Living Well in the Present Moment vs. Living Well Each Day

Living Well in the Present Moment vs. Living Well Each Day

I once discussed the concept of “the present moment” with a teacher.

He argued that “living well in the present” is an exceptionally high bar for most people—difficult to achieve and weak in practical guidance.

A more grounded, actionable principle is: Live well each day—make every 24-hour cycle count.

For everyone, a full day is the smallest closed loop of time.

For the vast majority, doing that consistently would already be extraordinary.

There’s a simple technique to make this principle stick:

Identify micro-habits you can sustain—and practice and record them daily. My personal micro-habit list for 2025 includes: waking up early, meditating, reading or listening to books, writing or reflecting, running or exercising, studying English, and taking cold showers.

The core method for building micro-habits follows BJ Fogg’s Behavior Model: anchor new habits to existing ones.

Take meditation: to build it reliably, I pair it with my afternoon nap—so when I wake up, I sit for five minutes of stillness. That tiny trigger makes consistency effortless.

Or cold showers: I schedule them during the quiet window after waking but before running. That small, fixed slot has made the habit stick without friction.

Then comes tracking: spending just 3–5 minutes each day to log these habits—and sharing updates in a WeChat group—creates gentle accountability and reinforces continuity.

After a few months, the benefits compound: sharper focus (i.e., stronger capacity to live in the present), clearer daily outputs (“what did I actually produce today?”), and deeper alignment between intention and action.

Self-Awareness vs. Selfishness

Self-awareness and selfishness are often conflated—but they’re fundamentally different.

Self-awareness is about perception and reflection: knowing your values, limits, triggers, and patterns. Selfishness is a behavioral orientation—how you act when interests collide.

Key distinctions:

• Having self-awareness does not make you selfish.
• A self-aware person is often more capable of helping others—not less.
• Selfishness isn’t inherently negative. When paired with fair collaboration mechanisms, it fuels progress.
• What society rightly opposes is harmful selfishness—actions that advance one’s interest at another’s expense.
• Self-interest that doesn’t diminish others’ well-being isn’t just acceptable—it’s essential. Protecting your own boundaries, energy, and integrity is responsible stewardship.

Moderate self-interest is biologically necessary. The critical question isn’t “Should I care about myself?” but “How do I structure cooperation so self-interest serves collective good?”

Adam Smith’s “invisible hand” captures this: when individuals pursue their own rational interests within fair rules—markets innovate, services improve, and society advances.

Strong self-awareness, in fact, enables better service to others.

You can only empathize deeply if you understand your own emotions. You can only give sustainably if you know your limits. You can only guide wisely if you’ve mapped your assumptions.

Think of the airplane oxygen mask rule: secure your own mask first—then assist others. That’s not indifference. It’s prerequisite competence.

Education in the AI Era

What’s the most important education in the age of AI?

Wang Yuheng, on a recent show, named two essentials: physical education and aesthetic education.

On physical education:
In the end, your body is your foundation—the platform for all thought, creation, and connection. Yet most people grasp its irreplaceable value only when it’s too late: chronic fatigue sets in, mobility declines, recovery slows—not because they ignored health, but because they never built movement into identity.

And movement itself is aesthetic: rhythm, breath, effort, grace. It’s how we feel life’s vitality in real time.

On aesthetic education:
Low aesthetic literacy erodes judgment—not just taste, but moral and functional discernment.

It’s not merely a “gap.” It’s a pitfall. Once collective aesthetic sense is dulled or suppressed, our standards collapse. You stop asking, “Is this well-made? Is it coherent? Does it honor the user?”—because you no longer feel the weight of those questions.

Aesthetic education is non-negotiable—and it’s best started young. It’s the “childhood kung fu” of discernment.

Consider affluent retirees who spend years designing gardens or building private libraries. AI can suggest plant species or cataloging systems—but you choose the proportions, the flow, the silence between elements. That choice rests entirely on cultivated taste.

Without aesthetic grounding, AI’s output becomes overwhelming noise—or worse, a crutch that outsources judgment. You’ll either freeze at options or follow prompts blindly.

Aesthetic ability is, at its core, advanced judgment: a layered synthesis of pattern recognition, harmony sensing, value weighting, and contextual awareness. It’s not “pretty vs. ugly.” It’s “coherent vs. chaotic,” “resonant vs. alienating,” “enduring vs. disposable.”

More than taste, aesthetic education cultivates agency. With it, you navigate AI’s infinite possibilities with intention—not drift. In the AI era, education’s highest purpose is nurturing what remains irreducibly human: embodied presence, ethical intuition, and creative sovereignty.

AI Penetration Rate

Alibaba’s recent moves signal something significant: a re-energized Alibaba may be taking off.

At the start of 2025, the group declared “AI to C” (AI for consumers) as one of its top strategic priorities. Over the next three years, its investment in cloud and AI infrastructure is expected to surpass the total of the previous decade.

Virtually every Alibaba business unit is now mapping out AI-powered growth levers for the new fiscal year.

For Taobao & Tmall—the group’s core engine—AI integration is no longer optional. It’s a strategic imperative for 2025.

Driving evolution through AI is now Alibaba’s central organizational challenge.

Multiple Alibaba consumer-facing products have added “AI feature penetration rate” as a formal KPI—measuring not just whether AI features exist, but how many users actively engage them, and how much revenue or retention they drive. This metric will shape performance reviews and resource allocation across the group in 2025.

Beyond boosting internal productivity, AI is also reshaping how core resources—especially attention and traffic—are allocated.

Here lies a crucial insight: AI penetration rate.

Alibaba excels at identifying pivotal metrics—and this one powerfully nudges teams toward “AI-first” thinking. For individuals, it’s equally instructive: don’t just use AI tools—measure how deeply they’re embedded in your daily workflow and outcomes.

Lessons for SMEs and founders:

1. AI is irreversible. It’s not a trend to monitor—it’s infrastructure to adopt.
2. Anchor AI in user value. Solve real pain points—not tech for tech’s sake.
3. Follow Alibaba’s lead: AI boosts efficiency and reallocates scarce resources (e.g., attention, labor, capital). Prioritize both.
4. Leverage open ecosystems. Use open-source models, public APIs, and partner platforms—don’t build everything from scratch.
5. Track penetration—not just deployment. Did users adopt your AI feature? Did it lift conversion, retention, or satisfaction?
6. Start small, iterate fast. Pick one high-impact workflow (e.g., customer onboarding, content drafting), apply a proven AI tool, measure, refine.
7. Seek asymmetry. Giants scale horizontally. You win by going deep—dominating a niche use case, vertical, or user segment where your domain insight + AI creates unique leverage.
8. Demand ROI. Every AI initiative must pass a clear cost-benefit test: Will this generate measurable revenue, save verified hours, or reduce tangible risk? If not, pause.

Cross-Circle Thinking

Professional background, education, and personal interests naturally form distinct “circles”—each cultivating its own logic, language, and reflexes.

Art circles lean intuitive and expressive; tech circles prioritize precision and scalability; growth/traffic circles obsess over signals, channels, and conversion funnels.

Learning across circles—studying their mental models, decision heuristics, and success criteria—is where breakthrough thinking emerges.

Cross-circle thinking resembles interdisciplinary work—but with higher stakes and faster feedback. Marketing, for example, sits at the intersection of economics, psychology, data science, and design.

When you intentionally blend mindsets—say, traffic logic + artistic sensibility + engineering rigor—you unlock multiplicative effects: 1 + 1 + 1 > 3.

I’ve felt this acutely lately.

AI-native thinkers deeply understand capability boundaries—and instinctively reach for automation before manual work.

Traffic-savvy friends spot emerging channels and arbitrage opportunities before algorithms catch up.

Education designers bring sharp insights into learning loops, motivation architecture, and pedagogical scaffolding.

Recently, a project I co-designed fused all three: AI handles content generation and grading; traffic logic identifies low-cost acquisition paths; education design ensures engagement, mastery, and retention. The result? Automated delivery, scalable onboarding, and human-centered outcomes—all in one system.