By Sergey Ryzhavin, director of B2COPY, a money management platform for brokers and financial institutions.
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The Shortcut Society
We live in an age of shortcuts. At first glance, tools that save time, reduce stress, and human errors look like progress and seemingly make life easier. But beneath the convenience lies a quiet revolution in how we remember, learn, and even think. Let me bring here a few examples of the ongoing “shortcut economy” changes:
Memory shortcuts arrived with the advent of Google, Wikipedia, and the notes app on our smartphones. They helped us remember less data and numbers, because anything could now be displayed instantly by filling out a simple search prompt. The unintended consequence is the slow erosion of long‑term memory and the weakening of our ability to connect facts into coherent narratives.
Skill shortcuts followed. GPS apparently replaced orientation and recognizing paper maps, calculators replaced mental math, and autocorrect replaced spelling. Although these tools are truly invaluable, they also happen to fail occasionally. True, this occurs very rarely, but one rotten apple spoils the barrel, so to speak.
Thinking shortcuts are the newest frontier. AI assistants and large language models promise instant analysis, structure, and ideas. Yet the more we rely on them, the harder it becomes to face a blank page ourselves. Depth gives way to surface, originality to repetition.
Action shortcuts complete the cycle. Automation, delegation, and AI agents remove the need to perform tasks at all. But when the process itself vanishes, so does our ability to judge the quality of the result.
The Shortcut Economy doesn’t ask whether we like it. It simply exists. But the real fundamental disruptor here is AI, which begins to reshape the very capacity to structure thought.
The question is not whether shortcuts make life easier — they do. The question is what happens when the very skills that define human autonomy aren’t continuously practiced. Progress has always come with trade‑offs. The difference now is that the trade‑offs are no longer technical but gradually more and more existential.
We notice it in small ways at first. General writing becomes easier, faster, and less deliberate. Decisions are increasingly, but quietly, aided by various OTC algorithms rather than implemented step by step internally, supporting previously inseparable due diligence procedures. Tasks that once demanded hours of focus are now outsourced to tools that shoot out results in seconds.
In our book club, while discussing Brian Christian’s The Alignment Problem, we raised the question: Does AI cause a degradation of skills in those who use it? Personally, this issue worries me, as someone who actively relies on AI in my work with design, code, and content. That’s why I find it important to pause and reflect from time to time: how is the workflow being reshaped, and how is the brain’s responsiveness to different tasks changing?
It bears pointing out that shortcuts by themselves are hardly new: assistants that you can delegate tasks to have always existed. But previously, they were only available to those who could afford them. Executives, large organizations, rich people — parties with the means to hire entire teams to think, advise, and execute decisions on their behalf.
Now, technological advancements have brought access to shortcuts to a whole new level, making it affordable to practically anyone. Help from AI models is cheap, instant, and readily available, regardless of what your budget looks like.
Welcome to the Shortcut Economy.
From Choice to Necessity
Humans have always looked for shortcuts. Again, that part isn’t new. What’s new is that shortcuts are no longer optional.
In a world of overwhelming information density, shrinking attention spans, and constant cognitive interruption, prolonged skill acquisition is becoming structurally incompatible with everyday life. Over the past decade, the average attention span on a single task has dropped from roughly three minutes to under a minute. It’s what we call adaptation.
These days, if we need a draft written, some research summarized, or a fresh idea, language models can handle it in seconds. It’s hard to justify doing everything by hand when software almost instantly offers choices faster than most of us could generate even a simple idea. And honestly, after a long day, few people have the energy to push back against that convenience.
This is an ongoing conspicuous trend in itself. For example, no-code and low-code platforms make building software much simpler by hiding the complex parts, so future developers don’t have to spend years learning the technical details. When it comes to launching a website or automating a task, these tools really do speed things up. Still, while they let you get more done, they don’t necessarily help you understand how everything works under the surface.
That same trade-off — more output, less hands-on learning — pops up in all sorts of jobs now, from creating presentations to analyzing big data.
The Shrinking Return on Mastery
There was a time when learning something difficult carried a clear promise: invest the years, endure the frustration, and competence would pay off. That equation is breaking down.
Take any genuinely complex skill: trading, programming, engineering, medicine, even writing — the path to proficiency hasn’t become shorter in any of them. If anything, the knowledge base has expanded. But the environment around the learner has become noisier, more distracting, and more competitive.
Spending five to seven years becoming a competent discretionary trader once made sense. Today, that same individual is competing not only with other human professionals, but with automated strategies, institutional infrastructure, and an information firehose that erodes focus before it can compound.
Why Trading Exposes the Shift So Clearly
Trading isn’t just technical, it’s psychological. It demands sustained attention, emotional regulation, probabilistic thinking, and the ability to tolerate uncertainty for long periods of time. In other words, it requires exactly the kind of human capacities that the Shortcut Economy is steadily eroding.
For decades, retail traders were told that with enough discipline, education, and screen time, they could compete. Some did. Many didn’t. Today, the odds have shifted further since attention is becoming more and more fragmented.
In that context, it’s hardly surprising that copy trading, managed accounts, and other delegation models are gaining traction. They aren’t a rejection of learning. They’re an admission that learning everything the hard way is no longer viable for most participants.
This isn’t about cheating the system. It is the system adapting to human limits.
The Emotional Resistance
There’s understandable discomfort around this shift.
We like to believe that effort equals virtue, that shortcuts dilute authenticity, that outsourcing expertise diminishes agency. And in some cases, that’s true. Blind delegation carries risks. Dependency always does.
But there’s also a romanticism to the idea of “doing it the hard way” that ignores economic reality. Mastery still exists. It just belongs to fewer people — and those people increasingly operate as platforms rather than individuals.
The uncomfortable truth is that the Shortcut Economy doesn’t eliminate expertise. It concentrates it.
And concentration changes everything.
Operating Inside Reality
It’s tempting to frame all of this as a decline. A loss of depth. A degradation of human capability. And that narrative may be emotionally satisfying, but it misses the point.
Humans are adapting to an environment where attention is scarce, complexity is overwhelming, and time is the most constrained resource of all. Against this backdrop, insisting that everyone should still pursue deep mastery across multiple domains isn’t empowering — it’s exclusionary.
The real question isn’t whether shortcuts are good or bad. It’s whether we understand the trade-offs they impose, and whether we design systems that acknowledge human limits rather than pretending they don’t exist.
Trading, investing, and decision-making more broadly are already being reshaped by this logic. Not because people want instant results, but because without them, participation itself becomes unsustainable.
