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Everyone Hits This Wall with AI

  • Oct 23, 2025
  • 2 min read

Recently, a frustrated manager from a large FMCG company told me:

“AI is useless. It produces robotic texts, generic images, and wrong data.”

I hear this more and more. People start using AI tools — and hit a wall. The texts sound fake. The visuals lack detail. The style is off. The facts are wrong.

Here’s the truth: AI isn’t a better Google. It’s a gifted personal assistant with enormous potential — but one that, at first, knows nothing about you, your tone, or your goals.

If you treat it like a search engine, it will disappoint you. If you train it like a capable assistant, it will outperform you.

That’s what prompt engineering is about.

The old business saying fits perfectly:💬 “Shit in — shit out.”

You need to prepare your prompt carefully. Here’s a 5-step structure that works for any task — writing, visuals, audio, or code:


1️⃣ Explain who the AI should act as.

2️⃣ Describe the task clearly.

3️⃣ Provide context.

4️⃣ Show examples of what you want.

5️⃣ Give feedback and repeat.


💡 Example: Writing an apology letter to an unsatisfied client

Prompt:

Act as a customer success manager in a mid-sized B2B company. Write a short apology email to a client who received a wrong product batch and is frustrated. The goal is to rebuild trust, take responsibility, and offer a practical fix. Tone: professional, empathetic, and concise — 3 paragraphs max. Here’s an example of tone I like: “We value your partnership and understand the impact this has had.” After you write it, ask me if I’d like it to sound warmer, more formal, or more concise — and then adjust.

Try this approach once — you’ll never go back to one-line prompts again. It’s slower at first but works everywhere: text, visuals, audio, data, code.

 
 

Negotiation remains the core of commercial capability — a discipline where human judgment meets intelligent insight. It’s practical, empowering, and, perhaps for the first time in three thousand years, evolving rapidly. Mastering it today means learning to work with technology, not against it — turning data, empathy, and strategy into lasting advantage.

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© 2025 by Ruben Ter-Minasian.

All rights reserved.

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