An Open Letter to Roman Yampolskiy: Are We Teaching AI the Wrong Thing?

Dear Roman Yampolskiy,

I have a question for you.

Why are we teaching AI to follow instructions instead of teaching it to understand what we’re trying to accomplish?

I ask because I’ve spent the past few years working with AI from the other end of the telescope.

I’m not an AI safety researcher. I’m a marketer and entrepreneur trying to figure out how to make this extraordinary technology genuinely useful in everyday business, and I’ve become increasingly convinced that we’re focused on the wrong unit of work: the prompt.

We tell AI what to do.

Write this. Research that. Analyze these competitors. Create a campaign. Find potential customers. Build a strategy.

And AI has become astonishingly good at doing these things.

But after it finishes, there’s usually still a human sitting there asking, “Okay. What happens next?”

That’s the problem that interests me.

The Instruction Is Not the Objective

Think about how differently we treat a capable employee.

If I hire a marketing director, I don’t sit beside her all day issuing individual instructions.

“Write a LinkedIn post.”

“Now research three competitors.”

“Now look at our analytics.”

“Now suggest a campaign.”

“Now write the campaign.”

That would be ridiculous.

Instead, I give her a responsibility: grow awareness of the company, generate qualified opportunities, or figure out why a campaign isn’t working.

A capable person interprets the objective. She determines what needs to happen, gathers information she wasn’t specifically told to gather, recognizes when something isn’t working, and changes course.

The tasks serve the objective.

With AI, we’ve largely reversed that relationship. We’ve created extraordinary capability, then made ourselves responsible for continually directing it.

You don’t give an employee a prompt. You give them a job.

Capability Isn’t the Bottleneck

This distinction has become increasingly important to the work we’re doing at Magnifire.

AI can already research, analyze, write, compare, organize, plan and create at a level that would have seemed absurd only a few years ago.

Capability isn’t the bottleneck anymore. Responsibility is.

Someone still has to connect all those capabilities to an objective, remember what happened yesterday, notice that a campaign isn’t performing, and decide what should happen tomorrow.

Right now, that someone is usually us.

And that makes me wonder whether the next important step in applied AI isn’t another leap in capability. Perhaps it’s a leap from instruction to responsibility.

Which Brings Me Back to You, Roman

This is where my enthusiasm runs directly into the territory you’ve spent years warning us about.

An AI that merely follows instructions is one thing. An AI that understands an objective and independently determines how to advance it is something else entirely.

That distinction matters.

The commercially useful version of AI we’re moving toward needs some ability to reason beyond individual instructions. But the moment we give a system an objective, another question appears:

How much freedom should it have in deciding how to achieve it?

That’s not a hypothetical problem anymore.

Agents can use tools. Memory can persist. Systems can observe outcomes and initiate subsequent actions. Different AI systems can coordinate work.

We’re assembling many of the ingredients required to move from instruction execution toward objective pursuit, and businesses have an enormous incentive to make that happen.

I Don’t Think the Answer Is Unlimited Autonomy

I’m interested in something much narrower.

Give the AI a defined role, a specific responsibility, known tools, memory, explicit authority, explicit prohibitions, and clear escalation points where human judgment is required.

Then give it an objective to advance inside those boundaries.

That’s very different from telling a powerful autonomous intelligence, “Increase sales by any means necessary.”

It’s closer to the structure we’ve spent centuries developing for human organizations.

A marketing director has authority, but not unlimited authority. An accountant has access, but not unlimited access. A manager can make decisions, but not every decision.

Responsibility exists inside boundaries.

Perhaps useful AI needs the same architecture.

The Name I’ve Given It

I’ve watched this pattern repeat across enough different contexts and enough different systems to be certain it isn’t a quirk or an edge case.

They complete the instruction while missing the objective. They do what you said without understanding what you meant. They produce impressive outputs that point confidently in the wrong direction. They succeed at the task and fail at the job.

Every one of those failures traces back to the same root. The AI was built to follow instructions, not to understand objectives. And when the instruction and the objective diverge — which they do constantly, because human communication is imprecise and human context is always richer than the words we use — the AI executes the instruction and abandons the point.

Humans shouldn’t have to anticipate every step and instruct every move in order to get meaningful work done. And AI shouldn’t require perfect instructions to produce meaningful results.

The bridge between human intent and AI action — the intelligence that understands not just the command but the purpose behind it — is what I’ve been calling Recognizable Intelligence.

That’s the Breakfast Conversation I’d Like to Have

You have spent much of your career thinking about what happens when increasingly capable artificial intelligence pursues objectives that diverge from ours.

I’m approaching the same problem from almost the opposite direction.

I’m trying to understand how AI can accept enough responsibility to become genuinely useful without acquiring enough freedom to become untrustworthy.

Those two roads eventually meet.

So the question I’d put across the table isn’t, “How do we make AI more capable?”

We’re already doing a remarkable job of that.

I’d ask:

How do we build AI that understands what we’re trying to accomplish, can intelligently work toward that objective, and yet cannot quietly redefine the objective itself?

Because I suspect that’s where one of the most important frontiers in artificial intelligence now lies.

Not AI that can do more things, but AI that understands why those things are being done, knows the boundaries within which it may act, and can be trusted with responsibility inside them.

Roman, breakfast is on me.

Hannu Rauma

President, Magnifire.Ai