What’s Left When Everything Is Commoditized?
As a simple mind experiment, let’s plug in our brains and visualize an extreme case of AI disruption.
In this not-so-impossible future, everything we know today is getting commoditized, reduced to fixed computation costs.
This is already happening with:
Repetitive tasks (data entry, administrative)
Well-documented tasks (monthly reports, taxes)
Routine software development (websites, single-page applications, data analysis)
Early design work (product, visual, conceptual)
Light research and analysis
But we can imagine this trend continuing, with many advanced tasks semi- or fully automated. In a few short years, it’s likely that 90% of the computer work we do today on a daily basis has been taken on by the machine.
If one thing is certain, it is that humans are notoriously good at leveraging excess creativity (surplus of time → increased capacity for creative thinking), and this won’t change with the introduction of mainstream AI. So what’s next?
Context, Context, Context!
The “prompt engineers” of today are the “context engineers” of tomorrow. Humans will take a more product-management type role controlling and adjusting the flow of tasks.
I think “context engineering” will become the new “prompt engineering”. Context management is an ongoing evaluation of progress towards both high and low level goals. While next-gen AI will surely be able to handle simple context, human input and alignment towards proper contextual nuance will be essential. The question of “where should we spend our time/resources” often relies on intuition, on-going reflection, a mission or raison d'être, and an understanding of time management. These human strengths will endure for quite some time.
The Real World
And then there’s the physical world.
A foreign concept to many of us that live in the reflections of our laptops, the real world remains very real and difficult to navigate. Interfacing between the digital and physical worlds is complex and requires advanced edge case management (like that time it took 10 trips to home depot to fix the garage door despite having tried to think ahead at every step).
Almost everything involving manipulating or interfacing with the real world will need humans, at least until the humanoids extend a helping hand.
And speaking of humanoids, we can extend the above thought experiment to robotics as well. At some point in the future we will have a similar wave in robotics to that of LLMs today, where we find that robots can suddenly do almost every simple task that humans can.
What then becomes valuable is guiding the robots and managing their tasks and context.
Networking, Authenticity (Humanness)
This is a big one in my opinion and the most under-explored.
Value increases with scarcity, and amid a new world of machine-generated content and guidance, there is less of “that which is human”.
Let’s take a simple example: you’re hiring for a new role at your company. All of the job candidates are machine-polished on fine digital paper, and are even prompted on the video call interview with on-screen reminders and suggested responses.
What do we look for to choose a candidate? We might look for personality, signs of abstract thinking, spontaneity, and passion. Or in other words, humanness. It may even be the case some day (soon?) that video interviews are no longer enough and we must get together in person to measure these characteristics.
So here we may have personality valued much higher than it is today (witty thinking, passion, humor).
And where do we develop personality? In a large part from other humans. Through networking, authenticity, shared creative experience, and teamwork.
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