools are not mature enough yet. It is not perfect. It still makes mistakes. I will adopt it once it fits our normal workflow. I will use it once it behaves more like the software I already trust.
Some caution is justified. AI does make mistakes. It needs oversight. It can be wrong with enormous confidence. None of that should be hand-waved away.
But a lot of what sounds like careful thinking is really fear in a blazer.
People do not want to be beginners again. They do not want to feel foolish. They do not want to change how they work. And most of all, they do not want to discover that the future may not organize itself around their preferences.
So they wait.
Or they demand that AI squeeze itself into the old categories before they will touch it.
But the point is not that AI should conform to our expectations of the old world. The point is that the world of software is already changing shape around us.
For most people, using AI is going to get much easier, not harder. The cutting edge will always be chaotic. That part is real. The people chasing frontier models, building systems, or competing at the highest levels will keep running hard just to stay in place.
But that is not most people.
For most people, the story is much simpler: the tools are moving toward them.
The interface is flattening. The friction is dropping. The barrier is lowering.
Which brings me back to that one skill.
The One Skill That Actually Matters
If I were starting over today, I would not try to master every tool. I would not memorize every model name. I would not build my whole plan around whatever the loudest person on social media said this week. I would focus on one thing.
It is the thing that turns AI from a parlor trick into leverage. The thing that separates a frustrating conversation from a useful one. The thing that will matter when the tools get cheaper, faster, and woven into ordinary life.
Here is what I have learned from building these agents, using them, and watching other people struggle with them: the people who get the most out of AI are rarely the people with the most jargon. They are the people who know how to bring the problem into the room.
They can explain where they are.
They can explain what they are trying to do.
They can show what they are seeing.
They can name the constraints.
They can say what success looks like.
And when the first answer is not quite right, they know how to add context and keep moving.
That matters because sometimes the agent can do the task itself. It can research, compare, summarize, write, analyze, draft, debug, and plan. Other times it cannot directly do the work because the work still lives in your body, your tools, your permissions, or the physical world. But even then, it can still move things forward, if you know how to bring it close enough to the problem.
A screenshot.
A photo.
A spreadsheet.
A rough draft.
An error message.
A sentence that says, “Here is what I tried, and here is where I am stuck.”
That is often the difference between frustration and leverage.
Which is why I think so many people are misunderstanding this moment. They are waiting for AI to become a cleaner version of old software. They are waiting for it to fit neatly inside the workflows they already know. They are waiting for the future to come dressed like the past.
But that is not how this works.
The people who will do well here are not the ones who demand that AI conform to their expectations. They are the ones who learn how to work with it as it actually is becoming.
So if you feel behind, take a deep breath.
We are standing in the fog, and a lot of people are mistaking the fog for the future. But from where I sit, it feels more like a marine layer on the coast: thick in the morning, disorienting for a while, enough to make you wonder whether the sun is still there. And then, almost without warning, it starts to burn off.
That is what I think is happening for most people.
You are not going to need to master a hundred different tools.
You are going to need one habit: the ability to bring another mind fully into the work.
And here is the trick.
This may not be a new skill at all.
It is what makes good marriages work.
What makes good teams work.
What makes good leaders work.
What makes good friendships work.
The one skill you need to be successful with AI?
Collaboration.
