A question was posed by a community member: a mother, whose son is nearing university graduation, wants to pursue a career in artificial intelligence. Her question was specific: Should he pursue an AI degree? Studying abroad could cost hundreds of thousands.
The response was succinct: Don't study it; just start doing it.
Why this advice? The AI industry is currently in its "wild frontier" phase. What does this mean? It's like the early days of Liangshan before the heroes formally gathered—achievement is measured by who can successfully pull off the mission, regardless of background. It's an era where capability trumps pedigree.
History offers parallels. During the Five Dynasties period, Zhu Wen promoted talent based on ability, not origin. He appointed a minor Tang official, Jing Xiang, directly as his chancellor. Another scholar, Li Zhen, was put in charge of military affairs and excelled. Why? Because building a new order requires practical skills, not aristocratic bloodlines. Those from prestigious families often contributed little beyond writing poetry. The real contributors were frequently those overlooked by traditional elites.
Consider the company C3.ai, Inc. Its founders graduated from Wuhan University and South China University of Technology—respectable institutions, but not globally top-tier. Yet, the company nearly secured $2 billion in funding. While the long-term prospects might be uncertain, the key point is that investors aren't funding academic pedigrees. They are funding the ability to "produce results."
The sole criterion for success in this frontier phase is problem-solving. Academic qualifications are largely irrelevant at this stage.
Some might argue that there are prodigies and entrepreneurs from major tech companies. Certainly, but that's not the narrative for the average person. When Jack Ma founded Alibaba, initial success didn't hinge on degrees. He spoke of ordinary people achieving extraordinary things. His "18 Arhats" were his students and followers—ordinary individuals who joined him early. Ma reportedly told them they might only become junior leaders after the company formalized, so they had to strive. Ultimately, their achievements far surpassed those of later hires from prestigious schools. Why? They drank from the well first. The reward for pioneers in a technological wave is exponentially faster than climbing the seniority ladder.
An ancient strategist, Han Feizi, advised the King of Qin that the rival states were weakened by internal strife, corruption, and exhaustion, while Qin was strong and its treasury full. He declared it a once-in-a-millennium opportunity to unify the empire, urging immediate action before the window closed. Hesitation would only benefit rivals.
The AI industry is at a similar juncture. Entering now is like being one of the early pioneers. Waiting to complete a degree means missing the boat—even a junior position might be gone.
Beyond the frontier phase, what other stages exist in an industry's lifecycle? Any technology-driven industry typically undergoes three phases.
First, the Frontier Phase. Everyone is experimenting, and no one holds the definitive answers. Information asymmetry is valuable, and the ability to execute is paramount. It's a period of百花齐放 (a hundred flowers blooming) and intense competition where anyone has a chance.
Second, the Growth Phase. Giants rapidly emerge and begin carving out territories. Moats are dug, and ecosystems become more closed. The barrier to entry for ordinary individuals rises sharply.
Third, the Maturity Phase. The field consolidates, leaving only one or two dominant players, much like how search is dominated by Baidu and Google, or social media by WeChat. By maturity, the rules of the game are set, and newcomers must play by them.
We are currently transitioning from the frontier to the growth phase. Spending two years on a degree means graduating just as the frontier period concludes. The giants will have already secured their territories and built their moats. What awaits then? High-salaried, prestigious, yet demanding and granular roles as ordinary employees in large corporations—essentially, becoming a cog in the machine. And this is after investing a small fortune for a ticket that arrives two years late.
The author's own company is in consulting, without inherent software or coding capabilities. This year, however, revenue from AI-related endeavors has surpassed that of the core consulting business. This wasn't achieved by earning a computer science degree, but by entering the arena at the right time and taking action. It started with solving a real problem using AI tools, then another, and another, eventually validating the approach.
This is the driving force of the era. It doesn't recognize diplomas or seniority; it only recognizes whether you have entered the fray.
The advice to the mother is this: Your son is about to graduate—perfect timing. Don't spend a fortune on a degree that only pays off in two years. Instead, find an organization or identify a real-world problem and solve it using AI. In a year, he will have a track record of accomplishments, not just a diploma. Achievements can be cashed in immediately; diplomas often mean waiting in line.
The window of opportunity won't wait. As Han Feizi said two millennia ago: if not now, when?
A new course on personal advancement is also in active preparation. Given the rapid pace of change in AI, the content is being adapted continuously, almost to the point of a complete overhaul. The commitment remains to "over-deliver" on value. Stay tuned for its upcoming release.
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