CZ's Digital Brain: A Guide for Everyone

AI Analysis Time: February 8, 2026 Generated from 68 Markdown files Note: This report is AI-generated and for reference only.

What is This?

Imagine someone who puts their daily thoughts, ongoing projects, things they've learned, and even their mistakes in a public place—like a transparent "brain backup." That's what this repository is: CZ's (zccz14) digital thinking space.

Who is CZ? A technologist focused on quantitative trading and fintech, founder of the No Trade No Life (NTNL) project. He calls himself a "high-energy-consumption brain," enjoys thinking and writing, and pursues "things falling into place naturally." He even says: "If I'm gone one day, these are the raw materials for an AI to resurrect me."

What's in this repository? Simply put, there are three main categories of content:

• LOGS: 54 work diaries, recording what he did, thought, and what pitfalls he encountered each day. Like a programmer's version of a "social media feed," but more authentic and in-depth.
• INSIGHTS: 9 well-considered long-form articles covering topics like investment strategies, human-AI collaboration, and AI system design. If LOGS are raw stones, INSIGHTS are polished gems.
• Other Content: Includes introductions to quantitative trading projects (EA, FSA), a simulated "Qi Pa Shuo" debate, an in-depth analysis of the US government's Bitcoin seizure, and an interpretation of a private equity fund industry conference.

The repository spans from early January to early February 2026, documenting about a month of intensive thinking and creation. The content mainly revolves around three themes: how to use AI better for coding and content creation, how to make money scientifically in financial markets, and how to understand the relationship between humans and AI.

Core Projects: Explained by Analogy

CZON: Like Your "AI Writing Assistant + Auto-Translator + Personal Website Generator"

One-sentence explanation: CZON is a tool that turns your Markdown files into a multilingual website. AI handles translation, categorization, and summary generation—you just focus on writing.

What it does:

• Auto-translation: Like hiring a 24/7 translation team. You write in Chinese, and it automatically translates into English, Japanese, and other languages. It uses "adversarial translation"—one AI translates, another AI proofreads, like a publisher's "translator + proofreader" process (see CZON Adversarial Translation).
• Smart Categorization & Summarization: Like a librarian, automatically tagging your articles, writing introductions, and generating summaries tailored for different platforms (short & snappy for Twitter, professional for LinkedIn, relatable for Xiaohongshu) (see CZON Summary Types Memo).
• Zero-configuration Site Building: As simple as a "point-and-shoot camera"—you don't need to know web development. Write your article, run one command, and a beautiful multilingual website is generated (see The Meaning of CZON).

Why it's useful: If you have ideas to share with the world but don't want to spend time learning web dev, doing translations, or handling SEO, CZON automates all that grunt work. You only need to focus on the "writing."

Origin of the name: Each letter in CZON has meaning—C for Content-oriented, Z for Zero-configuration, O for Organic AI-native, N for an N-shaped creative energy curve (see The Meaning of N).

EA (Earnby.AI): Like an "AI-Managed Yu'e Bao," but with Higher Returns

One-sentence explanation: EA is a blockchain-based fund project. You deposit money, AI-driven quantitative strategies make profits for you, and there's a principal protection mechanism.

What it does:

• Principal-Protected Investment: Like deposit insurance for bank savings, EA splits capital into "senior" and "junior" tranches. Your money is senior; the project's own money is junior. Only after the project's money is lost does your principal get affected (see EA Project Introduction).
• AI Quantitative Trading: Like hiring a sleepless fund manager, using machine learning models to monitor markets 24/7 and trade automatically. Strategies include directional trading (predicting rise/fall) and delta-neutral strategies (profiting from spreads regardless of direction).
• Flexible Redemption: Flexible like Yu'e Bao. Withdraw anytime. Standard redemption takes 7 days; instant redemption is immediate (with a 0.5% fee).

Why it's useful: Traditional financial products offer lower returns, and bank deposit rates can't beat inflation. EA offers an option with ~12%-22% annualized returns, operating via blockchain smart contracts for transparent, verifiable fund flows.

Full Spectrum Analysis (FSA): Like a "GPS for Investment Decisions"

One-sentence explanation: FSA is a mathematical method that tells you, at any given moment, how much capital to invest and what leverage to use to maximize long-term returns.

What it does:

• Calculates Optimal Position Size: Like GPS giving you the best route, FSA calculates the proportion of capital you should invest based on your assessment of various possible market outcomes (see Full Spectrum Analysis).
• Prevents Ruin: Built-in "black swan protection," like a car's airbag—even in extreme scenarios, you won't lose everything.
• Adapts to Various Markets: Whether stocks, futures, or cryptocurrencies, as long as you can describe "what could happen, its probability, and the gain/loss," FSA can give advice.

Why it's useful: Most people decide investment amounts based on gut feeling. FSA turns this decision into a math problem. It's an upgraded version of the classic "Kelly Criterion," handling more complex real-world scenarios.

SandTable: Like an "Investment Strategy Simulator"

One-sentence explanation: SandTable is an experimental framework that lets you simulate various investment strategies on historical data to see which works best.

What it does:

• Strategy Backtesting: Like pilots training in a flight simulator, you can "test fly" your investment strategy on historical data without risking real money (see SandTable Naming).
• Separation of Concerns: Breaks investment decisions into three independent parts—market environment (what you can't control), signal strategy (how you judge the market), and betting strategy (how you manage capital)—for separate optimization (see Experimental Paradigm Restructuring).

Why it's useful: The name comes from ancient military sand table wargaming—generals simulated battles on sand tables before going to the real battlefield. SandTable lets investors "rehearse before engaging."

Core Philosophies: Understood Through Everyday Examples

Capital Protracted War: A Survival Guide for Ordinary Investors

Simply put: Don't aim to get rich overnight, and don't just save money foolishly. Use small monthly losses you can afford to wait for a life-changing opportunity.

An analogy: Imagine you're fishing. You spend 10 yuan daily on bait (your affordable cost). Most days, the bait gets eaten with no catch. But catching one big fish feeds you for a year. The key: bait money shouldn't affect your daily life, and you must have the patience to keep fishing.

How to do it:

1. Prepare a Stable "Ammunition Supply": For example, allocate a small portion of your monthly salary as the maximum investment loss you can bear. Like a war needs a supply line.
2. Let a Program Trade for You: Don't watch the markets yourself. Write an automated trading program (can't code? Let AI help). Human emotion is the biggest enemy in investing—greed when winning, fear when losing.
3. Increase Investment When Profitable: When a strategy starts making money, it means you're on the right track. Use the profits (not principal) to increase your position. Like "betting with house money" in poker.
4. Define "Victory Conditions": Investing isn't an endless marathon. Set a clear goal for "how much profit to take" beforehand, and actually take it.

In his article, CZ refutes three common misconceptions: the pessimists who think "ordinary people are doomed to lose," the gamblers who advocate "go big or go home," and the dogmatists who preach "be friends with time and get rich slowly." He argues none address a fundamental problem: human lifespan is finite; wealth growth cannot wait indefinitely (see Capital Protracted War).

This philosophy also sparked a brilliant simulated debate—in the format of "Qi Pa Shuo," featuring a fierce 4v4 clash between the "Steady Growth Faction" and the "Class Leap Faction" (see Qi Pa Shuo Debate).

The Market's "Three-Body Problem": Why Stock Markets Are Both Predictable and Unpredictable

Simply put: Three "forces" are at play in the market, interacting like three celestial bodies gravitationally bound. No one controls the others, so market behavior has patterns yet is full of surprises.

An analogy: Imagine an ecosystem with three animals—wolves (momentum capital, speculators chasing trends), sheep (value capital, investors buying low/selling high), and grass (liquidity capital, market makers facilitating trades). Too many wolves, sheep get eaten, wolves starve. Too many sheep, grass gets eaten, sheep starve. Only balance among the three sustains the ecosystem.

What this theory explains:

1. Why markets boom and crash: When "wolves" (speculators) are too many, they trample each other, causing a crash.
2. Why markets recover after crashes: After a crash, "sheep" (value investors) find prices cheap and start buying, leading to gradual recovery.
3. Why long-term prediction is impossible: Like the three-body problem in physics, the interaction of three forces is too complex for precise long-term prediction. But short-term trends and volatility patterns can be exploited.

CZ also uses a clever 3x3 matrix to show the perfect symmetry between the three capital types and three market variables (premium, momentum, volatility)—each capital type has its own "profit source," "risk source," and "cost source," with no party dominating forever (see The Three-Body Dynamics Hypothesis of Capital Markets).

How Humans and AI Collaborate: Let Go of the Need for Control, Learn to Be a "Hands-Off Manager"

Simply put: People hesitate to delegate work to AI because they fear AI's mistakes will be their responsibility. The solution isn't tighter supervision but establishing mechanisms to "recover when things go wrong."

An analogy: Like the first time you hand car keys to your newly licensed child. You're nervous not because you're controlling, but because you fear an accident. The solution? Not grabbing the steering wheel from the passenger seat (you might as well drive yourself). Instead: ensure the car has airbags (recoverability), the child knows traffic rules (intent alignment), and you can call them to pull over anytime (intervenability).

How to do it:

1. Intent Alignment: First, ensure AI understands what you want. Like briefing a new employee—align on goals before letting them work independently (see How to Solve Human Need for Control).
2. Controlled Risk: Ensure AI mistakes can be detected, corrected, and recovered from. Like "version control" in software development—roll back if something breaks.
3. From "Operator" to "Architect": You don't need to write every line of code. Design rules and workflows, letting AI operate freely within the framework (see Software Engineering Architecture for Module-Level Human-AI Collaboration).

CZ found in practice that the biggest issue with AI writing code isn't "not smart enough" but "not knowing what to discard"—it keeps all old code for fear of breaking compatibility, leading to bloated code, like a hoarder who never throws anything away (see Vibe Coding Major Failure).

Returning to Simplicity: Why "Simple" is Harder Than "Complex"

Simply put: True simplicity isn't because you don't understand complexity; it's choosing to return to simplicity after experiencing all the complexity.

An analogy: A person who never left their small town finds town life simple, versus a world traveler who chooses to return to the small town finds it simple—these are two different kinds of "simple." The latter's simplicity is a choice; they know what they gave up.

What this philosophy tells us:

1. Can't Skip Complexity: You can't become a master by imitating a master's actions. You must step into pitfalls and make mistakes yourself to truly understand principles that "sound like platitudes."
2. Can Lower the Tuition: While you can't skip, you can replace "fatal big losses" with "controlled small losses." Like learning to swim—you must get in the water, but start in the shallow end.
3. AI Can't Skip Either: When AI writes code for you, if it hasn't experienced the project's evolution, it can't understand which abstractions are core and which are temporary workarounds.

(see Returning to Simplicity: Complexity is an Inevitable Path of Cognition)

On Human Nature: In the AI Era, What Makes You Unique

Simply put: AI can replicate your knowledge and mimic your style, but not your experiences and growth trajectory. Your value lies not in "what you know" but in "what you've experienced."

An analogy: Two people can cook braised pork belly. One learned from a recipe, the other learned from their grandmother since childhood. The recipe can be copied, but the memories of learning from grandma—the kitchen conversations, the improvements after failures—cannot.

Core viewpoints:

1. The Non-Replicability of Memory: AI memory is data, infinitely replicable. Human memory is intertwined with emotion, physical experience, and a sense of time—unique.
2. The Importance of "Leaving Words": In the AI era, actively recording and expressing your thoughts is more important than ever. Not to leave perfect answers, but to leave a genuine growth trajectory.
3. Taste is the Ultimate Moat: When AI can do everything, "choosing what not to do" is more important than "what can be done." The essence of taste is the ability to refuse—you're willing to give up B, C, D for A.

(see On Human Nature)

Who is This For?

• If you're a programmer: You'll find extensive practical experience on AI-assisted programming—which scenarios AI excels in, where it fails, and how to design architectures for better AI-generated code. Especially the view that "object-oriented programming isn't suitable for AI" (Vibe Coding Major Failure) and the "module-level human-AI collaboration" architecture design (Module-Level Human-AI Collaboration) are valuable insights from frontline practice.

• If you're interested in investing: You'll learn a complete personal investment framework—from the strategic thinking of "Capital Protracted War" (Capital Protracted War), to the mathematical tool of "Full Spectrum Analysis" (Full Spectrum Analysis), to the market theory of "Three-Body Dynamics" (The Three-Body Dynamics Hypothesis of Capital Markets). Even if you don't plan to do quantitative trading yourself, understanding these frameworks can help you view investing more rationally.

• If you want to do content creation: You'll learn about the new paradigm of content creation in the AI era—how to use AI for translation, categorization, and summary generation (From Creation to Distribution), how to tailor content style for different platforms (CZON Summary Types), and the core principle of "deep creation, shallow distribution."

• If you're interested in the future of AI and humanity: You'll see a technologist's deep thoughts on "human nature"—in an era where AI can do more and more, what makes humans unique? (On Human Nature) How to build trust with AI? (How to Solve Human Need for Control) Where are AI's limitations? (Embrace the Finite, Design the Infinite)

• If you're just curious: You'll see how a real person thinks, makes mistakes, and grows. 54 work logs record his daily highs and lows—sometimes excited about discovering a new tool (Dawn of Liberation), sometimes debugging bugs until dawn (WebSocket Debugging), sometimes having intense late-night discussions with friends (LLM Code Quality Discussion). These logs are more authentic and interesting than any polished article.

Where to Start?

Recommended reading order, starting from the easiest and most accessible, gradually deepening:

First Stop: Understand Who This Person Is

Second Stop: Understand Core Philosophies (Pick what interests you)

Third Stop: Dive into Technical Details (Advanced Readers)

Fourth Stop: Browse the Logs Casually

The 54 LOGS don't need to be read in order. Pick interesting titles. Here are some highly recommended ones: