Where Does the Core Competitiveness of Talent Lie in the AI Era?
As AI grows increasingly powerful, many people share the same underlying anxiety: what should one learn to avoid being left behind by the times?
Despite dedicating effort to mastering prompts, stockpiling multiple AI tools, or learning AI-powered drawing and video editing, individuals often remain anxious due to the rapid iteration of these tools.
What’s the Problem?
At the Feishu AI Masterclass Conference, insights from several frontline AI practitioners provided an answer. In the AI era, certain capabilities are becoming increasingly scarce.
Knowing How to "Leave Traces" Is More Valuable Than Writing Prompts
👉 AI can only assist you effectively if it can access and understand your work.
Many people invest significant time refining prompts, focusing on phrasing, structure, or keywords. During a conversation with Zhang Zala, Vivian, founder of Yihao AI Club and Forward 4 MCN, illustrated this point: “An AI without traces of your work is like a newly hired employee; an AI with traces is like a long-time trusted partner who has worked alongside you for years.”
This insight is critical because it overturns conventional wisdom.
In the past, higher professional barriers meant greater irreplaceability—this was because expertise was built upon the scarcity of execution: the better you were at something, the more valuable you became. However, AI continuously reduces the cost of execution. When execution is no longer scarce, mere ability to execute rapidly loses value.
“Being good at using AI will soon become a basic skill, as common as knowing how to use a computer—and thus no longer a competitive advantage,” said Vivian. What truly becomes scarce is the depth of AI’s understanding of you: your work background, business logic, and decision-making criteria. Can AI read, remember, and apply this knowledge?
Vivian noted that intelligent agents within Feishu function precisely this way. They are not chat windows that require you to re-explain your needs every time—documents, meetings, group chats, and spreadsheets all exist within Feishu, allowing context to accumulate automatically. AI sees your complete work environment, not just blank instructions.
For those skilled at leaving traces, AI grows stronger with each use; for those who aren’t, every interaction starts from zero. This is compound interest in the AI era.
The Ability to Deliver Results Is More Valuable Than Knowing Tools
👉 The key differentiator among AI talents lies in output, not tools.
Beginners often focus on “learning to use tools”: which products they’ve tried, how many workflows they’ve mastered.
During the panel discussion, Zhang Zala and Wang Daxian emphasized that the ultimate goal of learning and using AI is solving real problems—not mastering the tools themselves.
Tools are means to an end; results are the end. If your focus remains on tools, you’ll be trapped in endless updates. Only by centering on problem-solving can you find direction.
AI should seamlessly integrate into every aspect of work, rather than existing as a separate window requiring manual input and copying back results. Documents, meetings, chats, and spreadsheets all reside within Feishu. AI reads the context directly, understands what you're doing, and acts immediately.
Wang Daxian believes talent in the AI era should be evaluated based on actual deliverables, not tool checklists. For internal efficiency tools, measure improvements in productivity and departmental adoption. For external products, assess exposure, engagement, and revenue generated.
Knowing which tools to use isn’t particularly valuable; knowing how to use tools to solve specific problems is what truly matters.
Judgment Is More Valuable Than Generative Power
👉 Generation belongs to AI; judgment belongs to humans. The process of reviewing and revising—that is what truly belongs to you.
Many people use AI like this: issue one command, get a finished version; continue the conversation, receive another entirely new version. Each time starting from scratch, re-explaining requirements, until eventually the result may even be worse than writing it yourself.
The issue isn’t with AI—it’s that you’ve skipped the most crucial step: personally reviewing and verifying the output.
Raymond, host of Mossfire, shared his observation: “I often feel I’m the bottleneck for AI.” AI can help him read more and see more, but true comprehension and judgment cannot be replaced by AI.
Using AI in work is no different. One-click generation may seem time-saving, but if humans don’t participate in refinement, judgment isn’t developed. Going through ten rounds of revision is more valuable than directly accepting the tenth version.
Feishu Docs serves exactly as such a “shared workspace.”
When writing, select a passage, @Feishu AI Agent, and ask it to polish, expand, or condense the text—then apply the revised content directly into the main body. This isn’t about letting AI write for you, but collaborating with AI as co-authors.
More importantly, the text itself becomes context. When seeking AI assistance again, there’s no need to start from zero guessing your style preferences. Open the document, and it already knows.
The faster AI generates, the scarcer human judgment becomes.
So, in the AI era, what kind of talent is truly valuable?
Talent that excels at preserving context—enabling AI to understand them better over time, turning every collaboration into a foundation for the next.
Talent that delivers results—treating tools as means, problems as goals, and always taking ownership of outcomes.
Talent with strong judgment—unimpressed by one-click generation, building personal standards through repeated refinement with AI.
These three capabilities share one trait: they are compounding skills—each use strengthens them further, and their value grows with accumulation.
Tools change, and so does the way we work. The ultimate question remains: are you ready to embrace new capabilities to meet the new era?