AI Self-Growth Series #2: If AI Can Do It, Why Persist Yourself?

The concept of "AI Self-Growth System" (ASGS) has been absolutely fascinating me lately.

I asked AI: Does this count as an original concept or new theory I created?

AI replied:

In the previous article "Designing Self-Growth Systems with AI", we discussed the difference between "buildings vs species." Today we'll dig deeper into energy and philosophy, and propose a complete theoretical framework.

1. Tao Te Ching: Why "Persistence" Violates Universal Laws

This perspective might sound counterintuitive. We were taught since childhood: "Nothing is impossible for a willing heart" and "With enough effort, an iron pestle can be ground into a needle."

But in Taoist philosophy, "persistence" itself means your system design has a problem.

The Tao Te Ching teaches "Wu Wei Er Wu Bu Wei" (act without forcing, yet nothing is left undone). "Wu Wei" doesn't mean doing nothing—it means not acting recklessly, not going against the flow.

If something requires enormous "willpower" to "grit your teeth and persist," it means you're swimming upstream, fighting against physical laws, using your limited physical energy to fill a massive dissipative structure.

Physics tells us the world is a dissipative structure. Any ordered system (your business, your traffic pool), if not continuously fed with energy, will automatically move toward disorder, chaos, and death. This is called entropy increase.

Traditional business essentially fights entropy by burning "human energy." You must monitor employees daily, respond to customers daily, update code daily. Once you get sick, slack off, or simply "don't feel like it anymore," the system collapses. This is why founders are always exhausted—you're feeding your company with your life force (negative entropy).

AI business essentially fights entropy by burning "Tokens." For the first time, we have access to a purely rational, universally accessible, nearly infinite, immortal energy source.

2. But What If You Feel Uncomfortable Not Doing It?

Someone might ask: So we should do nothing at all?

No.

The key criterion is: Would you feel uncomfortable NOT doing this thing?

If not doing it makes you uncomfortable, then do it—even if it doesn't produce direct value. Like me writing this article: even if no one reads it, I feel better having written it. This is "following your heart," another layer of "Wu Wei."

But if you ask me to persist in making short videos or livestreaming every day, I can't do it. That's "going against my heart." That kind of "persistence" drains me, causes pain, and consumes willpower every day.

The real selection criterion isn't "can this make money," but "does this put me in flow."

What is flow? It's when you're doing something, completely immersed, forgetting time and self. Reference my previous article The Only Remedy for Human Suffering—various ancient wisdom traditions (meditation, Taoism, craftsmanship) all ultimately point to "focusing on the present moment." When you're in flow, you don't need to "persist" because you don't want to stop.

Then, outsource everything that requires "persistence"—the repetitive, boring parts—to AI.

3. Core Terminology: The ASGS Naming System

For a theory to stand, it first needs its own language. Here are the core concept definitions for ASGS:

Entropy Tax The "debt" you incur every day by not maintaining your system. If you don't post content for 3 days and traffic drops 10%, your daily entropy tax is 3.3%. Entropy tax is the "physical tax" the universe collects from all ordered systems.

Token Burn Rate The number of tokens consumed per unit time. This is your AI system's "electricity bill." A healthy ASGS should have a Token Burn Rate far lower than the revenue it generates.

Self-Growth Coefficient (SGC) The core KPI. Formula: SGC = New Traffic / Token Consumption. If SGC > 1, your system is "profitable"—each token spent brings more than 1 unit of value return. If SGC < 1, you're "losing"—the system hasn't achieved product-market fit yet.

Feedback Latency The average time from content publication to data feedback. A mature ASGS should have feedback latency as short as possible. If you publish an article and only know its performance 3 days later, that's too slow. The ideal state is real-time feedback.

4. The Energy Formula

To quantify this, I've summarized an AI Growth Energy Formula:

Growth = (AI_Energy × Data_Feedback) − Entropy_Market

AI_Energy: The amount of Tokens you invest and the quality of your Prompts. This is the system's fuel.

Data_Feedback: This is the most critical. Without feedback, the system is open-loop—just "automation," not "self-growth."

Entropy_Market: Competitors are also grinding, user thresholds keep rising. Your system must outrun entropy.

Reference: The Harder You Work with AI, the Less You Earn—because you're only increasing the denominator (output quantity) without optimizing the numerator (quality and feedback).

5. ASGS Maturity Model: From L0 to L3

Not all "automation" is "self-growth." I categorize ASGS into four maturity levels:

L0 Manual: You do everything by hand. Posting articles, replying to comments, analyzing data. You are the system's "energy source." You stop, it stops.

L1 Automation (Open Loop): You've set up scheduled tasks that let AI automatically generate and publish content daily. But there's no feedback loop—you don't know which content performs well or poorly. This is "blind walking."

L2 Self-Feedback (Closed Loop): The system can automatically adjust strategy based on data. For example, discovering that "AI watermark removal" content has high click-through rates triggers automatic generation of similar content. This is "a robot with eyes."

L3 Self-Evolution (Self-Replication): The system can discover new growth opportunities and replicate itself. For example, when one site succeeds in the "AI tools" domain, the system automatically analyzes the pattern and clones it to the "design tools" domain. This is "a digital species that can reproduce."

Most people are stuck at L1, thinking "automation" equals "self-growth." They're worlds apart.

6. Relationship with Classic Theories

ASGS wasn't invented from scratch. It stands on the shoulders of giants:

Relationship with PLG (Product-Led Growth) PLG emphasizes "the product itself drives growth"—users naturally share as they use it. ASGS further emphasizes that this "driving" process can be taken over by AI. Instead of waiting for users to share spontaneously, AI proactively identifies "share-worthy" moments and pushes them.

Relationship with the Amazon Flywheel Bezos's flywheel: Lower prices → More customers → More suppliers → Lower costs → Lower prices... repeating. ASGS's flywheel: More content → More data → Better AI decisions → More precise content → More traffic... But the key difference: Every step of the ASGS flywheel can be driven by AI, requiring no human effort.

Relationship with Pieter Levels (@levelsio) Methodology Levels is a legend in the indie developer community—one person running a dozen products, earning millions annually. His core philosophy is "Launch fast, iterate based on data." ASGS engineers this philosophy: not humans iterating, but AI iterating. You design the rules, AI executes the evolution.

7. Prioritize High-Leverage Work

If you must "choose" to do something, prioritize work with leverage.

What is leverage? Something you do once that keeps producing returns.

Writing a book has more leverage than writing 100 social media posts. Building a product website has more leverage than posting 100 Instagram notes. Building an AI automated marketing system has more leverage than manually sending 1,000 outreach emails.

Reference The E^F Law: V = (E^F × S) / N. Here F is Focus (focus coefficient). When F > 1 (flow state), energy E grows exponentially. AI's value is that it enables "system-level flow"—you design once, AI executes with extreme focus 24/7, and S (systemization level) gets infinitely amplified.

8. Grit Your Teeth and Build It Into a System

Many people's problem: encountering a repetitive task, doing it 3 times, getting annoyed, but too lazy to optimize, so they continue manually doing the 4th, 5th time...

Anything that makes you repeat an action more than 3 times should be considered for automation.

Grit your teeth, focus, and build it into a system once.

Reference Maxwell's Demon Guide: How to Become an Information Age Demon—the real leverage in the information age isn't working harder, but creating a "demon" that works hard for you.

Dr. Wu Jun has a saying I deeply agree with: "The best way to improve efficiency is to do less."

Yes, to achieve "doing less," you need to build more "AI-automated self-growth systems." Then the only thing you need to do is pay the Token Fee to keep it running.

9. AI Automated Marketing Example

Let's look at a specific scenario: Automated SEO Marketing.

Traditional approach (Struggle): You hire an SEO expert to dig keywords from Google Keyword Planner daily, then find writers to write articles, add images, and publish. Persist for a month, write 30 articles. Exhausting.

ASGS approach (Flow): You build an AI self-growth system:

Sensor Layer: Scripts automatically monitor the fastest-rising long-tail keywords in Google Search Trends daily. For example, discovering: "AI video watermark removal free..."

Controller Layer: AI analyzes the search intent of this keyword and decides to generate a Landing Page specifically solving this problem. It automatically plans the page structure: Pain point → Solution → Tool recommendation → FAQ. Reference How to Use Vibe Marketing for AI Automated Marketing.

Actuator Layer: AI calls Vercel API to automatically deploy new pages, calls Midjourney to generate cover images, automatically submits to Google Search Console for indexing.

Feedback Loop: This is the most important step. If users click this page and stay for more than 1 minute, the system determines "this keyword is effective" and automatically generates 10 related pages around this keyword. If bounce rate is extremely high, the system determines "content mismatch" and adjusts Prompt strategy next time.

Throughout this process, you don't need to "persist" at anything. You just pay the API Token cost. This is the core logic mentioned in 5 Business Processes You Can Automate Today (No Coding Required): Build once, run automatically, compound infinitely.

10. Failure Boundaries: When Will the System Die?

Any theory needs boundaries to stand. ASGS can also die, typically from these three causes:

Data Poisoning: If the sensor layer mistakes crawler traffic for real users, the decision layer will hallucinate and the system starts spinning empty. I once knew someone doing Newsletter automation—his system automatically scraped trending news and sent them daily. But because there were many bot email addresses mixed in his subscriber list, his "open rate data" was artificially high. The AI judged "current strategy is working great," when in reality, real users had long since left. This is classic data poisoning.

Platform Sanctions (God's Wrath): Google algorithm updates, Twitter bans. This is "physical attack" from a higher dimension. No matter how perfect your ASGS is, if Google decides to de-index you, your traffic goes to zero overnight. So ASGS's highest principle is: decentralize as much as possible (multi-platform distribution), or simulate being human enough (avoid being identified as a Bot).

Energy Deficit: When Token Cost > Revenue. If your system consumes $10 in Tokens daily but only brings in $5 revenue, it's a "vampire," not a "blood generator."

The good news: Token prices drop 10x every year. This means the survival threshold is dropping dramatically each year.

11. Implementation: AI Coding and Workflows

Two main implementation paths for ASGS:

Path One: AI Coding (Vibe Coding) Use tools like Cursor / Windsurf / Antigravity to have AI write code directly. You describe requirements, AI implements. The entire system is fully customized with maximum flexibility.

Path Two: Workflow Automation Use no-code tools like n8n / Make / Zapier to string together various SaaS services. No coding required, but fast and stable.

The two paths don't conflict. You can use AI coding for core logic and workflows for edge connections. The key is let machines do repetitive things, you do only creative things.

12. Become a Creator

So what's the highest ROI activity?

Building "AI Self-Growth Systems."

Do it once, earn continuously. Build once, run automatically, compound infinitely.

In the traditional world, effect and effort are linear. But in the AI world, if you encapsulate your effort E into a reusable system S, and let AI run with high focus F continuously, your value V will grow exponentially. This is the E^F Law applied to ASGS.

Stop persisting, start designing. Starting today, become a creator and maniacally build "AI Self-Growth Systems."

Further Reading

• 📗 AI Self-Growth System Complete Tutorial (40 Chapters)
• Designing Self-Growth Systems with AI (Series opener)
• The Only Remedy for Human Suffering (Flow and being present)
• Maxwell's Demon Guide
• The Harder You Work with AI, the Less You Earn
• The E^F Law
• How to Use Vibe Marketing for AI Automated Marketing
• 5 Business Processes You Can Automate Today