What Ordinary People Must Change First to Seize AI Opportunities

A lot of people say AI is the best chance for ordinary people to turn their lives around in this era. I totally agree, raising both hands in support.

I started working in the internet industry in 2005. That was when the internet was just transitioning from Web 1.0 to Web 2.0 (how many people still know what Web 2.0 is?). In 2009, I shifted to the mobile internet field.

As someone from a rural background, I definitely enjoyed the opportunities and benefits brought by mobile internet, and I had some gains too.

From my industry experience and intuition, the technological and industrial transformations brought by AI, as well as the opportunities it offers to ordinary people, are unmatched by any stage I’ve experienced before.

So, grasping AI opportunities, learning how to use and harness AI, isn’t an anxiety-inducing or hustle culture statement but a very sincere suggestion.

AI is a powerful tool, but the value and effect it brings can vary greatly depending on who’s using it. In my collaboration with AI, I found the following aspects limit its performance.

Your personality is AI’s personality

This is a very important limiting factor.

I’m actually a cautious, conservative person. In the non-AI era, in actual projects, I had many ideas, but when it came to realization, a lot of doubts and hesitations would pop up in my mind. I always wondered: Can this be done? Is that feasible? Will anybody really use this? During execution, there were always many entanglements.

When I use AI, those mental restrictions unconsciously limit my use of AI’s abilities. So many times, it’s not that AI can’t do it, but that I’m the one limiting AI’s performance as the idea generator and decision-maker.

After realizing this problem, I started consciously changing these issues in my personality and thinking. I intentionally made myself a bit more breakthrough-prone, more willing to try. Do whatever comes to mind, don’t set too many limits for yourself first. The cost of trial and error with AI in idea exploration and getting the most basic feedback is really low, at most wasting some tokens and a bit of time (really not much time at all).

Are you willing to spend money investing in AI tools?

I’ve been running a solo company for about eight weeks, and currently, I have basically no income. But I am now subscribed to Codex and Claude Code, each costing $100 a month, so I spend about $200 a month on AI tools, not counting investments in other tools.

Looks like a lot of money, right?

But if you’ve ever been part of any internet startup, or worked at an internet company, you’d know how much it would cost per month to hire employees with capabilities like Codex and Claude Code.

Just thinking about it that way, $200 a month is absolutely very cheap.

Although I haven’t made any money through AI yet, I believe it’s just a matter of time because I’ve already positioned myself in this industry’s trend. It’s like the industry saying, as long as you’re standing in the breeze, even a pig can fly.

So, if you want to achieve something in the AI field and accomplish some things, you need to be bold, invest in AI tools with a long-term perspective, and see it as an investment.

Your ability boundary is AI’s ability boundary

AI is almost omnipotent, but not really. Even though you don’t need to write any code or do any design by hand, in fact, your ability boundary is AI’s ability boundary.

This ability doesn’t necessarily mean just professional ability; it also includes your comprehensive abilities, or rather your vision and knowledge base.

Even though I’ve been in the design side of the internet industry for over 20 years, I know I have hard deficiencies in certain areas of design. For instance, my design can never reach the level of detail and refinement I expect. Also, my grasp of user needs is actually lacking a lot.

These hard deficiencies left over from the non-AI era still form big limitations when I use AI. AI seems to amplify my abilities, making me perform better in those areas with deficiencies than before; but if you compare my results with those produced by more capable designers using AI, I’ll still show a big gap.

Fortunately, in the AI era, you can learn quickly with AI, broaden your vision and knowledge. By constantly collaborating with AI, you can also quickly make up for and improve your lacking abilities. But the prerequisite is that you have a learning mentality, and secondly, that you know how to design a method or toolset to learn quickly using AI.

Are you willing to keep up with the latest industry information?

In the AI era, the cost of obtaining the latest firsthand information is very low. The simplest way is to subscribe to the official blogs of leading companies and follow the information of the most cutting-edge practitioners in this industry and field.

In the past, the barriers to reading and understanding these industry insights and related papers were very high for ordinary people, let alone putting them into practice.

But in the AI era, you can completely understand and learn quickly through AI. It helps you understand those profound information and related knowledge from a “novice” perspective very clearly.

If you don’t know where to start, I would suggest entering from two points: a company and a person. The content released by companies usually lets you see changes in models, products, APIs, Agents, open-source, computing power, and application cases; while the value of industry figures lies in translating many changes into judgments, methods, reminders, and practical experience.

For company information sources, I look at these 10 first:

OpenAI News: See ChatGPT, Codex, API, models, safety, and product application.
Anthropic News: See Claude, Claude Code, Agent, safety research, and enterprise applications.
Google DeepMind Blog: See Gemini, AI for Science, multi-modal, and cutting-edge research.
Meta AI Blog: See Llama, open-source models, multi-modal, and large-scale AI applications.
Microsoft AI: See Copilot, enterprise AI, AI workflows, and organizational practice cases.
NVIDIA AI Blog: See computing power, GPU, AI infrastructure, robotics, and physical AI.
Hugging Face Blog: See open-source models, datasets, toolchains, and developer community.
Mistral AI News: See European frontier models, open-source/open weight models, and enterprise deployment.
xAI News: See Grok, real-time information, Agents, and product updates.
Perplexity Hub: See AI search, research functions, information acquisition methods, and product changes.

Industry figures I prioritize following:

Sam Altman (OpenAI CEO): Personal Blog / X. Follow to see OpenAI’s product direction, AI infrastructure, and his views on the AGI economy.
Dario Amodei (Anthropic CEO and co-founder): Personal Site / X. Watch for Claude, safety, interpretability, and his thoughts on AI risks and societal impact.
Demis Hassabis (Google DeepMind CEO and co-founder): Google DeepMind / X. Look into Gemini, AI for Science, and how foundational research enters the real world.
Jensen Huang (NVIDIA Founder, President, and CEO): NVIDIA Official Page / LinkedIn. Follow developments in computing power, chips, AI factories, robotics, and industrial infrastructure.
Mira Murati (Thinking Machines Lab Founder, CEO, former OpenAI CTO): Thinking Machines Lab / X. Observe next-gen AI products, human-AI interaction, and the direction of the new AI Lab.
Andrej Karpathy (AI researcher, educator): Personal Site / Bear Blog / X / GitHub / YouTube. Learn how he explains LLM, Agent, and AI programming clearly.
Andrew Ng (DeepLearning.AI Founder, Managing Partner of AI Fund): Personal Site / X / LinkedIn / DeepLearning.AI. Focus on AI education, learning paths for ordinary people, and practical implementation methods.
Ethan Mollick (Wharton School Professor, researcher of AI, innovation, and organizations): One Useful Thing / X / Bluesky / Wharton Profile. Explore how AI integrates into work, education, organizations, and everyday life.
Simon Willison (Independent open-source developer, Datasette creator): Personal Blog / LLMs Tag / Mastodon / Bluesky / X. Consider model evaluation, tool use, Agent, security issues, and developer practices.
Aravind Srinivas (Perplexity co-founder, CEO): X / LinkedIn / Perplexity Hub. Investigate AI search, answer engines, and next-gen information retrieval.

Of course, I’m not saying everyone needs to scan through all this info every day. A more practical approach is to bookmark these resources, then set aside fixed time each week to let AI summarize recent changes for you. Ask it how these changes relate to your work, projects, and life.

Don’t just stay at the information-gathering stage. Also, ask yourself one more question: How can I apply this in my current work? Similarly, AI can quickly absorb these cutting-edge insights and methods. It’ll do the heavy lifting for you and implement the content in your current projects.

In this era, the best information and resources are at your fingertips. The only thing limiting you and AI is your willingness.

Are you willing to create things?

For ordinary people, or those in non-AI sectors (like product managers, designers, developers, testers, etc.), it’s crucial to correct a mindset:

In the AI era, don’t just stick to simple chats with AI (don’t just use AI as a quick search engine). You can absolutely create something yourself to solve real-life problems.

When you observe your life, what are the tasks you spend time on repeatedly? Or, what current tools fail to meet your needs? Or maybe your needs are unique and no tools yet address your issues?

Great, that’s when you can make something for yourself.

You could say, when you start to make a tool for yourself, you’re already more competitive in the AI era than over 90% of your industry.

Previously, NVIDIA’s Huang (Jensen Huang) was asked: Is AI taking away people’s jobs? He replied: AI won’t take away human jobs. In the future, those who can use AI will take the jobs from those who can’t.

Although I’ve discussed five aspects, at the end of the day, it’s still about people. A person’s awareness, thinking, quality, and vision will affect their ability to seize opportunities in the AI era, and whether their skills continue to grow. So, for ordinary people, the most crucial thing in capturing the great opportunities of the AI era is whether you’re willing to change and update yourself.