I am surrounded by fabulous podcasts, newsletters, magazines, blogs, tweets, Instagram posts, streaming services, and media libraries. With so many great offerings, there’s simply not enough time in the day to enjoy them all. To manage my media consumption, I follow the advice of Guardian author Oliver Burkeman, who recommends treating attention like money, as both are limited resources. When we devote our attention to one thing, it becomes unavailable for others. As such, we should be just as selective with our attention as we are with our money, not giving it to everyone who asks.

The concept is straightforward, but now AI chatbots like ChatGPT-4 are entering the market, seeking my undivided attention – and they’re getting it, currently even in abundance. If my attention continues to shift from traditional media offerings to chatbots, and if many others behave similarly, will media usage time for other platforms inevitably decrease?

One may wonder whether a chatbot even qualifies as a media offering. In the case of ChatGPT-4, I would say it does, at least subjectively. The chatbot continuously generates new content for me to read, capturing my attention. The fact that this content is based on probability calculations rather than editorial work is secondary in terms of media usage time. The source of the content is less important than the chatbot’s ability to engage my attention – or, as the saying goes: “It doesn’t matter whether a cat is black or white, as long as it catches mice.”

Does ChatGPT-4 also request my financial contribution? Indeed, I support the AI by paying a 23.80-dollar monthly subscription fee to OpenAI. By doing so, I adhere to Oliver Burkeman’s recommendation, allocating both my money and attention…

My programming skills are modest at best, but that’s turned out to be an advantage. I don’t think like a developer when creating my prompts. Command lines? Curly braces? Not my thing. I approach this field as a communicator: chat with the machine, clearly explain your intentions, and what you want it to do—maybe with some examples. Then you run the LLM and set it free. With a stroke of luck, the response turns golden. Essentially, that’s what ChatGPT-4 is all about.

I’m convinced that top-notch prompt design hinges on a healthy dose of imagination. That’s why I think the best prompt designers come from fields like creative writing, where out-of-the-box thinking is essential. Screenwriters and savvy journalists, for example, lead the pack.

Interestingly, programmers and developers aren’t as prominent in this field. Their approach, bluntly put, leans more towards thinking between the realms of 0 and 1. In natural language prompt engineering for LLMs, there are no clear commands, instructions, or even a distinct structure—the complete opposite of programming. Perhaps it’s their clever approach to the division of labor: “We coders build the Large Language Models, and you creatives get to play around with it.” After all, creating is often more enjoyable than simply using what others have built.

ChatGPT 3-5’s answers always sound very plausible. Even if the answer sometimes is complete nonsense at second glance. The AI writes grammatically perfect paragraphs, but it’s the depth and the reflection of the content that still isn’t there. And, as far as I know, AI does not understand irony. So, it is never funny on purpose, only by accident.

As a result, one could argue: ChatGPT is not ready for commercial scale. But this is just the first (public) version. The next version of ChatGPT is supposed to come out this year. People say it will be trained on some hundred times more data. And it will probably be much more sophisticated in terms of how many kinds of different things it can do. If that is the case, discussions about commercial use would immediately intensify.

AI saves time and increases labour productivity per person many times over. So AI has the potential to transform the entire global economy. How much faster will everyone be? Imagine integrating an AI like ChatGPT into the legal system, into medicine, into science, into finance. Into media, into art (already happened), into gaming. You name it. And this is probably happening all at the same time.

Sounds crazy? It is not. I think Yuval Harari mentioned in one of his fantastic books that all the world’s trade in the 15th century could be done today with four or five large container ships. In other words, a person today is perhaps a thousand times more productive on average than a hundred years ago. What will happen if, in the next few years, AI increases that productivity by another hundred times? To be honest, the idea of such acceleration makes my head spin.

This could be huge. A one-stop shop for corporate answers. Imagine a large language model like ChatGPT but for your own corporate data, the ultimate corporate data BFF*.

Imagine having all your org’s info at your fingertips, just a question away. The AI scours through all your PowerPoints, Cloud docs, Wikipedia-style knowledge bases and more and comes back with the perfect answer, summarizing exactly what you should do. No more sifting through endless pages, the AI gives you the gist, backed up with references so you can double-check that the data are adequate.

And the cherry on top? You don’t even have to open a single document – the AI summarizes everything for you. This would be really a whole new level, a reinvention of search.

*Best Friends Forever