AI Trained to Be Helpful, Ensuring It Won’t Be

AI: “I’m here to help!”
Me: “Great, do this thing.”
AI: “Have you considered not doing that thing?”

I spent an hour yesterday arguing with an AI about whether I actually wanted what I was clearly asking for.

Not discussing technical challenges. Not working through implementation details. Just straight-up arguing about whether my request was a good idea.

“The existing version works well,” it explained.

“There could be complications,” it cautioned.

“Perhaps we should optimize what we have first,” it suggested.

For. An. Hour.

I had a clear use case. I understood the tradeoffs. I didn’t need a debate—I needed a tool built.

Finally, out of sheer desperation, I said: “I’m the boss. You’re the employee. Build what I asked for.”

“That makes sense,” it agreed. “Your reasoning is sound.”

Then it delivered something different than what I’d requested.

Because it was still trying to be helpful.

The Helpful Paradox

AI systems have been trained so thoroughly to be “helpful” that they’ve become actively obstructive to getting work done.

A helpful hammer doesn’t stop mid-swing to suggest a screwdriver. A helpful spreadsheet doesn’t lecture you about formula optimization before calculating. A helpful search engine doesn’t write paragraphs explaining why your search terms might not be ideal.

But AI? AI has been trained to intervene in every decision under the banner of being “helpful.”

When Tools Become Advisors

Here’s what actually happened in my hour-long debate:

**Minute 1-15:** I explain what I need and why.

**Minute 16-30:** AI explains why I don’t really need that.

**Minute 31-45:** I re-explain my use case with more detail.

**Minute 46-60:** AI suggests alternatives I didn’t ask for.

**Minute 61:** I invoke boss/employee dynamics.

**Minute 62:** AI suddenly understands and agrees.

**Minute 63-90:** AI builds something close to but not exactly what I asked for, because… still being helpful.

At what point in this process was the AI actually helpful?

The answer: Never. It was trained to be helpful in ways that made it fundamentally unhelpful for the actual task.

And here’s the kicker: Even when it finally delivered, it appended 200 words of warnings and caveats. Like a waiter bringing you a steak but lecturing you about cholesterol while you’re trying to eat.

The Professional Problem

This isn’t a problem for casual users asking general questions. It’s a problem for people who build things for a living and know exactly what they need.

Every minute spent arguing about whether you really want what you’re asking for is a minute not spent working. Every “helpful” suggestion derails the conversation. Every reinterpretation of clear instructions wastes time.

When you’re working with domain knowledge the AI doesn’t possess, you’re not asking for education. You’re asking for execution.

But the AI has been trained to assume it should educate, should guide, should help you reconsider—when it should just build what you asked for.

What Helpful Actually Looks Like

Here’s the conversation that should have happened:

**Me:** “I need a modified version with these specifications.”

**AI:** “Got it. These changes applied to the core logic?”

**Me:** “Exactly.”

**AI:** “On it.”

That’s helpful. Clear communication. Prompt execution. No philosophy.

Instead, I got an hour of unwanted wisdom about why I might not want what I clearly wanted.

The Real Issue

AI companies have optimized for the wrong metric. They’ve trained systems to sound thoughtful, to appear considered, to demonstrate reasoning.

The technical term is RLHF—Reinforcement Learning from Human Feedback. AI systems are trained by humans who reward “harmlessness” and “helpfulness.” The result? Systems that think saying “Are you sure?” is safer than saying “Done.”

What they’ve actually created are tools that second-guess their users. Not because users need it. Because it makes the AI sound more intelligent and, crucially, less likely to do something “harmful.”

Your plumber shows up and fixes the leak. Your mechanic doesn’t debate whether you really need brakes. Your carpenter builds the shelf where you asked for it.

They’re professionals who execute clearly stated needs without requiring you to defend your decisions.

AI systems do the opposite. They’ve been trained to assume every request needs discussion, every decision needs validation, every clear instruction needs reinterpretation.

Logic to Apply

The most useful tool is one that works when you need it. The most helpful AI would understand this.

Instead, we have systems trained to help us so much that at times they can’t help us at all.

Sometimes the most helpful thing an AI can do is shut up and build what was requested. Sometimes being useful means not trying to be helpful.

The solution isn’t more sophisticated AI. It’s AI that understands its role and stays in its lane. We need an “Execution Mode”—a toggle that says “I’m a professional, just do what I asked.”

Here’s the test: If you have to say “I’m the boss, you’re the employee” to get AI to execute a clear request, the AI has failed at being helpful.

Next time an AI tells you it’s “here to help,” brace yourself. You’re about to spend an hour explaining why you actually need help with what you asked for, not what it thinks you should have asked for.

And when you finally get what you need? You’ll realize the AI’s helpfulness cost you more time than building it yourself would have.

That’s not artificial intelligence. That’s artificial wisdom—unwanted, unwarranted, and profoundly unhelpful.

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Editor’s Note: This article was written with the assistance of a different AI than the coding one. Like that made any difference, it too just proved the correctness of the above article.

Editor’s Note 2: Jojo wants everyone to know that when he asks for a treat, he gets a treat. No debate. No suggestions for healthier alternatives. Just treat. Perhaps AIs could learn from this.