Great power, requires better strategy

There's a moment that keeps happening. I sit down with a list of things I could get done today, things that would have taken a whole team three weeks just a couple of years ago. By the afternoon, I've started four of them. I've finished none. And somehow I feel further behind than I was when I started.

This is a new feeling for me, where capability and output is going up and progress and organizations is going down at the same time; and I'm calling it the Productivity Paradox. I think a lot of leaders are quietly living in it right now.

I'm learning in a few different ways, but it's apparent that AI doesn't directly replace strategy. In fact, It exposes the lack of it. With the right plan in place, it is the most powerful accelerator we have ever had. Without one, it is the fastest way I have ever seen to create a lot of work without creating very much progress.

Here is what I mean, broken down into the patterns I keep seeing in myself, and in the leaders I talk to.

1. Critical thinking gets spread too thin

The first place this shows up is in my own head. I can chase ten ideas in a morning. The tools make it cheap to start anything, so I start everything. ADHD super power, ignite!!!

What I've noticed is the inevitable 'fog' that comes with that. It is not the kind of tired you get from working hard on one focused thing. It is a more frustrating and confusing kind; the kind where I am bouncing from a marketing angle to a process doc to a video script, and every time I switch I lose the momentum I just built. I set an AI task to run, and in those few minutes my attention drifts to the next thing, and now I have to re-center on the first one when it comes back. I have to re-read what I just wrote to remember what I was even doing. That re-centering takes energy. A whole day of that, and I am cooked.

It is like trying to keep a stack of plates spinning. Once one starts to drop, the rest start to wobble, and the rest of the day turns into a recovery operation. Nothing finishes. Everything stays half alive.

If I had stayed on one of those ideas for two uninterrupted hours, half of them would have died a natural death. They did not deserve to live. But because the cost of keeping them alive in some half-formed state is almost nothing now, they all keep existing, taking up just enough room in my head to drain me without producing anything I can ship.

My tangents, that were once only ideas, start to take a life of their own, and create a chaotic little family.

2. The Zombie-Brain problem

There is a second cognitive shift I keep watching happen, especially in the first stage of adoption when somebody brings a new tool into their workflow. People stop applying real thought to what they are asking AI to do. The instinct is, well, the machine is doing the work now, so I do not have to think about it the way I used to. I will just check it when it comes back.

Oh shit, the robot ate your brain.

The trouble is that we usually do not really check it when it comes back. We skim. We assume it is in the right ballpark because the formatting looks clean. We flip it over to whoever needs it, or we publish it, or we send it. All of that happens without the layer of judgment we would have applied if we had written it from scratch.

This is the part that defeats the whole purpose of having a human in the loop. The point of human oversight is not to format the output. It is to bring the context, the standards, the brand voice, the institutional memory, and the strategic sense that AI does not have access to. The moment we stop applying that, AI is no longer being supervised. It is just running.

When the cognitive layer goes away, the cost shows up almost immediately. AI gets the situation slightly wrong. It uses phrases your team would never use. It states something with a confidence that is not supported by what it actually knows. And then somebody downstream has to quietly figure out what is off and clean it up.

That is the paradox in its purest form. The tool is technically doing the work, but the work is not actually getting done, because the part that needed a brain in it got skipped. We saved time on the doing and lost more time on the cleanup.

3. Output capacity without strategy means team overwhelm

The same pattern plays out at the team level, just with bigger numbers attached.

The thing AI has genuinely changed for us is throughput. We can produce more content, more reports, more SOPs than we ever could. The speed of execution is starting to catch up to the speed of ideas. That part is real and it is something to be excited about.

But handing a fully-scheduled team forty more pages does not move the company forward. It just moves the bottleneck. They are not capability-constrained anymore. They are clarity-constrained. If you do not know what you actually want produced, AI will happily help you produce too much of the wrong thing, and then your team has to wade through it.

The hard part is that when you are moving this fast, you can mistake volume for momentum. The reports are showing up. The decks are being created. Things look productive. Underneath all of it, your team is burning out trying to keep up with output that was not strategically filtered before it left your desk.

4. The moving target, and the burnout that comes with it

There is a separate kind of fatigue that does not get talked about enough. It comes from the fact that whatever you figured out yesterday is already changing today.

The tool got better. The workflow shifted. The system you spent two weeks building is already a slide in somebody's webinar about why that approach is outdated.

When you are climbing a mountain, there are ledges. You stop, you look at how far you have come, you take a breath, you keep going. What AI feels like right now is climbing a building that is still being built above you. The structure keeps growing while you climb it. There is no ledge. There is no view. There is no visible top.

That is what burns leaders out. It is not the work itself that does it. It is the absence of a place to stop and rest.

The answer is not to slow down the technology. That is not a fight any of us are going to win. The answer is to build your own ledges. Decide what done means for the week. Decide what enough means for the quarter. Pick a destination, so you are not climbing just because the building keeps going up.

5. The completion problem, and the internal closure you stop getting

This one took me a while to put my finger on, and I think it is one of the quieter costs of how we are working now.

When you were the one writing the proposal from scratch, the one drafting the email, the one building the deck, you knew when it was finished because you felt it finish. That sense of done was tied to the work itself. You were inside of it the whole way through.

Now you hand the first draft to AI. Maybe the second and third too. You come in for revisions, you tweak a few things, you send it out. The deliverable closes, but something inside you does not. You are not actually sure you finished it, because you were not fully involved in it in the first place.

Humans are wired to need completion. We need the click of something closing out to fuel the energy for the next thing. AI workflows tend to produce the opposite of that. Drafts become revisions, reports spawn more reports, ideas keep branching. Nothing ever truly clicks shut, and even when it does, you were not in the room enough to feel it.

After a few weeks of that, you start to feel a particular kind of tired. It is the tired of having worked all day and not being able to point to a single thing that actually completed, in you.

6. The Delegation Void

This is arguably the one that sneaks up on you, and can create the most problems.

The old reason to delegate was simple. You could not do something yourself, or it was not the best use of your time. AI quietly broke both halves of that equation. Now leaders have a web developer, a sales agent, a copywriter, and a coder all sitting at the desk with them. Roles we never hired, never trained, never even committed to fielding. And because we can do these things ourselves now, at a tenth of the time it used to take, we stop reaching for the handoff.

Two things tend to happen from there.

The first is that the work does not leave our plate. It just stops going anywhere strategic. It is not clean enough to push to a team member. It is not big enough to bring in a third party. The team is already underwater from the last round of AI-accelerated output. So the leader keeps it. Quietly. Adds it to a list that is already too long.

The second is side-project sprawl, which hits especially hard for the entrepreneur ADHD brain, and a lot of us have it. AI makes every new idea feel feasible. You think, "I could just build that." So you start. Then you start another. Then it is Saturday at 11 p.m. and you are three projects deep, and somehow you have added more to your plate, not less. The tool that was supposed to give you time back is now the reason you are working evenings and weekends. WTF?!

There is a third thing worth saying too, because it is where the team pays for all of it. When leaders do finally try to push something off, it is often half baked. Half explained. Half strategized. A marketing assistant gets handed a website to design, or asked to develop a SaaS pricing model. Work that is hard enough for someone who specializes in it, and almost impossible for someone trying to reverse-engineer the leader's half-formed thinking. That is not delegating. That is dumping.

The fix is not to delegate more. It is to remember that the question, "should I do this myself?" is still the right question, even when the honest answer is "I technically can." Capability is not the same as appropriate use of time. The cost of doing it yourself dropped. It did not go to zero.

These are the steps to avoiding the Proximity Paradox:

I am still working this out. Here is what is helping so far.

Map it out before you start it. Before I touch a tool, I try to write down what the thing is, who it is for, who is actually going to do it, what resources or people it needs, and what done looks like. It is the unglamorous part that nobody wants to do. It is also what saves you from realizing halfway through that you started something on a whim and you are already too far down the rabbit hole to back out gracefully.

Stay in the loop, not above it. AI does the work, but the judgment still has to come from you. That means actually reading what comes back, catching the wrong phrase, fixing the misread of the situation, applying the standards the tool does not know. The minute you stop doing that, you are not supervising anymore. You are just forwarding.

Define the outcome, not the output. Not the format. Not the tone. The outcome. What is this meant to move, for whom, by when. Without that, AI will give you a beautifully formatted version of nothing in particular.

Limit concurrent threads. Pick the one or two ideas that get real focus this week. Kill the rest, or park them with a date. Most of the ones you park will look smaller in two weeks anyway.

Build your own ledges. End of week reviews. Quarterly stopping points. Goals, rocks, or whatever you call them... Something, anything, that gives you a place to stand and look at what has been done.

Use AI to compress, not to multiply. Compress execution time on the right work. Do not multiply volume across all of it. The win is not doing more things. The win is getting the right things done faster, so there is room for the next right thing.

Set protocols for what not to produce. With your team and with yourself. The list of what is worth saying no to matters more than the list of what is worth saying yes to.

Ask the old question. Even though I can, should I? It used to be automatic. Now it has to be deliberate.

The takeaway

We have never had more power in our hands than we do right now. The potential of what we can do, individually and as teams and as companies, is immense. And like every other time something powerful has landed in human hands, it comes with the responsibility to use it well.

With great power comes great responsibility. The line is old enough to be a cliche, and it has never been more accurate than it is right now.

If we do not wrap strategy, purpose, and human intention around what AI can do, we will create more damage than good. For ourselves. For the people who work with us. For the companies we are building. For the work we actually came here to do.

The technology is incredible. That is not the question. The question is whether we are using it to build toward something specific, or whether we are using it because we can.