# In the Age of AI, Which Part of Myself Do I Want to Amplify? Willdom Lee · 2026-10-25 [HTML](https://willdomlee.com/en/articles/amplify-yourself) · en > Today, Zhang Xue, the founder of Zhang Xue Motorcycles, returned to his hometown in Hunan, completed a challenge he had failed to finish 17 years ago, and set a Guinness World Record. As someone from the same province, also born in the 1980s, I have always found his story moving. Back then, his abilities, circumstances, and resources could not yet support that dream. He spent 17 years gradually assembling what he needed, with failures along the way. Today, he came back and did it. It brought me back to a question I have been turning over lately: **What if the very process of assembling those abilities is changing?** I feel increasingly certain that the capabilities of the world's best AI systems already far exceed most people's understanding of them. Many people still use AI to search for information, write articles, make slides, or solve a specific problem. Those are valuable uses, but stopping there means missing a much bigger opportunity. Today's leading AI agents can write programs, call tools, operate software, and, under the right conditions, plan and execute complex tasks autonomously. In the past, a project spanning several disciplines often required a team working for weeks or months. Now, with top-tier AI, one person has a chance to carry out a substantial portion of that work independently. **What is changing is not just our efficiency, but the limits of what one person can accomplish.** ## 01 | AI has changed. Have our ways of working kept up? I see a common pattern: people start using AI but continue to organize their work exactly as before. A problem comes up, so they ask AI. They copy the answer. Then another problem comes up, and they ask again. The human still drives every step. AI is simply a smarter tool. But agents offer much more than that. We can let them work continuously toward a goal: carrying out tasks, checking results, spotting problems, adjusting their approach, and asking for human intervention when necessary. People remain responsible for the goals, the rules, and accepting the results. **The key is to let the agent's heartbeat run on its own, rather than waiting for a person to wake it up every time.** ![](https://willdomlee.com/assets/a/amplify-yourself/01.webp) Recently, we tried using AI to change how we follow up with customers. Previously, the person conducting the call listened and took notes at the same time. It was inefficient, details could be missed, and the record depended partly on that person's interpretation. On one occasion, we transcribed more than a hundred minutes of follow-up recordings using a locally deployed Whisper model, then asked AI to extract problems, criticism, and suggestions for improvement. Each important comment linked directly to the original recording, so the team could replay and verify it at any time and act on customer feedback faster and more accurately. But that was only the first step. The issues were then handed to managers, who used AI to keep following up and drive organizational improvements. That was when the agent's heartbeat truly began. It made me realize that the valuable change was not producing a customer satisfaction report faster. It was bringing customers' actual voices more fully into the company's improvement process. Of course, AI's ability to identify and track problems does not mean those problems solve themselves. People still have to exercise judgment, make decisions, and take responsibility. ![](https://willdomlee.com/assets/a/amplify-yourself/02.webp) **Increasingly, what limits AI's value is not what the model can do, but whether we can redesign the work and make use of the results it produces.** ## 02 | AI-empowered individuals are emerging. Are organizations ready? I believe the idea of an exceptionally capable individual is no longer just a concept. Someone with professional experience, a strong understanding of the business, and skill in using AI is gaining capabilities that once required a team. They can do more than complete additional tasks themselves. They can design workflows, coordinate multiple agents, and consistently deliver more complex results. More significantly, these capabilities can accumulate. Business knowledge, working rules, skills, past experience, and feedback all become the foundation for the next task. A person's value will depend less on how many tasks they personally complete, and more on the capabilities they can coordinate and the value they can keep creating. ![](https://willdomlee.com/assets/a/amplify-yourself/03.webp) But there is a tension here that is easily overlooked. Suppose an employee takes the initiative to automate their work and becomes dramatically more efficient. What happens next? Do they get more meaningful work and room to grow, or do they face a threat to their job and an even longer task list? **If an organization cannot answer that question, why would employees volunteer to eliminate their own work?** This is not simply a matter of employees' understanding of AI. It is a management issue. Organizations need to think through at least a few questions: - How will the gains from greater efficiency be shared? Will they all turn into more tasks, or will some of the benefit go back to employees? - What will the freed-up time be used for? More repetitive work, or work that calls for greater judgment and creativity? - Will people who embrace AI be rewarded, or simply given more to do? Without clear answers, smart people will often choose to use AI quietly. Their personal efficiency improves, but the organization does not become stronger. **So instead of asking, “Why aren't employees using AI?”, managers should first ask, “What do people who use AI gain from working here?”** **Individuals can grow more capable through their own efforts, but exceptional teams do not emerge automatically.** They need organizations to provide room, resources, and incentives. I even think that some companies' future competitiveness will depend less on how many people they employ and more on whether they can help talented people and AI work together effectively. That change has already begun. It is not a distant future. ## 03 | When our capabilities expand, what do we actually want to do? At this point in the discussion, I find myself thinking that technology is not the most important question. Once someone can call on powerful agents and hand over much of the execution, where will they choose to put their own time and energy? Into strengthening their professional abilities?\ Exploring their interests more deeply?\ Or returning to dreams they abandoned because they lacked the skills, time, or resources? If we use AI only to make ourselves busier, without reconsidering what we truly want to do, we gain efficiency but miss a much larger opportunity. It makes me think of **building dreams**. We used to decide how big we could dream based on the skills, resources, and teams we already had. Perhaps now we can try reversing that order. First, think seriously about what we want to create. Then, with AI continuing to evolve, gradually build the capabilities needed to make it happen. Like an architect. Start with a blueprint, design the structure, build it brick by brick, and keep refining it until it actually works. Today it might be one skill or one agent. Tomorrow it might be a system that works continuously, or even an AI team you have assembled yourself. Of course, not everyone needs to build a team, start a company, or pursue a grand ambition. But at the very least, we no longer need to dismiss today's possibilities so readily because of yesterday's limits. **AI changes not only how efficiently we pursue our dreams, but how big we dare to dream.** Dreams can be grand, but bringing them to life still takes focus, concentration, and daily persistence. AI can shorten the time needed to assemble the capabilities; it cannot replace that persistence. That is precisely why Zhang Xue's story speaks to so many people. ## 04 | Stop watching and start doing If you already have reliable access to top-tier AI, do not settle for asking it a few questions now and then. If you are close to that point but have not seriously explored how to use it, or are still hesitating over whether to pay, I suggest running the numbers again. For people who can afford it and have a real need, **tens or even hundreds of dollars a month can be more than a subscription fee: it can be a chance to rethink the limits of what you can do.** Of course, paying does not create value by itself. Money is not the only barrier; time, access, and the effort of learning matter too. What counts is whether you keep putting those capabilities to use. Then again, if you sign up for a hundred-dollar plan, you may feel obliged to use it a few times—and perhaps that gets the flywheel turning. Half a joke, half serious. If you do not know where to start, try this: Choose something you repeat every week that does not require much of your own decision-making, and let AI do it from beginning to end. You have just three responsibilities: explain the goal, set the rules, and check the results. Once it works, find a way to have it run regularly on its own. The first attempt may be rough. But your understanding will move from “I've heard it can do this” to “I know how far it can get.” Do not judge what today's strongest AI can do solely from other people's demonstrations. **Use it yourself. Use it seriously. Keep using it.** Then take some time to ask yourself: As more and more work can be handed to AI, where do I want to spend my time? Are the things I once gave up because I lacked the ability worth trying again? And the most important question: Which part of myself do I really want to amplify? --- Originally published in Chinese on WeChat, 南山独唱团. [Read the original](https://mp.weixin.qq.com/s/ZGqVq4Q_uxH32HVPidOChw).