Why You Don’t Need to Fear “Giants”

When friends bring up the threat posed by tech “giants,” my view is simple: in most cases, you genuinely don’t need to fear them.

Generally speaking, unless you possess overwhelming strength, early-stage startups should avoid entering a giant’s core business—where direct head-to-head competition is inevitable.

But what if you start at the margins of a giant’s business? Growth there often draws attention quickly—and triggers rapid imitation.

To a giant, copying a product looks easy.

But is it actually easy? Let’s examine this more closely:

Organizational bloat is almost inevitable at scale. Unless the CEO personally champions the initiative—or a truly empowered leader drives it—the new project will likely calcify into a miniature version of the same unwieldy bureaucracy.
Resource allocation is deeply political. Within a mature giant, a small new project—especially one unrelated to, or even conflicting with, current core operations—faces steep internal hurdles securing budget, talent, or engineering bandwidth. Worse, it may trigger zero-sum resource battles. Real-world examples abound. The result? Innovation teams end up fighting alone—deprived of the very “advantages” the parent company supposedly offers.
Mental models are sticky. Teams pulled from legacy units inevitably fall back on proven internal patterns—reproducing familiar workflows, interfaces, or assumptions. Think of how many Western internet products failed in China precisely because they couldn’t adapt their mental models to local user behavior and expectations.
Cost advantage? Often nonexistent. Giants rarely operate with startup-level cost discipline. Their infrastructure, compliance overhead, and process layers inflate unit economics—making agility expensive.

Not fearing giants doesn’t mean ignoring them. When competition arises, you must study your opponent’s strategy—and, crucially, their blind spots.

For a startup, obsessing over giants is a distraction. What matters far more is doing your own work well: staying patient, managing risk deliberately, waiting for the right moment—and seizing opportunity when it arrives.

Why Scores Are Rising

Dr. Li shared an observation: student scores are trending upward—not because standards have dropped, but because high-quality learning resources are now widely accessible.

Take Bilibili: thousands of clear, engaging videos break down complex concepts and teach effective study methods. More students are integrating these into their routine—using them as active supplements to classroom learning.

Beyond formal MOOCs, such platforms deliver massive auxiliary value.

One notable pattern: high scores are clustering and low scores are clustering. Why? Because a significant number of students still don’t know how to leverage external tools—whether online tutorials, tutoring, or peer communities—to accelerate learning.

The gap between those who harness digital tools and those who don’t is already stark. With AI entering education, that gap will widen further—fast.

The Primary Purpose of Being Alive

The first purpose of being alive is to become the master of yourself.

Only from that foundation can you discover your own meaning, and arrive at your own version of fulfillment.

Yet a vast chasm lies between intention and reality: resisting low-grade dopamine traps—and all the forces that quietly hijack your attention and time: short videos, mental clutter, trivial tasks.

Crossing that chasm is a lifelong challenge for most people.

Take short-video apps. Yes—they offer real utility. But they also profoundly constrain human potential. Calling us “data-farmed beings” isn’t hyperbole. Corporations design these platforms around one principle: endlessly satisfying our preferences. The result? Millions become heavy users of what amounts to digital opium.

If you feel physically restless—or even anxious—after just 60 minutes without scrolling, you’re likely already dependent.

That’s why Steve Jobs, despite launching the wildly popular iPad, reportedly banned his children from using it—and told interviewers his kids had never touched one. He understood how easily such tools trap us in shallow dopamine loops. Sustained immersion makes “self-mastery” nearly impossible.

Truly autonomous individuals—those who remain uncontrolled by algorithmic feeds or ambient noise—are exceedingly rare.

Turning “Dark Cards” into “Open Cards”

Top poker players excel not just at bluffing—but at card counting. Its core purpose? To convert uncertainty (“dark cards”) into usable knowledge (“open cards”).

The earlier you reveal hidden information, the higher your odds of winning.

A key counting tactic? Inferring opponents’ hands from their betting patterns and the visible cards on the table.

This logic applies directly to product strategy.

Example: Use market research to reverse-engineer competitors’ priorities, roadmaps, and constraints—then identify openings they’ve overlooked or under-served.

Sometimes, all it takes is cultivating two habits: disciplined curiosity (asking “What are they really optimizing for?”) and structured inference (connecting observed signals to plausible underlying realities). That alone yields powerful insights.

Even when impact feels subtle, playing with open cards is always better than playing blind. Information is your most critical resource—and research, analysis, and reasoning are how you reduce uncertainty.

Understanding Leverage

Leverage is an amplifier. It magnifies both strengths and weaknesses—making it inherently double-edged.
Mastering leverage is central to boosting personal and organizational productivity.
Those who wield leverage skillfully outperform those who don’t—by orders of magnitude.
Capital is one of the most potent levers—but beyond a certain scale, it flips: you serve capital, rather than capital serving you.
Because leverage multiplies risk, many people lose everything overnight—not from bad ideas, but from misjudging the downside exposure it introduces.
Leverage also warps psychology. High-leverage situations breed dangerous overconfidence—especially in the short term.
Today, we interact with leverage constantly—often unconsciously. The widespread availability of leveraged tools (cloud computing, APIs, no-code platforms) and infrastructure is why productivity has surged so rapidly across industries.
Example: You may not know the term “influence leverage,” but if you regularly post thoughtful updates on WeChat Moments, you’re already using it.
Why will AI accelerate productivity further? Because it dramatically upgrades every layer of leverage—from idea generation to execution speed to distribution scale.
For individual growth, the highest-return lever remains deliberate learning: reading deeply, taking rigorous courses, seeking mentors—and, in the AI era, learning how to use AI to amplify your creativity, judgment, and output.