There may not be much time left for white-collar workers.

It’s not about spreading anxiety, just sharing personal thoughts!
When a company hires an employee, they’re not primarily interested in you as an individual, but rather in your skills, time, and the value you can create for the company within that time—essentially, “value exchange.”
In November 2022, ChatGPT suddenly emerged, and for the first time, humans experienced the shock of natural conversation with AI.
After ChatGPT, what do we truly need?
We found the answer, but we stopped at the chat window.
You ask AI to write a market research report, then manually copy it into a PowerPoint presentation.
You ask AI to generate code, then switch between three software programs to deploy it.
You ask AI to analyze data, then open Excel to reorganize the format.
Conversation is the starting point, not the end, so people have developed a stronger demand:
It’s not “Tell me how to do it,” but “Help me get this done.”

This is the inevitable birth of Clawdbot.
We are no longer satisfied with a “talking encyclopedia”; what we need is a super intelligent butler:
Able to understand, coordinate, execute, and close the loop.
Imagine this workflow:
You tell Clawdbot, “Help me prepare a plan for Mr. Zhang tomorrow, including Q3 sales data, competitor analysis, and three pricing strategies, and send it to my email by 8 PM, CC Manager Li.”
Clawdbot won’t just give you a paragraph of text.
It will automatically open the sales database to extract Q3 data → call the analysis AI to generate insights → trigger the competitor monitoring tool to fetch the latest updates → activate the strategy generation module to output the plan → format it into a PDF → schedule an email to send → mark a follow-up reminder in your calendar.
What you get is a result, not just an answer.

The time left for traditional white-collar workers is truly limited.
Anthropic CEO Dario Amodei warned: in the next 1-5 years, 50% of entry-level white-collar jobs will disappear.
It’s not that the white-collar identity itself will vanish, but that the “value logic” of traditional white-collar work is changing: jobs that once relied on “sitting in the office, knowing how to use office software, and understanding basic professional processes” are increasingly replaceable; those who can stay are the ones with skills AI cannot do—making decisions, empathizing, industry expertise, resource integration, and solving complex problems. Possessing such skills will inevitably be limited to a small group.
The future doesn’t belong to those who copy and paste from chat windows, but to those who enable AI agents to collaborate seamlessly, who can harness AI to complete complex real-world tasks, and who are defining new productivity.
Clawdbot is not just another AI tool; it’s an inevitable evolution after ChatGPT—a crucial leap from “getting answers” to “completing work.”
The time left for white-collar workers may truly be limited.
But perhaps the time for AI commanders has only just begun.

And we should reflect on what remains unchanged amid these changes—that is the true “moat” of the workplace. After all, the core competitiveness in the workplace has never been “how many nights you stayed up” or “how many tasks you completed,” but rather “how much value you created within limited time.”