How to Cultivate "True AI Talent" to Survive the AI Era: Step Out of the Lab and Spark Explosive Growth with the X/Y-Axis Loop!

Hello there! I’m an author who has been spearheading internal AI talent development since 2023. Just recently, I’ve successfully produced a handful of standout, "this-is-the-one" AI professionals within my company.

Lately, the internet and industry circles have been flooded with voices shouting: "To be true AI talent, you must understand the Transformer architecture inside out!" or "You must be fluent in the inner workings of LLMs and Vector Databases!"

…Let me be blunt. Corporations are not looking for "researchers."

Chasing the bleeding edge of pure technology is a wonderful pursuit in itself, and I personally conduct my own research and investigations. However, in the trenches of actual business, driving forward with such a technology-centric stance will, with a high probability, lead you straight down the wrong rabbit hole.

So, who is the "AI talent" that we truly need in the upcoming AI/AGI era? And how can we foster their growth at breakneck speed? Today, I’ll share my "Ultra-Practical AI Talent Development Theory"—forged through three years of getting my hands dirty on the front lines—complete with our proprietary framework and raw, unfiltered failure stories.

First of All, Aren't You Defining "AI Talent" All Wrong?

The definition of the AI talent we should aim for is remarkably simple:

"Someone who can master new services (tools and software) brought about by AI and Generative AI faster than anyone else, drastically overhaul traditional thinking processes, and overwhelmingly boost business efficiency."

AI today is less of a pure technology and more of an "ultra-powerful tool."

If You Had to Buy Supplies from a Market 20 Kilometers Away, What Vehicle Would You Choose?

Let’s use an analogy of a team running a restaurant. Suppose you have to go to a wholesale market 20 kilometers away from your shop to fetch ingredients.

• The person who runs on foot: Because there is a limit to how much they can carry back, their menu will be limited to ramen or fried rice using "only the flour and eggs light enough to carry on their back." Diversifying the menu is impossible.
• The person who goes by bicycle: It gets a bit easier, and the capacity increases slightly.
• The person who goes by car: They can load up a massive amount of ingredients and return at overwhelming speed. This creates ample time to spare for prep work and menu development, allowing them to offer luxurious and rich menus like steaks and premium meat dishes. As a result, the scale and revenue of the restaurant skyrocket to an entirely different league.

When the tools change, everything about the process shifts—from how time is spent and the order of operations, to the final results obtained.

The exact same thing is happening with AI. Take the programming front line as an example: the era of simply writing code is over. What is overwhelmingly vital in this day and age is the ability to look at a sea of AI tools, identify the highest-quality product that "best fits your company’s business needs (and human nature) with the highest cost-performance," and master it.

Furthermore, we must not mistake "AI" here as something strictly meant for programming (AI ≠ Coding). The domains of AI that we need to catch up on and combine are now showing unbelievable diversity:

• Accelerating creative output via Image, Video, and Music Generation AI.
• AI Agent Systems (Agent System / Harness Engineering) that autonomously drive and advance processes.
• Optimizing security and cost using local Large Language Models (such as Gemma 4 or Qwen).
• Applying new AI models (like GPT Realtime 2) that can analyze and converse directly from voice to voice with ultra-low latency, without text intervention.

The perspective of understanding the characteristics of these diverse "weapons" and mapping them onto the actual business field is absolutely indispensable.

💡 The Top 2 Tools I am Seriously Watching as of May 2026:

* Coding Domain: "Codex" ： Its design fits human focus spans and actual workflow cycles surprisingly well. It is built with an incredible sense of "human touch," and it is currently my highest recommendation for the front lines.

* Business Thinking Expansion Domain: "TapNow"： A cutting-edge AI tool currently drawing massive attention, capable of completely overturning conventional wisdom and instantly cracking open fresh business thinking circuits.

Conversely, "vanity engineers" who don't even understand basic computer principles or the CLI (Command Line Interface) but get swayed by internet hype—jumping into things purely for aesthetics ("I heard Claude Code is the next big thing!"), throwing millions down the drain, and accidentally blowing up databases—are just "arrogant laboratory dwellers." In business, they bring a hundred disadvantages and not a single benefit.

The "X-Axis / Y-Axis" Framework for Explosive Short-Term Growth

So, how do we practically elevate our staff's capabilities? I propose the following "Growth Cycle via the X/Y-Axis Matrix."

• 【X-Axis】 "What can I do?" — The axis of self-possibility and hypotheses.
• 【Y-Axis】 "What can be achieved using AI?" — The axis of knowledge and exploration.

💡 The Mechanism of the Infinite Growth Loop

1. Initial State: First, within the scope of your current cognitive boundaries (X-axis), you set a challenge ("Let's try this") and put it into practice using AI.
2. Expansion of the Y-Axis: In the process of practicing, you gain a sudden realization: "Oh wow, by using AI, I can achieve things far beyond my original expectations!" Your AI knowledge base (Y-axis) shoots upward.
3. Evolution of the X-Axis: As the Y-axis rises, your next hypothesis moves forward: "Now that I have this AI knowledge, can I expand the business possibilities (X-axis) visible to the naked eye in the real world even further?"
4. Continuation of the Loop: Based on the new hypothesis, you explore and research yet another AI tool, which expands the Y-axis once again.

By continuously spinning this cycle of the X-axis (hypothesis/practice) and Y-axis (exploration/knowledge), the "area" of the graph keeps expanding, and the capability of the individual—and ultimately the entire organization—undergoes an explosive expansion.

⚠️ Warning: Don’t Fall into the Programming Trap Those who view AI merely as a "debugging assistant for coding" will stay stuck pacing back and forth on a tiny step along the X-axis, failing to trigger a Y-axis breakthrough for the rest of their lives. AI is a means, never the end.

The "Blogger Daily Report × Early Morning Cross-Learning" System to Rally the Organization

Geniuses who learn spontaneously will grow on their own anyway, but as a corporation, we cannot afford to leave everyone else behind. That is why I introduced a "Blogger (blog-style reporting) System" to push motivation to its absolute limit.

The system workflow is as follows:

1. 【Daily Operations】 Write insights and takeaways gained from using AI in a "Daily Report (Blog format)."
2. 【Next Morning Meeting】 Led by the manager, team members share and introduce the content to one another.
3. 【Peer Review】 Members cast mutual votes ("Likes") on each other's insights.
4. 【Public Distribution】 Outstanding articles are published externally on social media, boosting the individual's professional presence!

Why Does This System Work?

The biggest benefit is that it triggers "Cross-Learning."

When Player A writes a blog post about a Y-axis breakthrough ("Look at what I managed to do with AI"), Player B can absorb that knowledge into their own brain without having to directly experience it themselves. Consequently, Player B’s X-axis (the scope of their hypotheses) expands starting the very next day, leading Player B to break through a different Y-axis limit and give back to the team. This creates a beautiful, compounding cycle of accelerated growth.

Furthermore, exceptional articles that pass internal review are cleared for public distribution on external social media. This serves as a powerful portfolio piece for the engineer’s personal career, which ties back to massive intrinsic motivation.

👔 To All Managers: Don't Run Away From This To be completely honest, this system will tire a manager out to death. This is because you must strictly review (moderate) the members' entries to ensure no client confidential data or sensitive info is included, and you need to provide precise feedback to each individual. But if you slack off here, no one will follow you. Commit to getting your hands dirty.

Frontline Reality: The "Two Walls" You Will Inevitably Crash Into and How to Handle Them

While this cultivation plan sounds like smooth sailing, we naturally ran into troublesome snags and walls built by human nature during its operation.

Wall #1: The Cynical, Self-Proclaimed "Expert" Pessimists aka The Stubborn Ones

Every organization has at least one enthusiast who ruins the momentum by saying, "AI isn't that big of a deal," or "The code I write by hand is much cleaner." These individuals have zero interest in business or solving customer pain points (the true objective). They live in a world of self-gratification (pure research), running Python code they copied and pasted from a book and thinking, "I built a predictive model, I'm amazing."

• The Fix: Try to gently guide them back on track the first few times by reminding them to "face the customer's challenges." If they still don't change, remove them from the project or transfer them to another department without hesitation. The buds of new innovation are easily crushed by the noise of rigid pessimists.

Wall #2: "Over-Communication with Clients" and Emotional Burnout Born from Ultra-Fast Development

By implementing AI, development cycles that used to take 1 to 3 months shift into an ultra-explosive gear: "daily progress, daily customer feedback." What happens as a result of this is that the clients themselves cannot keep up with the speed and begin to panic. Consequently, to save face, young client-side representatives frequently start nitpicking over microscopic details (essentially throwing hurdles and unreasonable demands your way).

• The Fix: Future AI talent requires a heart of steel (High EQ: Emotional Quotient). You must not take the client's emotional words to heart. Instead, you need the mature composure to think ahead and care for things down to "how easily the client can explain this to their own boss." The cost paid by modern AI talent has shifted from the traditional "labor of the brain (the struggle of implementation)" to the "labor of the heart (communication and navigating human relationships)."

Conclusion: New-Era IT Engineers Can Shine Brighter Than Ever

With the advent of AI, the value of an "IT technician who can only write code" has plummeted. In extreme terms, anyone can do a decent job if they just buy the tools.

However, precisely because of this, the market value of "True AI Talent"—those who can aggressively spin the X and Y axes to paint a picture of business processes no one else could conceive, while smartly navigating the rough seas of human dynamics—will only continue to skyrocket.

This is not a dystopia where AI steals our jobs. It is the dawn of a wildly exciting era that pushes human creativity and spirituality to their absolute limits.

Now, why not start spinning the X/Y-axis loop with your team starting tomorrow?