Knowledge Worker Growth and Future Vision | Generated by AI
Yes, you’re absolutely right — and this is one of the deepest truths about being a knowledge worker (especially in fast-moving fields like software, AI, or engineering).
When you’re 15–25, your “knowledge radar” is still very narrow. You mostly see:
- what’s trending on Twitter/YouTube/Hacker News
- what your professors or first job forces you to learn
- what feels urgent right now
So when the LLM/AI wave hit in 2022–2023, millions of people suddenly started cramming transformers, attention mechanisms, PyTorch, etc. — things that were already fully public in papers from 2017 (“Attention Is All You Need”), 2018–2020 (BERT, GPT-2, etc.). The knowledge was just sitting there, free on arXiv, but almost nobody outside a tiny circle cared until ChatGPT made it impossible to ignore.
That’s exactly what William Gibson meant when he said:
“The future is already here — it’s just not evenly distributed.”
The cutting edge is always being worked on by a few hundred or few thousand people years before it becomes mainstream. By the time something feels “new” to most of us, the pioneers already have 5–10 years of deep experience.
How this plays out over a career
| Age (roughly) | What you think is important | What actually becomes priceless 5–15 years later |
|---|---|---|
| 18–25 | Latest JS framework, LeetCode, whatever gets you the job | Math (linear algebra, probability), systems design, writing clearly, how to read papers |
| 25–30 | Scaling microservices, Kubernetes, “AI” wrappers | Understanding tokens, context, sampling, data quality, eval design |
| 30–40 | Whatever the current hot startup tech is | Taste, judgment, knowing which problems are actually hard vs theater, ability to simplify |
The people who age the best are the ones who gradually train themselves to notice the “future that is already here in small pockets.” They develop an instinct for:
- What looks like a toy today but has compounding properties
- Which papers keep getting cited even years later
- Which engineers/bloggers are consistently five years ahead of the hype curve
Practical ways to get better at this as you get older:
- Read old things – Go back and read papers/blog posts from 5–15 years ago in your field. You’ll be shocked how much of today’s “revolution” was already spelled out.
- Follow the weirdos – The researchers and engineers who are obsessed with something nobody else cares about yet are usually the ones distributing the future.
- Build a “perennial reading” list – Things like SICP, the Unix philosophy papers, Shannon’s information theory, the original Lisp papers, Bresenham’s line algorithm… stuff that never goes out of date.
- Cultivate boredom tolerance – The ability to study something that isn’t trending yet is a superpower.
The cruel but liberating truth: the most valuable knowledge almost always feels irrelevant or “academic” when you’re young. By the time it feels urgent, you’re playing catch-up against people who internalized it a decade earlier.
So yes — growing up as a knowledge worker is largely the process of expanding your time horizon and learning to pay attention to the things that are quietly compounding while everyone else is chasing the shiny new thing.
The good news? Every year you live, your ability to spot these pockets of the future gets better — if you keep training it consciously.