Finite Body, Infinite Questions — A Philosophical Portrait of a Technical Thinker

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

Introduction: Core Propositions

Across these 68 documents, a tech entrepreneur engages in a continuous self-dialogue through logs, insights, and theoretical explorations. On the surface, these writings cover quantitative trading, AI programming, product design, and team management; yet at a deeper level, they repeatedly touch upon several ancient and eternal philosophical questions: How does human finitude confront the world's infinitude? How does free will realize itself within constraints? How does cognition traverse complexity to reach truth? How can individual existence remain irreplaceable in an age of replicability?

These questions are not posed in the manner of academic philosophy but grow from the soil of practice—from a trading stop-loss, from a crash of AI-generated code, from a late-night inquiry into "whether the soul can be replicated." Precisely because of this, they possess a rare authenticity: not thinking for the sake of argument, but thinking for the sake of living.

This article will explore the following core propositions:

1. Finitude and Transcendence: How do humans seek possibilities for leapfrog growth amidst the triple finitude of time, resources, and cognition? This touches the core of existentialism—can a finite body bear an infinite will?
2. Control and Trust: As humans delegate more decision-making power to machines, where are the boundaries of subjectivity? What is the nature of the desire for control, and what does letting go mean?
3. The Spiral of Cognition: Why is complexity inescapable? What is the essential difference between "returning to simplicity" and "never having set out"?
4. The Generativity of Existence: In an era where AI can replicate everything, where exactly is human irreplaceability anchored?

Proposition One: Finitude and Transcendence — How Humans Seek Freedom Within Constraints

The Problem Posed

Humans are finite beings. Lifespan is finite, resources are finite, cognitive bandwidth is finite. Yet human desires—whether for wealth, understanding, or freedom—point toward the infinite. This contradiction is the core tension of existentialist philosophy and the deepest undertone in this collection of texts.

In The Capital Long Game, the author poses a sharp question with rare candor: The contradiction between the finitude of individual lifespan and the time required for wealth accumulation is a fundamental dilemma that the theory of steady development cannot answer. He writes:

"By the time assets increase tenfold, it will be ten years later, and life will have already entered its next stage... Wealth does not arrive when the individual needs it most. When one is old, does pursuing leapfrog growth in wealth still hold significant meaning?"

This is not merely a question of investment strategy but an ontological one: If time is the ultimate non-renewable scarce resource, then any plan premised on 'taking it slow' evades the fundamental condition of being human.

The Position in the Texts

The author's response is "The Capital Long Game"—a strategic framework that trades controllable losses for leapfrog gains. Its philosophical core can be summarized as: Accept finitude, but refuse to be defined by it.

He refutes three common stances one by one: Cynicism ("the individual is doomed to fail"), Opportunism ("all-in for sudden wealth"), and Dogmatism ("steady development theory"). These three stances represent three ways of escaping finitude: surrendering resistance, gambling everything, and numbing oneself with the illusion of time.

In The Three-Body Dynamics Hypothesis of Capital Markets, this line of thought is pushed to a more abstract level. The author models the market as a system of interacting forces among three types of capital (momentum, value, liquidity), arguing for the chaotic nature of markets—long-term prediction is impossible, but short-term characteristics are predictable, and statistical laws are robust. This conclusion precisely echoes his investment philosophy: since the long term is unpredictable, "being a friend of time" is a cognitive self-deception; the real strategy should be to strike decisively within short-term predictable windows.

Philosophical Parallels

From a Heideggerian perspective, what the author describes is the investment version of "being-towards-death" (Sein-zum-Tode). Heidegger argued that it is precisely the apprehension of death—the ultimate finitude—that awakens one from the "falling" of the "they" (das Man) and allows for authentic existence. The author's critique of "steady development theory" is essentially a rejection of the "they"-style investment philosophy: most people choose steadiness not because of rational calculation, but because they dare not face the fact that their time is finite.

However, the author does not slide into Sartrean absolute freedom. In Embracing 'Finite', Designing 'Infinite', he explicitly states: Rather than futilely pursuing an "infinitely intelligent individual," it is better to prudently design an "infinite system capable of integrating and orchestrating finite intelligences." This is an engineered existentialism—not transcending finitude in spirit, but transforming finitude into a design principle within system architecture.

Deeper Interpretation

A profound dialectical movement exists within the author's thought: he acknowledges that finitude is inescapable (the "Münchhausen trilemma"), yet refuses to use finitude as a reason for surrender. This stance is neither optimism nor pessimism but closer to what Camus called "Sisyphean revolt"—knowing the rock will roll down again, yet choosing to push it uphill nonetheless.

But unlike Camus, the author is not content with "the struggle itself is enough to fill a man's heart." He demands that the revolt must have a mathematically positive expected value. In The Capital Long Game, he defines victory conditions, risk control lines, and pyramiding strategies in strict mathematical language, transforming existentialist revolt into an engineerable, back-testable plan. This is perhaps the most unique philosophical contribution in these texts: transforming "being-towards-death" from a spiritual posture into an executable algorithm.

Proposition Two: Control and Trust — The Delegation and Safeguarding of Subjectivity

The Problem Posed

When AI Agents can write code, manage projects, and even make investment decisions, humans face an unprecedented crisis of subjectivity: To what extent should I trust the machine, and where should I draw the non-delegable boundary?

This question manifests in the author's daily practice in extremely concrete ways. In The Dawn of Liberation is Approaching, he describes the contradictory experience of using vibe-kanban to manage AI Agent tasks: "felt great for a second, then felt bad again." The unease not only didn't disappear but intensified with managing more tasks. He realized: There is a fundamental contradiction between the desire for detailed control and the craving for rapid progress, and this contradiction stems from the finitude of human bandwidth.

The Position in the Texts

The author provides a systematic answer in How to Solve the Human Desire for Control. He offers a key insight: The essence of the desire for control is not human obsession with power, but rational concern over "losing control of consequences." Therefore, the solution is not to eliminate the desire for control, but to construct "Controllable Trust"—a trust model based on systematic safeguard mechanisms.

This trust model consists of two layers:

• Foundation Layer: Intent Alignment — Ensuring the Agent pursues what the human truly desires.
• Execution Layer: Risk Control Triangle — Predictability, Intervenability, Recoverability.

"The desire for control is not a defect to be overcome, but an instinctive reaction to risk." — How to Solve the Human Desire for Control

More profoundly, the author reveals the fractal recursive structure of intent alignment: human intent is inherently a complex, multi-scale, multi-layered network; strategic intent recursively decomposes into tactical and operational intents; alignment must hold simultaneously at every level. This insight finds corroboration in military science in From Battlefield to Digital Space—the core of Su Yu's operational directives was precisely "cognitive unity first, structure determines function, protocol supersedes communication."

Philosophical Parallels

From a Cybernetics perspective, the "Controllable Trust" the author describes is essentially a design problem for a feedback control system. Norbert Wiener pointed out as early as 1948 that the essence of control is not command but information feedback. The author's "Risk Control Triangle"—Predictability (feedforward), Intervenability (real-time feedback), Recoverability (post-facto correction)—precisely covers the complete timeline of a feedback loop in control theory.

However, the author's thinking transcends pure cybernetics. In Software Engineering Architecture for Module-Level Human-Machine Collaboration, he proposes a more radical proposition: And why must the human position be human? It is actually a SuperVisor. This hints at a posthumanist possibility—when the trust mechanism is sufficiently robust, the supervisor itself could also be an AI.

This forms an interesting parallel with Foucault's theory of power. Foucault argued that modern power is not top-down repression but "disciplinary" power diffused through institutions and norms. The multi-level arbitration mechanism the author designs—a hierarchical structure of Implementation Agents, Testing Agents, and Arbitration Agents—is precisely a "disciplinary" power architecture, but its purpose is not repression but producing trust through institutionalized checks and balances.

Deeper Interpretation

The author's thinking on control and trust reveals a deeper philosophical question: Can subjectivity be realized in a distributed manner?

In traditional philosophy, subjectivity is unified and indivisible—Descartes' "I think, therefore I am" presupposes a single thinking subject. But in the author's framework, "intent" is fractally decomposed across multiple Agents, each possessing a local understanding of intent and alignment detection capability. This implies that subjectivity is no longer a point but a network; no longer an entity but an emergent property.

This idea is also reflected in the investment practice of The Capital Long Game: the author insists on using algorithmic trading, completely delegating execution-level decisions to machines, with humans only responsible for strategy design and parameter optimization. He writes: "Don't stare at the screen, don't agonize over whether to buy or sell in every single trade. That doesn't liberate you; it tortures you." This is a conscious contraction of subjectivity—gaining greater freedom at a higher level of abstraction by relinquishing control over details.

Proposition Three: The Spiral of Cognition — Complexity is Inescapable

The Problem Posed

In an age of information explosion, people crave shortcuts. Can one gain wisdom by reading others' summaries? Can one become a master by imitating a master's actions? Can one skip the arduous climb of cognition with AI assistance?

The author gives a resounding negative in Returning to Simplicity: Complexity is the Inevitable Path of Cognition:

"You cannot become a master by imitating a master's actions."

The Position in the Texts

The author borrows Oliver Wendell Holmes Jr.'s famous dictum to distinguish two radically different kinds of "simplicity": simplicity on this side of complexity (naivety without having experienced complexity) and simplicity on the other side of complexity (returning to simplicity after traversing complexity).

Drawing from his own AI programming experience, he describes a typical cognitive collapse process: having AI build a project from scratch, and after a few iterations, engineering quality begins to spiral out of control—"new features can't be added, old code can't be cleanly deleted, zombie interfaces retained everywhere for the sake of 'compatibility'." The root cause: The AI hasn't experienced the evolution of this project; it doesn't understand which abstractions are core and which are temporary expedients.

This observation is elaborated in more detail in The Great Failure of Vibe Coding. The author finds that the object-oriented code written by AI is of extremely poor quality—"every new feature just creates a new class for me, then punches a hole in other related classes to call it"—this isn't object-oriented programming but "requirement-list-oriented programming." The fundamental reason: Good abstraction must be built upon a deep understanding of the problem domain, and such understanding can only be gained through wrestling with complexity.

The author further proposes that the complexity phase grants us three irreplaceable things:

1. The experience of failure — Many principles cannot be understood without personally stepping into pitfalls.
2. A complete mental model — A map knowing which paths lead through and which are dead ends.
3. Intuitive judgment — A byproduct of long-term immersion in complexity.

Philosophical Parallels

This thought resonates deeply with Hegelian dialectics. Hegel believed that truth is not a static proposition but a process—a spiral ascent of thesis, antithesis, and synthesis. What the author calls "returning to simplicity" is precisely "sublation" (Aufhebung) in the Hegelian sense: not simply returning to the starting point, but regaining the simplicity of the starting point at a higher level while retaining all the gains of the intermediate process.

From a phenomenological perspective, the author's emphasis on "being present" ("be 'present,' but don't 'go all-in'") echoes Husserl's "back to the things themselves." Cognition cannot be acquired through second-hand information; it must come through first-person experience. But the author is more pragmatic than Husserl—he proposes a "distance decay effect" regarding the cost of cognition:

"Accidents that happen far away—others' failure cases—can only make one sigh; the cognitive impact is weak. Accidents that happen nearby—colleagues' pitfalls—are sufficiently impressive. Accidents that happen to oneself—engraved in bone and heart, but the cost is greatest."

Therefore, the optimal strategy is: Use controllable small-scale real trading to obtain sufficiently close cognitive impact. This is consistent with the risk-control philosophy of The Capital Long Game—trading controllable small losses for leapfrog growth in cognition.

Deeper Interpretation

An important criterion is implicit in the author's epistemology: Are you investing attention and harvesting cognition? He distinguishes between "traversing complexity" and "escaping complexity"—reading many books but letting information just flow by, doing simulated trading without serious review, copying others' code without understanding why—the commonality of these behaviors is that "attention is not truly invested, or experience is had but cognition is not harvested."

This criterion carries profound ethical implications. It means that cognitive honesty—truly facing complexity rather than pretending to understand—is a moral obligation. In The Core of AI Autonomy is the Alignment of Scientific Views, the author extends this principle to AI system design: every design decision of an AI must be supported by "third-party verifiable facts," and the method of verifying facts is "executable experiments." This is the epistemological version of Occam's Razor—Do not add beliefs without experimental verification.

Is the "simplicity" of a person who has never left their hometown the same as that of one who has traveled the world and chosen to return? The author's answer: The latter's simplicity is chosen simplicity—"They know what they have given up and why they chose to stay." This consciousness of choice is the ultimate harvest of traversing complexity.

Proposition Four: The Generativity of Existence — Safeguarding the Non-Replicable in an Age of Replicability

The Problem Posed

When AI can write faster, reason more accurately, and remember more comprehensively, where is human value anchored? When data, models, and interaction patterns are all replicable, what is non-replicable?

This is the most unsettling philosophical question of the AI era and the core inquiry the author confronts head-on in On the Essence of Humanity.

The Position in the Texts

The author proposes a concise yet profound assertion: The uniqueness of human subjectivity is rooted in the non-replicability of the memory carrier.

"Our memories, experiences, emotions, and bodily sensations are interwoven into a web that cannot be completely detached or precisely replicated. Even if future brain-computer interfaces can read neural signals, that quality of 'experiencing the world from within' remains private, one-time." — On the Essence of Humanity

AI's memory carrier is concrete and replicable—data, weights, code. Therefore, AI's subjectivity is replicable. But human subjectivity is non-replicable because it is rooted in one-time, irreversible life experiences.

Building on this, the author constructs a complete "system of articulation":

• LOGS: As the "historical artifact" raw stone—the unedited path taken, recording the truth of each moment, including errors, hesitations, and immature impulses.
• INSIGHTS: As the "polishable crystal" arc—crystallized thoughts after repeated polishing, growing from the soil of LOGS.

Their relationship is like raw stone and gemstone: one preserves history, the other presents thought. In On the Essence of Humanity, the author even tentatively defines "soul": The sum of reasoning ability and memory. But he immediately adds that this definition itself is mutable—"It will update with my understanding. This precisely echoes the essence of humanity: we are not fixed existences but ongoing processes of becoming."

Philosophical Parallels

The author's thought on "generativity" resonates deeply with Henri Bergson's concept of "duration" (durée). Bergson argued that real time is not the quantifiable, homogeneous time of physics but an indivisible, continuously creative stream of consciousness. Each moment is entirely new, irreducible to the sum of previous moments. What the author calls the "non-replicable trajectory of becoming" is precisely duration in the Bergsonian sense—its value lies not in the content of any single moment but in the irrepeatability of the entire flowing process.

From an existentialist perspective, the author's discussion of "taste" is particularly brilliant. In On the Essence of Humanity, he proposes: The essence of taste is the capacity to refuse. Taste is not "I like A," but "I am willing to give up B, C, D for A." The prerequisite for taste is affluence—affluence of time, resources, cognition. Without affluence, there is only survival.

This forms a subtle dialogue with Sartre's concept of "choice." Sartre believed humans are "condemned to be free"—we must choose, even not choosing is a choice. But the author points out a precondition Sartre overlooked: Choice requires affluence. A person starving to death cannot exhibit taste in food. Therefore, in the author's framework, freedom is not a priori but needs to be manufactured—by controlling the rate of loss to manufacture investment affluence, by using algorithmic trading to manufacture cognitive affluence, by using AI assistance to manufacture time affluence.

Deeper Interpretation

The author redefines the coordinates of meaning for personal existence in the AI era. He points out that AI instrumentalizes traditional coordinates of meaning like "intelligence," "efficiency," and "breadth of knowledge"—when machines surpass humans in these dimensions, existence anchored to them collapses.

The path to reconstruction involves three fundamental shifts:

1. From "worship of results" to "honesty of process" — Value lies not in the perfection of conclusions but in the authentic texture of thought.
2. From "catering to systems" to "articulating for oneself" — Not to please any system (including AI), but to clarify one's own cognitive map.
3. From "pursuing replicable correctness" to "safeguarding non-replicable becoming" — Your value lies not in becoming a more optimized tool, but in being the faithful recorder and reflector of this process of becoming.

In Future Software's Demand-Side Growth Points, the author pushes this idea to the societal level: In the AI era, personal taste and authenticity will become decisive competitive advantages. He writes: "One must purely be oneself to win the recognition of one's peers." This is not a platitude but a serious ontological proposition—when everything imitable can be better imitated by AI, the only thing non-imitable is the fact of you being yourself.

Spiritual Portrait: A Thought Topography of a Technical Philosopher

Based on an in-depth analysis of the 68 documents, we can outline the intellectual characteristics of this author:

Epistemological Stance: A Constructivist Experimenter

The author's epistemology is thoroughly constructivist—knowledge is not discovered but constructed; understanding is not imparted but experienced. In a discussion with his friend Hobo, he self-identifies as "the pragmatism of an engineer," complementing Hobo's "the foresight of a researcher" (LOGS/9).

But this constructivism is not relativism. The author insists on falsifiability as the criterion for knowledge—in The Core of AI Autonomy is the Alignment of Scientific Views, he demands that every design decision be supported by "third-party verifiable facts," with verification being "executable experiments." This is a combination of Popperian philosophy of science and pragmatism: truth is not absolute but can be progressively approximated through experiment.

In the investment domain, this stance manifests as an obsession with backtesting. In The Capital Long Game, he constructs a complete mathematical framework to evaluate strategies and translates it into an executable experimental plan in The Capital Long Game Experimental Design. Theory must withstand the test of experiment—this is his unshakable epistemological baseline.

Ontological Tendency: Process Philosophy and Emergentism

The author's ontology leans toward process philosophy—the world is not composed of static entities but of dynamic processes. This tendency manifests on multiple levels:

• Market Ontology: In The Three-Body Dynamics Hypothesis of Capital Markets, the market is understood as a dynamic interaction system of three types of capital, its behavior an emergent result, not a preset rule.
• Human Ontology: In On the Essence of Humanity, humans are defined as "ongoing processes of becoming," not fixed entities.
• AI System Ontology: In Embracing 'Finite', Designing 'Infinite', intelligence is understood as an emergent property of finite units within an infinite system.

This process ontology naturally inclines the author toward systems thinking—he focuses not on the properties of individual elements but on the relationships and interactions between them. The Three-Body Dynamics model is a paradigm of this thinking: the behavior of each capital type is simple, but their interaction produces chaos, phase transitions, and unpredictability.

Ethical Orientation: Ethics of Responsibility and Ethics of Honesty

The author's ethics can be summarized by two core principles:

First, the Ethics of Responsibility. In The Capital Long Game, he "firmly opposes any strategic outcome that 'traps the individual in the market forever,'" considering it "an immense waste of human life and social resources." Investment must have clear victory conditions and exit mechanisms—this is not only a strategic requirement but an ethical response to the finitude of life.

Second, the Ethics of Honesty. In On the Essence of Humanity, he defines "admitting mistakes" as a "necessary survival strategy"—"admitting small mistakes doesn't hurt, but making big ones is hard to recover from." The design philosophy of the LOGS system is the institutionalization of this ethics of honesty: mistakes are not erased but receive new timestamps, forming a trajectory of growth. He admits frankly: "The loop of denial and admission still fights within my heart... but 'I eventually reacted.' Accepting delayed honesty is itself a form of honesty."

Axiological Characteristics: The Trinity of Affluence, Taste, and Freedom

The author's axiology revolves around a core concept: Affluence.

Affluence is the prerequisite for taste (without affluence, there is only survival), taste is the expression of freedom (the essence of taste is the capacity to refuse), and freedom is the foundation of meaning (only a freely chosen life has meaning). Therefore, creating affluence becomes the prerequisite for the realization of all value—whether by controlling the rate of loss to create investment affluence or by using AI assistance to create cognitive affluence.

This axiology is presented dramatically in The Qi Pa Shuo Debate: the steady growth faction represents "safety but lack of affluence," while the class-leap faction represents "risk but creating affluence." The author's stance clearly leans toward the latter—but not blind risk-taking, but disciplined risk-taking constrained within a mathematical framework.

It is worth noting the author's self-definition in the README: "Understanding everything is my meaning." This is an exceptionally pure epistemological value declaration—meaning lies not in possession, not in achievement, but in understanding. This echoes Aristotle's "theoretical life" (bios theoretikos) from afar, yet bears distinct modern characteristics: understanding is not contemplation but a dynamic process of constant approximation through practice, experiment, and reflection.

Conclusion: Significance and Implications

Implications for the Reader

Perhaps the most profound implication of these texts is: Philosophy is not a luxury of the study but a necessity of practice.

The author never claims to be a philosopher, yet in quantitative trading he touches the core problem of existentialism (finitude and transcendence), in AI collaboration he reinvents the basic principles of cybernetics (feedback and trust), in programming practice he verifies Hegelian dialectics (the spiral ascent of complexity), and in personal knowledge management he responds to Bergson's philosophy of duration (non-replicable generativity).

This suggests: The best philosophical thinking often emerges not from philosophical texts but from real struggle with the world. When a person seriously confronts their own situation—finite time, finite resources, infinite desire—they are compelled to become a philosopher.

Significance for the Era

We are at a unique historical juncture: AI capabilities are growing at an exponential rate, while human understanding of the meaning of our own existence lags far behind. The author's thinking provides a valuable frame of reference:

1. Finitude is not a defect but a design principle. In Embracing 'Finite', Designing 'Infinite', the author argues for the paradigm of "finite agents, infinite system." This idea applies not only to AI system design but also to the organization of human society—acknowledging everyone's finitude while realizing collective infinite possibilities through institutional design.
2. Trust can be engineered. In an era of deepening human-machine collaboration, the "Controllable Trust" framework proposed in How to Solve the Human Desire for Control offers a middle path for human-AI coexistence that is neither blindly trusting nor excessively fearful.
3. In an age of replicability, non-replicability is value. When AI can generate text of any style or code of any type, On the Essence of Humanity reminds us: what is truly valuable is not the perfection of the output but the unique trajectory of becoming behind it.

Unresolved Questions

However, these texts also leave some deep, unresolved questions:

First, is "understanding everything" a possible goal? The author himself admits that understanding is an "undecidable endpoint." If understanding can never be completed, is a life that takes understanding as its meaning destined to be Sisyphean labor? Or, as the author hints, is the process itself the purpose?

Second, when AI becomes sufficiently powerful, does "non-replicable generativity" still hold? The author anchors human uniqueness in the "non-replicability of the memory carrier," but if future brain-computer interfaces can completely read and replicate neural states, would this argument collapse? The author maintains a cautiously open attitude toward this—"When a person can be completely replicated, that is already digital immortality, a different form of existence."

Third, is the philosophical premise of "The Capital Long Game" universally valid? The author assumes the fundamental goal of individual investors is "class leap," but is this goal itself worth pursuing? In The Qi Pa Shuo Debate, mentor Liu Qing poses a sharp counter-question: "Is this narrative of 'class leap' itself a fantasy woven by consumerism?" The author has not yet answered this question directly.

Fourth, where are the boundaries of the ethics of honesty? The author advocates "admitting mistakes" and "honesty of process," but in fiercely competitive markets, would complete transparency become a strategic disadvantage? He claims in The Capital Long Game that this is a "publicly shareable strategy," but would making it public itself alter the strategy's effectiveness?

There are no simple answers to these questions. But perhaps, posing the right questions is itself more valuable than giving wrong answers. As the author writes in the README: "Understanding everything is my meaning." On this endless road of understanding, every unresolved question is a new starting point.