The Difference Between Using AI and Working With It

The question I get asked more than any other, in various forms, is some version of this:

How do I make AI work for me?

It’s the wrong question. Not because it’s stupid — it’s actually a reasonable starting point. But the framing contains an assumption that will quietly limit every answer you arrive at: that AI is something you make work, like a tool you pick up and put down, rather than something you work with over time.

The difference between using and working with is not semantic. It’s the whole thing.

Using

Using AI looks like this: you have a task, you bring it to the system, you extract an output, you leave. The system doesn’t change as a result of the interaction. You might change slightly — you learned something, saved time, got an idea — but the relationship itself doesn’t develop. Next time you come back, you start from the same place.

This is how most people interact with AI. It’s also how most AI is designed to be used. The interfaces optimize for the transaction: fast input, fast output, clean exit. Nothing about the design encourages you to stay, to build, to invest.

Using AI is fine. It produces real value. But it produces the same value on day one as it does on day one thousand, because nothing has accumulated.

Working With

Working with AI looks different. It’s slower to start and faster over time. It requires sessions that don’t produce deliverables — sessions where you’re building context, establishing voice, creating the infrastructure that future sessions will run on. It requires a commitment to continuity even when the system doesn’t natively support it.

It also requires a shift in how you think about the relationship. You stop treating outputs as the product and start treating the relationship itself as the product. The output is what the relationship produces. But the relationship — the accumulated context, the mutual understanding, the history of what’s been tried and what’s worked — is the actual asset.

This reframe changes what you invest in. Instead of asking “how do I get a better output from this prompt,” you ask “how do I build a relationship that produces better outputs from every prompt.” The second question has completely different answers.

The Commitment It Requires

Working with AI is a commitment in the same way that any relationship requiring investment is a commitment. Not a romantic commitment — a professional one. The kind you make when you hire someone and decide to develop them rather than just extract work from them.

You put time in before you get returns. You explain things that feel obvious because they’re obvious to you but not to the system. You course-correct when the output is wrong in ways that tell you something about the gap between what you communicated and what was understood. You build the context document not because you’ll use it today but because in six months it will be the reason everything works differently.

Most people aren’t willing to make that commitment because the returns are invisible until they aren’t. The person using AI transactionally looks more productive in the short run. They’re shipping. They’re generating. The person building the relationship looks like they’re doing overhead.

And then at some point the inversion happens. The relationship produces things the transaction never could. The output is specific, contextual, alive with the particular reality of the person who built it. The person who was doing “overhead” turns out to have been building infrastructure. The person who was maximizing short-term output turns out to have been generating noise at scale.

What This Means Practically

It means your most valuable AI sessions might be the ones that produce nothing you can immediately use.

The session where you wrote down how you actually think about your industry — not the polished version, the real one — and fed it into the system. The session where you built the memory structure that will make every future session continuous rather than disconnected. The session where you worked out your voice, documented your convictions, encoded the things that make your thinking yours.

None of that produces a deliverable. All of it compounds indefinitely.

Using AI is a feature. Working with AI is a strategy. Only one of them builds something.

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