For decades, progress was incremental — put in a few more years, gain a little more edge; experience was like interest, compounding every year. What AI brings is discontinuity: not faster, but a different road entirely. You’re still flooring the accelerator on the old road when the navigation tells you — no road ahead.

On the fault line, there are no senior drivers.

Seniority is devaluing.

AI’s sharpest move isn’t replacing people — it’s making “experience”, the hard currency of the old world, suddenly worthless. The defining trait of large models happens to flatten industry experience: the industry knowledge, business details, judgment and intuition that once took a newcomer ten years to accumulate can now be retrieved in seconds, at 70–80% fidelity.

And so the most counter-intuitive scene unfolds: young people with zero industry experience are breaking out faster than veterans. They carry no baggage — they simply work the “AI-native” way. Meanwhile, those clinging to the old playbook find their experience is no longer a moat, but an anchor dragging them down.

The thinner your résumé, the faster you run. That’s not a joke — it’s the new rules having a laugh.

But don’t read this upheaval as a war of “youth vs. old guard.”

What truly separates people is never age — it’s mindset. Stay on the leading edge, stay open-minded, and you remain young — the number on your ID is just a footnote the world adds.

And the ones with the best odds are never the youth with nothing, but the combination of capital + experience + mindset: you carry no baggage, yet you have tools, resources, and a grasp of how your industry works below the surface. AI-native work can do a lot, but it still can’t solve the concrete problems of the real economy — supply chains, compliance, real assets. That unglamorous work still needs people who know the domain.

There’s one precondition: stay open-minded, always. Don’t use your experience as an excuse to reject the new rules — that’s turning your moat into a wall around yourself.

The second shock AI delivers is a total restructuring of organizations.

Too many jobs no longer exist. That’s not hyperbole — it’s a list being written right now. Old structures were built around old jobs; once the jobs vanish, the structure has to be rebuilt.

The deeper change is a reversal in how collaboration works: we used to worship “teamwork”, yet a team’s output was always held back by its least-aligned member. Today, when requirements are clear enough, the pairing of human and AI is the smoothest collaboration there is. In many steps of the work, “human-to-human” collaboration has nearly disappeared — because its inefficiency came precisely from human unpredictability.

The organization of the future doesn’t bolt AI on as a tool — it redesigns itself around what AI can do: what AI handles directly, what gets done in human-AI collaboration, and which boundaries must stay with humans. Only such AI-native organizations can grow the more complex, AI-driven, Web3-native industry applications.

However the world changes, for each of us it comes down to a few concrete things:

• Stay deeply in sync; communicate proactively — AI makes information flow faster, but alignment matters more than ever. A muddled mind is a thing even AI can’t help.
• Get genuinely good at AI tools — this isn’t a bonus point; it’s a basic skill.
• Build a full-picture view — don’t stay stuck in your corner of the back end. Understand the overall business logic of the product; only then does end-to-end delivery stop being your weak spot.
• Align early — project initiation, requirement definition, business value: these are exactly the stages to think through first. AI executes; humans must decide the direction.
• Clear thinking, solid execution — with AI in hand, no goal is beyond reach.

What AI changes is how we work: incremental becomes discontinuous, collaboration becomes human-AI, organizations become native. What it doesn’t change is why we work: understanding problems, judging value, staying true to direction — and above all, a permanently open mind.

Tools will be replaced, generation after generation. But the people who can think things through, explain them clearly, and build them — they will always have a place.