Honestly, until a few months ago I had no idea this role even existed. But now I am fascinated by it.

So, what exactly does a Prompt Designer do? They are basically translators between humans and AI. They know how to "talk" to artificial intelligence to get the best results — turning our messy, creative ideas into clear instructions that AI can actually understand and work with.

Why am I so excited about this? Because every time we use ChatGPT, Claude, or any AI tool, the quality of our results depends entirely on how we ask. And that is a skill that can be learned.

The AUTOMAT Framework

AUTOMAT is an acronym I have been using to structure my prompts more intentionally:

• A — Act as a particular persona. Who is the AI impersonating?
• U — User Persona and Audience. Who is it talking to?
• T — Targeted Action. What do you want it to do?
• O — Output Definition. How should the response be structured?
• M — Mode, Tonality, Style. How should it communicate?
• A — Atypical Cases. Are there edge cases to handle differently?
• T — Topic Whitelisting. What relevant topics can it discuss?

The framework sounds technical but it is really just common sense made explicit. When you ask a colleague for something, you naturally give them context, specify the format you need, and tell them who it is for. We forget to do this with AI — and then wonder why the output is generic.

I am still learning this. But the more I practice, the more I see prompt design as a form of communication design — and that feels very close to what I have always cared about.

Today, AI helps me study, explore, and go deeper. Many fear that using AI will weaken our ability to think. Part of me agrees. But the real question is not whether we use AI — it is how, and how consciously.

Two mistakes I see everywhere

1. Letting AI do the work for us. If we delegate the cognitive effort, we also cancel the learning. No effort = no neuroplasticity. Growth requires friction.

2. Treating AI summaries as primary sources. A summary of a summary is not knowledge. It is processed content, often built on weak or second-hand sources. If you ask AI for research, ask it for the sources — then read them yourself.

Learning lives in the "desirable difficulty" zone: hard enough to stretch you. Not so hard that you give up.

How I actually use AI to learn

I use AI as a tutor, not a substitute. I do not ask it to summarise what I have not read. I use it to:

• Discuss ideas I have already studied
• Challenge my reasoning
• Generate metaphors that help me understand faster
• Translate concepts across domains or languages
• Explore different perspectives on something I already have an opinion about

AI is a tool. The hype will pass. Your curiosity and passions are what matter. Fall in love with the goal, not the tool. And protect what makes us human: creativity and critical thinking.

Pantone chose Mocha Mousse as the colour of 2025 — it is warm but not aggressive, neutral but with personality. The moment I saw it, I wanted to explore what it actually means visually.

My process: I started gathering references on Pinterest, then organised them in PureRef to build a cohesive moodboard — colours, subjects, palette, architectural elements. I was after something almost photographic, something I could imagine in a design campaign.

Then I used Midjourney to bring these concepts to life, iterating until the atmosphere felt right.

For those working in design or marketing: this combination of tools is especially useful in the exploratory phase. Quick concepts, testing directions, mockups for presentations. They do not replace real work, but they accelerate that phase where you are still figuring out where you want to go.

Each image must serve a purpose. I am learning to use AI generation not as a final output, but as a thinking tool — a way to make the abstract concrete before committing to a direction.

As an architect, I have spent years developing an eye for proportion, light, material. Could a prompt really capture any of that?

A few months in, my answer is: sometimes yes, often no — and the gap between the two is entirely on me.

This week I have been working with PANTONE 11-4201 Cloud Dancer — one of the key colours for 2026. It has been a surprisingly good test case. Cloud Dancer is not just "off-white." It is a specific mood: stillness, restraint, the kind of quiet that feels intentional rather than empty.

The tool does not replace the designer's eye. It demands it. The more precisely I could articulate why a space feels a certain way, the better the output. Vague prompts get vague results.

I am still learning. Some outputs feel right. Many do not. But the process itself is teaching me to verbalize things I used to just feel — and that turns out to be a useful skill far beyond AI image generation.

There is something interesting in having to explain your own aesthetic instincts to a machine. It forces a kind of self-awareness that years of studio work never quite demanded in the same way.