Written by: haotian

I've seen many friends showcasing new AI tools, flaunting prompt techniques, and sharing dazzling workflows. But, I wonder if others feel the same: we, who think we are at the forefront, are actually just breathless followers trying to catch up. The development of AI is so rapid that even being immersed in it feels like we can't keep up with the pace:

1) If we were to define a "half-life" for learning AI skills, it would probably be measured in weeks.

I was still learning how to better harness Cursor when Claude Code came out and became all the rage. I was proud of the various prompt engineering techniques I had figured out, but once Skills emerged, I felt like those techniques were suddenly useless… In the past, learning a new technology could sustain you for three to five years; now, it might be outdated in just three to five months.

This is the harsh reality we face today: the so-called skills and techniques that we spend a lot of time researching may not keep up with a new version of AI iteration. But gradually, you'll realize that in the end, AI development will bring everyone to the same starting line. Who uses the tools uniquely, and whose prompts are more exquisite will all be leveled out.

What ultimately matters in the competition? "Curiosity and learning ability." While others still think AI tools have nothing to do with them, your repeated explorations, experiences, and trial-and-error have already put you a step ahead.

2) Using AI has shifted from being secretive to proudly showcasing it.

Additionally, I've observed a very interesting phenomenon: six months ago, when everyone was using AI to write code, they did so secretly, fearing being discovered that "your code is purely AI-generated." Now? My programmer friends are actively showcasing the projects they've done with AI, saying things like, "Look at this dashboard, check out this little app I had Claude finish in 10 minutes this morning," with pride in their tone.

This shift in mindset is crucial. In the past, our workplace value was based on "what skills I have," but now it's shifting to "what I can achieve with AI." Just like after the Industrial Revolution, no one would mock you for using machines instead of handmade production; AI is the same—it is a productivity tool.

Those who reject AI will eventually realize that it wasn't AI that eliminated them, but those who use AI. Speed itself is a barrier.

3) For those working with AI, explore the subjective initiative beyond the boundaries of AI.

Of course, this doesn't mean we should mindlessly rely on AI. Many times, AI may overstep its bounds, acting outside your intended scope and wasting a lot of valuable time. This forces us to harness AI with cognitive logic rather than being completely led by it.

It's important to understand that no matter how powerful AI is, it is still just a tool; it cannot provide you with the understanding of "what to do" and "why to do it." For example, you might just want AI to help you optimize a simple data query function, but it ends up unnecessarily restructuring your database architecture.

AI execution has significant issues with conditional triggers and rule definitions, which are the boundaries of our capabilities that we should expand. We need to think about what AI cannot do, especially within its path-dependent scope, and then leverage human subjectivity on top of that.

Ultimately, the way to harness AI is not to chase the speed of AI tool iterations but to genuinely contemplate the "limitations" of AI's thinking and execution. Then, we can use the innate wisdom of consciousness to fill in the gaps.

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