# Attention Is All There Is

Dear fellow technologist,

It’s not just you. Everyone in tech is worried.

I’ve heard the same fears from recent grads at hackathons to senior peers at meetups. And it’s not just engineers. Or designers. Or ICs.

It’s product. It’s management. It’s leadership.

It’s everyone.

Including myself.

We’re all navigating this together.

AI is not a fad. It is not going away. The shape of our work is changing in real time, and nobody fully knows where this ends up. But eventually, this pace of change will become normal. The noise will settle into the background. The work will continue to be the work.

It’ll just look different.

The tooling will change. Team sizes will shrink. Expectations will increase. The economics of building software will change. The line between what makes sense to build, buy, automate, maintain, or throw away will shift.

But the work itself is not disappearing.

It’s just becoming cheaper.

And when execution becomes cheaper, the scarce resource shifts from time to attention.

By “attention,” I mean the judgment, care, taste, and sustained effort required to build something good.

For most of my career, execution was the bottleneck.

• Could we build this?
• Could we afford this?
• Did we have enough engineers?
• Did we have enough time?

And because it was the bottleneck, execution had risk. Implementation cost money. Coordination cost money. Mistakes cost money.

So organizations built systems to reduce that risk:

• Planning.
• Process.
• Approvals.
• Meetings.
• Specialization.

And even then, you often still built the wrong thing.

AI meaningfully changes those equations.

A single person can now generate more code, more designs, more writing, more prototypes, more ideas, and more experiments than ever before.

• Iteration is cheaper.
• Experimentation is cheaper.
• Validation is cheaper.

Cheaper execution just changes where the bottleneck lives.

Someone still has to decide:

• What is good.
• What is correct.
• What is coherent.
• What aligns with the vision.
• What should actually exist.

That work does not disappear - it becomes more important.

Managers already operate this way. It’s how founders scale. Agency owners, creative directors, tech leads, producers - they all understand the reality of high-leverage coordination work.

So, even in a future where one person can direct the output of ten engineers’ worth of AI agents, there are still limits. Not technical limits - human ones.

Because the hard part was never typing.

The hard part is:

• maintaining context
• recognizing problems
• spotting inconsistencies
• giving useful feedback
• preserving quality
• making judgment calls under ambiguity
• staying aligned on what matters

AI systems are powerful, but they are also human in the ways they fail.

They get distracted. They optimize for the wrong thing. They misunderstand intent. They produce confident nonsense. They miss obvious context. They stop being curious.

And when that happens, someone needs to redirect the work.

Direction itself is becoming the job.

The future will involve smaller companies, smaller teams, and dramatically more leverage per person.

But it will also create entirely new businesses that previously couldn’t exist economically.

A company that once needed fifty people may now need five.

A founder who once needed funding may now just need conviction and good judgment.

A niche product that never could have justified a full engineering team may suddenly become viable.

But someone still has to care.

Someone still has to ask:

• “Is this actually good?”
• “Does this solve the problem?”
• “Does this feel right?”
• “Should we ship this?”

This transition is going to feel very different depending on what you valued about your work in the first place.

If the act of doing was the thing you loved most - the typing, the implementation, the craftsmanship itself - this may feel like you are letting go of the steering wheel as the car flies down the highway.

Terrifying.

But if what you loved was the value creation - solving problems, building systems, helping organizations move faster, shaping products, making ideas real - this can feel like gaining superpowers.

We’ve seen shifts like this before.

Higher levels of abstraction have always changed the shape of technical work.

This may be the biggest shift yet.

Or it may not be.

Either way, my advice is this:

Move closer to the value.

Understand how the business actually works. Understand where money comes from. Understand what customers actually need. Understand why decisions get made.

Find people and businesses with real problems worth solving.

Learn how to direct leverage, not just produce output.

Because execution is becoming cheaper.

But attention is not.