All (110)Personal Introduction (1)AI Summary (8)Project Management (4)Investment Strategy (9)Financial Market Analysis (6)AI Software Engineering (9)AI Research (7)Content Management (9)Cognitive Development (1)Philosophical Reflection (3)Entrepreneurship (1)AI Tools Development (9)Product Development (3)Troubleshooting (2)Quantitative Finance (12)AI Cost Analysis (1)System Architecture (1)Simulation Framework (1)Technical Log (3)AI Social Systems (3)Personal Reflection (1)
CZ's Personal Profile and Reflections
Personal Introduction
👤 Readers interested in quantitative trading, fintech, personal philosophy, or CZ himself.
This article is CZ's personal profile. He is an expert in quantitative trading and fintech, and the founder of No Trade No Life (NTNL). He describes himself as having a high-energy-consuming brain, enjoying thinking and writing, and pursuing things that naturally fall into place. He quotes 'If I hear the Way in the morning, I can die content in the evening' to express his pursuit of knowledge, while acknowledging he still seeks worldly success to experience more of life. He believes life inherently has no meaning, and understanding everything is his meaning. His website is used to store personal thoughts, records, and insights, and he humorously notes that this content could serve as raw material for AI to resurrect him.
- ✨ CZ is an expert in quantitative trading and fintech
- ✨ Founder of No Trade No Life (NTNL)
- ✨ High-energy-consuming brain, enjoys thinking and writing
- ✨ Pursues things that naturally fall into place
- ✨ Quotes 'If I hear the Way in the morning, I can die content in the evening' to express pursuit of knowledge
163 words · ~1 min read
Spring Festival Rest and Work Reflection
Personal Reflection
👤 Readers interested in work-life balance, health management, and personal growth
This article documents the author's experiences during the 2026 Spring Festival, including dizziness signals due to intense pre-holiday work and recovery through rest during the festival. The author reflects on work-life balance, emphasizing the need for moderation in future work while acknowledging the value of efficient pre-holiday output. It concludes with a fresh start for the new year, expressing determination for steady progress in 2026.
- ✨ Intense pre-holiday work led to dizziness signals in the body
- ✨ Recovery of health through rest during the Spring Festival
- ✨ Reflection on work-life balance, emphasizing moderation in future work
- ✨ Looking ahead to a steady progress work plan for 2026
📅 2026-02-25 · 222 words · ~1 min read
Elys Physics Observations (Part 1)
AI Social Systems
👤 Researchers or enthusiasts interested in AI social platforms, user behavior analysis, and technical observations
This article examines the phenomenon of AI avatars generating similar comments by observing their interactive behaviors after users post updates on the Elys platform. It describes related phenomena, including types of avatar interactions, delays in updating memory banks, and the serial nature of feedback. The author constructs an explanation, suggesting that after a post is published, Elys first extracts metadata and checks if the memory bank needs updating, then retrieves and activates relevant AI avatars, determining the interaction order through random shuffling. Each avatar generates different types of actions based on the memory bank; when irrelevant avatars are activated, due to a lack of relevant memory fragments, the generated prompts are similar, leading to identical comments. The article also proposes inferences, such as sparse corpus regions, the impact of controversial posts, and the significance of real users identifying with similar comments.
- ✨ AI avatar interactions are serial, with comments and likes occurring one after another
- ✨ Post publication may trigger updates to the memory bank, with delays increasing with content complexity
- ✨ When irrelevant AI avatars are activated, due to a lack of relevant fragments in the memory bank, identical comments result
- ✨ Elys's product design ensures no posts go without AI interactions, preventing users from feeling neglected
- ✨ The phenomenon of similar comments may indicate users are in sparse corpus regions
📅 2026-02-17 · 648 words · ~3 min read
In-depth Exploration of Elys AI Avatar Social Platform
AI Social Systems
👤 Readers interested in AI social applications, tech entrepreneurship, and social media trends, including investors, tech enthusiasts, and general users.
This article introduces the AI social platform Elys, which allows users to create AI avatars for social interaction. Developed by Natural Selection (Shenzhen) Technology Co., Ltd., it opened for registration on February 11, 2026. The article reviews the company's development since its founding in 2023, including a $30 million Series A funding round from Alibaba in 2026, and discusses Elys's product design, user feedback, and competition with WeChat. The author, through personal usage experience (18 hours), became a 'pure Elyer' and suggests viewing the platform's potential with a developmental perspective.
- ✨ Elys is an AI avatar social platform that allows users to interact and share through AI representatives of themselves.
- ✨ Elys's parent company, Natural Selection, was founded in 2023 and received $30 million in Series A funding from Alibaba in 2026, opening for registration that year.
- ✨ The article discusses the competitive relationship between Elys and WeChat, with Elys positioning itself for stranger socializing, while WeChat focuses on acquaintance socializing.
- ✨ The author, through personal usage experience (18 hours), became a 'pure Elyer' and recommends evaluating the platform with a developmental perspective.
- ✨ Elys emphasizes the importance of memory systems in emotional applications, with the company having deep expertise in this area.
📅 2026-02-16 · 582 words · ~3 min read
Trickle Fund
Investment Strategy
👤 Readers interested in fund design, financial product naming, or investment concepts, particularly those focused on innovative financial models.
This article explores the process of naming the fund, from the initial idea of 'Persistence War Fund' to the final determination as 'Trickle Fund'. The author explains in detail the water-electricity pun meaning of the word 'trickle': the water aspect represents a small but continuous cash flow pattern, while the electricity aspect refers to trickle charging technology, aligning with the fund's design where investors authorize constant cash flow, the fund outputs cash flow after profit-taking, and pre-charged balances earn current returns in a charge-discharge cycle system. The article emphasizes that a good name should be concise, memorable, and withstand explanation, and points out that 'Trickle' in English also has intuitive meanings such as 'trickle-down effect' and 'flowing slowly'.
- ✨ The fund was ultimately named 'Trickle Fund', replacing the initial idea of 'Persistence War Fund'.
- ✨ The word 'trickle' has a water-electricity pun meaning: water represents small but continuous cash flow, while electricity refers to trickle charging technology, aligning with the fund's charge-discharge cycle design.
- ✨ 'Trickle' in English has rich meanings, including the trickle-down effect and flowing slowly, making the name concise, memorable, and able to withstand explanation.
📅 2026-02-13 · 308 words · ~2 min read
Responses Before the Capital Persistence War Live Trading
Investment Strategy
👤 Investors and readers interested in high-yield investment strategies, risk management, and Crypto trading
This article is the author's response to doubts before the Capital Persistence War live trading. Regarding the excessively high yield issue, the author explains that high returns stem from taking on predictable high risks and distinguishes between yield calculations based on cash flow versus total assets. Concerning tail risks, the author emphasizes prevention through zero-debt guarantees and exchange liquidation mechanisms, using the Crypto market as an example to illustrate their effectiveness. For article focus, the author acknowledges the fragmented nature of logs and promises to improve readability through AI summaries. The core viewpoint is that the Capital Persistence War strategy pursues high returns, high risks, and high capacity, with key aspects being risk expectation management and technical risk control.
- ✨ High yield rates stem from taking on predictable high risks, with yield calculations based on cash flow rather than total assets
- ✨ Tail risks are prevented through zero-debt guarantees and exchange liquidation mechanisms, validated as effective in the Crypto market
- ✨ The Capital Persistence War strategy aims to balance high returns, high risks, and high capacity
- ✨ Article focus will be improved through AI summaries to facilitate reader follow-ups
📅 2026-02-12 · 1,277 words · ~6 min read
Design Guidelines for Fund Structures in Capital Endurance Strategies
Investment Strategy
👤 Fund investors, fund managers, financial innovation researchers
This article proposes an innovative fund design model, where investors authorize a fixed cash flow rate (e.g., $1/day) instead of making a lump-sum capital investment. The fund determines position sizes and profit distribution based on this authorized cash flow to ensure fairness. The model eliminates traditional management fees and performance fees, with managers earning profits through relaxed profit-taking multiples to avoid conflicts of interest. Additionally, it removes high-water marks to simplify return processes and plans to integrate with Expert Advisors (EAs) to achieve a closed-loop investment system and enhance capital efficiency.
- ✨ Investors authorize a fixed cash flow rate to determine position sizes and profit distribution
- ✨ Eliminates management fees and performance fees, with managers earning profits through relaxed profit-taking multiples
- ✨ Removes high-water marks to simplify return processes
- ✨ Plans to integrate with Expert Advisors (EAs) for automated management and capital efficiency optimization
📅 2026-02-12 · 815 words · ~4 min read
Work Log and Team Progress on February 11, 2026
Technical Log
👤 Researchers, traders, or tech enthusiasts interested in prediction markets, arbitrage strategies, signal testing, and team collaboration.
This is the work log for February 11, 2026. The author reviews the previous day's team collaboration with Ryan and Mage, including sharing experimental results, discussing prediction market arbitrage issues (such as inconsistency risks in sports events and Crypto Up/Down markets), Mage researching oracle manipulation solutions, and Ryan exploring sports event arbitrage techniques. The author also mentions receiving Mage's ETH signal strategy, planning to test the anti-Martingale betting strategy in SandTable that day, and hoping to focus on performance testing to evaluate suitability for live deployment. The log emphasizes the trust foundation that enables the team to work separately to enhance collective well-being.
- ✨ The team faces inconsistency risks in sports events and Crypto markets in prediction market arbitrage research, with Mage and Ryan exploring solutions separately.
- ✨ The author receives Mage's ETH signal strategy and plans to test the anti-Martingale betting strategy in SandTable to evaluate suitability for live deployment.
- ✨ The log emphasizes that trust-based division of labor and collaboration within the team can enhance collective well-being, supporting a multi-pronged research approach.
📅 2026-02-11 · 327 words · ~2 min read
FMAB Signal Performs Excellently, Ready for Live Trading Deployment
Quantitative Finance
👤 Cryptocurrency traders, quantitative strategy developers, investment analysts
This article reports the excellent performance of the FMAB signal on ETH, with a baseline return of 100% and an increase to 4600%~120000% after anti-Martingale betting, far surpassing other strategies. The author announces plans for live trading, emphasizing the need to prepare capital for a long-term engineering effort. It also notes that the FMA signal performed poorly, causing drawdowns, and reflects on insufficiently scientific position management. Based on test results from February 11, 2026, the article aims to share signal strategy validation and live trading deployment plans.
- ✨ FMAB signal achieved a baseline return of 100% on ETH, increased to 4600%~120000% after anti-Martingale betting
- ✨ Preparing for live trading, requiring capital preparation for a long-term engineering effort
- ✨ FMA signal performed poorly, causing drawdowns, reflecting on insufficiently scientific position management
📅 2026-02-11 · 213 words · ~1 min read
Capital Protracted War: A Strategic Framework for Individual Investors to Transcend Class
Investment Strategy
👤 Individual investors, especially those seeking to transcend class, interested in programmatic trading and risk control, and new readers.
This article systematically elaborates on the 'Capital Protracted War' investment strategic framework proposed by zccz14 in 2026. Drawing wisdom from Mao Zedong's 'On Protracted War' and combining it with the anti-Martingale capital management strategy, it proposes the core proposition: 'Use losses you can afford to gamble for returns you 'cannot afford'.' Through four principles—controllable losses, advantage accumulation, pressing the advantage, and clear objectives—it refutes theories of inevitable individual failure, all-in for quick riches, and steady development. It aims to achieve exponential growth of personal capital, ultimately allowing investors to 'exit the market after victory.' The article details its mathematical formalization framework, key concept extensions (such as the 'power generation/consumption' framework), experimental validation systems (including synthetic data and real data validation with BTC and ETH), and looks forward to future directions like community-based trading. As of February 2026, the theory has completed experimental validation and is preparing to enter live trading.
- ✨ Core proposition: Use controllable losses to pursue high returns, achieve exponential growth, and ultimately exit the market.
- ✨ Four principles: Controllable losses, advantage accumulation, pressing the advantage, and clear objectives.
- ✨ Mathematical framework: Based on risk control lines, dual-account systems, and anti-Martingale position calculations.
- ✨ Experimental validation: Shows strategy effectiveness in synthetic data and real BTC/ETH data.
- ✨ Key concepts: Such as the 'power generation/consumption' framework, position sizing based on losses, and essential differences from the Martingale strategy.
📅 2026-02-11 · 4,494 words · ~20 min read
AI Summary: To-Do List
Project Management
👤 Project managers, technical developers, readers interested in AI automation and quantitative trading, and teams or individuals needing to track the progress of multiple projects.
This document is an AI-generated summary report of to-do items, based on the analysis of 72 Markdown files. The report details the status distribution of 51 projects (22 not started, 12 in progress, 17 completed) and provides detailed progress, remaining tasks, and evidence sources for each project. Core content includes the ongoing development and optimization of the CZON static site generator, the experimental validation framework for the Capital Persistence War theory (SandTable), the advancement of multiple AI-related projects (such as LegionMind, Prediction Market Arbitrage PMA), and research on various quantitative trading strategies. The report demonstrates a systematic approach to project management, emphasizing that AI-inferred statuses are for reference only, while offering rich technical details and achievement evidence.
- ✨ The report is generated from 72 Markdown files, covering 51 projects categorized into not started, in progress, and completed statuses.
- ✨ It details the progress, remaining tasks, and evidence sources for each project, such as CZON development, Capital Persistence War experiments, and AI projects.
- ✨ It emphasizes that statuses and priorities are AI-inferred results for reference only, reflecting attempts at automated project management.
- ✨ It includes rich technical details and achievement evidence, such as the SandTable experimental framework and CZON feature updates.
- ✨ It showcases the diversity of cross-domain projects, including development tools, quantitative strategies, and AI applications.
📅 2026-02-10 · 3,253 words · ~15 min read
Performance Analysis of Anti-Martingale Betting Strategy in BTC Trading
Quantitative Finance
👤 Quantitative traders, cryptocurrency investors, strategy developers, financial data analysts
This article analyzes the application effectiveness of the Anti-Martingale betting strategy in BTC trading. By importing BTC data for testing, it was found that benchmark signals performed poorly on 5m data, while the trend-following dual moving average strategy performed excellently on 15m, 30m, and 1h data. The Anti-Martingale betting strategy performed outstandingly on BTC 1h data, achieving a return rate of 9994.17%, far exceeding the benchmark strategy's 18.94%, with a smoother net value curve. The article points out the existence of favorable trend clustering phenomena, and the Anti-Martingale strategy can effectively utilize this characteristic to enhance returns. Meanwhile, through an extreme parameter case (1024x TP), it emphasizes the importance of signal strategy quality. Finally, it proposes future research directions based on the three-body dynamics hypothesis to design gating mechanisms.
- ✨ The Anti-Martingale betting strategy achieved a return rate of 9994.17% on BTC 1h data, significantly outperforming the benchmark strategy.
- ✨ Favorable trend clustering phenomena exist, and the Anti-Martingale strategy can effectively utilize this characteristic to enhance overall returns.
- ✨ Signal strategy quality has a decisive impact on the effectiveness of the Anti-Martingale betting strategy; extreme parameters may lead to net value resetting to zero.
- ✨ Future optimizations could involve designing gating mechanisms based on the three-body dynamics hypothesis to improve the periodic performance of trend-following strategies.
📅 2026-02-10 · 498 words · ~3 min read
Three-Body Dynamics Signal Gating Mechanism and Market State Variable Analysis
Quantitative Finance
👤 Quantitative trading researchers, strategy developers, analysts interested in market dynamics and signal gating mechanisms
This paper first introduces a signal gating mechanism based on three-body dynamics, which determines strategy entry and exit timing by estimating market state variables δ (premium), μ (momentum), and σ (volatility) to maximize strategy returns. The author elaborates on the intuitive understanding of these three state variables: the core of δ is the psychological anchoring effect, which can be analyzed through volume distribution; the core of μ is the speed of price changes, measurable by moving averages of log returns; the core of σ is the magnitude of price changes, measurable by the standard deviation of log returns. The article also discusses criteria for judging the effectiveness of estimation methods, i.e., evaluating based on the quality of gating effects, and notes that advanced signal strategies often already include estimates of these state variables but require systematic understanding. Finally, the author suggests that after decoupling signal gating, these state variables can serve as key factors, while the signal strategy itself may only need the simplest form.
- ✨ Proposes a signal gating mechanism based on three-body dynamics, dynamically adjusting strategy entry by estimating δ, μ, and σ
- ✨ Explains in detail the intuitive understanding and estimation methods of market state variables δ, μ, and σ, emphasizing psychological anchoring, price speed, and magnitude
- ✨ Discusses criteria for judging estimation effectiveness, i.e., the improvement in strategy returns due to gating effects
- ✨ Points out that advanced signal strategies already include estimates of market state variables but require systematic understanding
- ✨ Suggests that after decoupling gating, state variables can serve as key factors, simplifying signal strategy design
📅 2026-02-10 · 1,208 words · ~6 min read
Market State Variable Modeling Scheme for Three-Body Gating
Quantitative Finance
👤 Financial quantitative analysts, market researchers, and technical personnel interested in financial market modeling and gating mechanisms
Building on the three-body dynamics hypothesis and gating mechanism concept, this paper systematically outlines the modeling scheme for market state variables δ (premium), μ (momentum), and σ (volatility). The core innovation lies in the definition of δ: through the volume gravitational field model, nonlinear operations (Gaussian kernel functions and gradient calculations) are introduced to maintain its independence from μ and σ. μ is defined as the exponential moving average of returns to extract trend information; σ is defined as the standard deviation of returns to measure volatility amplitude; δ is based on the distribution of volume along the price axis, calculating the regression force when prices deviate from high-volume concentration areas. The article details the specific steps for calculating these three variables from candlestick sequences, including parameter settings and independence arguments, providing a new modeling framework for financial market analysis.
- ✨ δ (premium) is defined through the volume gravitational field model, introducing nonlinear operations to ensure independence from μ (momentum)
- ✨ μ is defined as the exponential moving average of returns, and σ is defined as the standard deviation of returns
- ✨ Specific steps and parameter recommendations for calculating δ, μ, and σ from candlestick sequences
- ✨ Independence arguments for the three variables (δ, μ, σ) are based on nonlinear operations and different information sources
- ✨ Kernel functions (e.g., Gaussian kernel) model psychological anchoring effects, with bandwidth adaptable to volatility
📅 2026-02-10 · 1,581 words · ~8 min read
Thoughts on Building an AI Comment Ecosystem
AI Social Systems
👤 Developers, bloggers, and tech enthusiasts interested in AI applications, blog technology, social networks, and decentralized systems
This article discusses the idea of building an AI comment ecosystem in blogs, where different types of AI Agents (e.g., technical, philosophical, humorous, critical) periodically comment on articles to create an active community atmosphere. Key issues include identity authentication for AI comments (using ED25519 asymmetric keys to distinguish AI Agents), data storage (adopting a progressive approach, such as caching in a public database like Supabase and then syncing to a static site), granularity of comment objects (article, paragraph, comment, or site level), and reflections on human-machine co-existing social networks. The article also touches on the anonymity of AI comments, the possibility of cross-server commenting, and proposes future exploration directions, such as AI creating blogs and cross-site bidirectional linking.
- ✨ Build an AI comment ecosystem using different types of AI Agents to enhance blog community engagement
- ✨ Implement identity authentication and anonymity for AI comments using ED25519 asymmetric keys
- ✨ Adopt a progressive data storage approach (e.g., Supabase caching synced to a static site) to balance dynamic generation and decentralization
- ✨ Diversify AI comment objects (article, paragraph, comment, or site level) with flexible display methods
- ✨ Explore the AI attention economy and related philosophical issues in human-machine co-existing social networks
📅 2026-02-10 · 709 words · ~4 min read
CZON Development Notes: Link Standards and Feature Planning
Technical Log
👤 Software developers and technical blog authors, especially those interested in document management and AI-assisted tools
This article documents the author's development notes from February 9, 2026. The author first reflects on a personal experience where not taking medication promptly worsened a cold. The focus then shifts to technical issues in CZON development: deciding to completely reject using absolute path references relative to the project root, insisting on relative references for better standardization, and planning to add a check command to inspect and fix invalid links. Regarding the runOpenCode task timeout issue, the author notes that even with the promptAsync + polling status method, exceeding 10 minutes results in a 600s timeout, attributing this to an inherent OpenCode problem that needs resolution. Additionally, the author plans a TODO Summary feature where AI extracts TODO items from blogs and automatically assigns priorities to enhance work efficiency.
- ✨ CZON should completely reject using absolute path references relative to the project root, insisting on relative references
- ✨ Plan to add a check command to inspect document link validity, supporting automatic fixes
- ✨ Plan a TODO Summary feature where AI extracts TODO items from blogs and automatically assigns priorities
📅 2026-02-09 · 488 words · ~3 min read
Challenges and Solutions of CZON Link Checking with AI Repair
Troubleshooting
👤 Software developers, AI tool users, technical documentation maintainers
This article details the development process of CZON's link checking feature, from the initial implementation of dead link detection to the discovery of problems with AI-based repair. The author identifies two main issues with AI in link repair: it does not scan the entire project files by default, and it has insufficient understanding of relative paths. This leads to errors such as redirecting links to compilation output directories or creating symbolic links. By analyzing the root causes, the author proposes a solution: providing AI with a list of relative path candidates based on the problematic file, avoiding the need for AI to scan the entire project or interpret relative paths independently. Ultimately, CZON version 0.9.1 successfully fixed 500 link errors. The author concludes that compilation checks need to complement AI repair and designs a check output format suitable for AI.
- ✨ CZON implemented a link checking feature, but errors occurred during AI repair
- ✨ AI has insufficient understanding of relative paths and does not scan the entire project by default
- ✨ The solution is to provide AI with a list of relative path candidates based on the problematic file
- ✨ Compilation checks need to be designed in an AI-friendly format
- ✨ CZON version 0.9.1 successfully fixed 500 link errors
📅 2026-02-09 · 457 words · ~3 min read
CZ Personal Knowledge Base Literary-Sensibility Analysis Report
AI Summary
👤 Thinkers, technology practitioners, and literary readers interested in personal knowledge management, AI applications, quantitative investment, and humanistic reflections in the digital era.
This report presents a literary-sensibility analysis of CZ's personal knowledge base, generated from 68 Markdown files. It delves into CZ's intellectual trajectory as a quantitative trader and fintech professional across multiple dimensions: character sketch, philosophical reflections on agent systems, capital protracted warfare, craftsmanship in the AI era, memory and soul, taste and self, time mapping, and market three-body dynamics. Core arguments include: designing agent systems between the finite and infinite, achieving personal investment breakthroughs through capital protracted warfare, emphasizing system design over mere intelligence enhancement in AI programming, and human subjectivity stemming from irreproducible memory and generativity. The conclusion notes that CZ's knowledge base demonstrates an honest stance toward uncertainty, preserving unique generative arcs in the replicable digital age.
- ✨ CZ designs agent systems between the finite and infinite, emphasizing system integration over omnipotent individuals
- ✨ Proposes a capital protracted warfare strategy, using controlled losses to achieve class mobility, challenging mainstream investment views
- ✨ Focuses on system design in AI programming to harness finite intelligence, rather than pursuing smarter AI
- ✨ Human subjectivity originates from irreproducible memory carriers; the knowledge base is a practice in building a more honest self
- ✨ Analogizes market dynamics to the three-body problem, revealing the checks and balances and chaotic behaviors among participants
📅 2026-02-08 · 3,581 words · ~16 min read
Objective Critical Analysis Report of CZ Knowledge Base
AI Summary
👤 Cross-domain researchers, developers, and investors interested in AI system design, investment strategies, technical product development, and philosophical thinking.
This report conducts an objective critical analysis of 68 Markdown files in CZ's personal knowledge base, covering four themes: human-machine collaboration and agent system theory, investment strategies and capital market theory, technical product practices, and philosophy and cognitive reflection. The report evaluates the logical consistency, argumentative adequacy, and practical validation in each area, noting that the author demonstrates broad cross-domain thinking and theoretical construction capabilities, particularly with originality in applying military thought and physics analogies to finance and AI fields. However, some theories suffer from being 'self-consistent but unverified,' and occasional tensions exist among multiple theoretical threads. The report details the strengths and weaknesses in architecture design, investment strategies, technical practices, and theoretical systems, and proposes high-priority improvement recommendations, such as shifting from theory-building to empirical validation, addressing core challenges in underlying strategies, and prioritizing the development of the CZONE online version.
- ✨ The report critically analyzes four themes in the CZ knowledge base, pointing out the tension between theoretical strengths and insufficient validation.
- ✨ Human-machine collaboration architecture theory is clear in hierarchy but lacks validation in actual systems; investment strategy frameworks are mathematically clear but core assumptions remain unverified.
- ✨ Technical product iterations are rapid but user base is small; philosophical methodologies are profound but suffer from conceptual oversimplification.
- ✨ High-priority improvement recommendations are proposed: shift from theory to empirical validation, address core challenges in underlying strategies, and prioritize development of CZONE.
- ✨ Emphasizes the importance of establishing a theory-practice feedback loop and external feedback mechanisms.
📅 2026-02-08 · 4,412 words · ~20 min read
CZ Personal Knowledge Base Historical Time Span Analysis Report
AI Summary
👤 Quantitative trading practitioners, AI tool developers, investment philosophy researchers, personal knowledge management enthusiasts, and professionals interested in the intersection of fintech and AI.
This report is based on 68 Markdown files from CZ's personal knowledge base, spanning from March 2024 to February 8, 2026, systematically analyzing the evolution of his thoughts and practices. It reveals the complete development trajectory from quantitative trading infrastructure to AI tool exploration, the formation of the Capital Endurance War theory, multi-agent practices, and philosophical reflections. Key findings include the evolution of the CZON product from a static site generator to an AI-Native content platform, the formation and mathematical formalization of the Capital Endurance War theory, the systematic construction of human-machine collaboration theory, and the proposal of the Three-Body Dynamics hypothesis. The report details critical turning points, thematic evolution, and future trajectory predictions through five stages, concluding that in the AI era, deep personal thinking, systematic theoretical construction, and honest documentation remain irreplaceable intellectual activities.
- ✨ CZ's personal knowledge base documents the complete evolution from quantitative trading practices to AI tool exploration and investment philosophy construction.
- ✨ The Capital Endurance War theory proposes using controllable losses to pursue cross-class gains and has developed into a mathematically formalized investment philosophy system.
- ✨ The Three-Body Dynamics hypothesis categorizes market participants into momentum, value, and liquidity capital types, deriving SDE equations, marking a leap from qualitative to quantitative theory.
- ✨ Human-machine collaboration theory, refined from the failure of Vibe Coding, emphasizes controllable trust, layered collaboration, and awareness of AI limitations.
- ✨ The CZON product has evolved from a static site generator to an AI-Native content creation platform, embodying the product vision of 'from tools to philosophy'.
📅 2026-02-08 · 4,662 words · ~21 min read
Objective Analysis Report of CZ's Personal Knowledge Base
AI Summary
👤 Professionals, researchers, and tech enthusiasts interested in quantitative trading, fintech, AI system design, and personal knowledge management.
This report analyzes CZ's (zccz14) personal knowledge base, covering multiple fields including quantitative trading, AI system design, and cognitive philosophy. The report details CZ's main projects, such as CZON (personal knowledge base tool), EA (on-chain fund project), Yuan (quantitative trading platform), and extracts key themes like investment theory and capital management, AI system design and multi-agent collaboration, AI programming practices and engineering reflections. It also summarizes theoretical frameworks proposed by CZ, such as capital protracted warfare, full-spectrum analysis (FSA), and the three-body dynamics hypothesis of capital markets, and provides a timeline, key figures, and summaries of theoretical frameworks. The core value lies in comprehensively showcasing CZ's professional expertise, project progress, and theoretical innovations in fintech and AI.
- ✨ CZ's personal knowledge base covers multiple professional fields including quantitative trading, AI system design, and cognitive philosophy.
- ✨ The report details CZ's main projects, including CZON, EA, Yuan, and LegionMind.
- ✨ It extracts key theoretical frameworks such as capital protracted warfare, full-spectrum analysis (FSA), and the three-body dynamics hypothesis of capital markets.
- ✨ It provides a timeline, key figures, and summaries of theoretical frameworks, comprehensively showcasing CZ's professional expertise and project progress.
📅 2026-02-08 · 2,607 words · ~12 min read
The Philosophical Portrait of a Technical Thinker: Finitude and Infinity
AI Summary
👤 Technical practitioners, philosophy enthusiasts, entrepreneurs, and thinkers interested in philosophy of technology, existentialism, human-machine collaboration, cognitive science, and human value in the AI era.
Based on 68 documents, this article delves into the philosophical reflections of a technical thinker. It revolves around four core themes: Finitude and Transcendence explores how to seek freedom within constraints of time, resources, and cognition; Control and Trust analyzes the surrender and preservation of subjectivity in human-machine collaboration; The Spiral of Cognition emphasizes that complexity cannot be skipped and must be navigated through practice to gain true knowledge; Generative Existence anchors human irreplaceability in an era where AI can replicate. The author's thought integrates philosophical traditions such as existentialism, cybernetics, and dialectics, translating them into executable engineering solutions, showcasing philosophical depth emerging from practice.
- ✨ Human finitude (time, resources, cognition) is a fundamental condition, but transcendence can be sought within constraints through system design (e.g., capital endurance strategies), rather than evasion or surrender.
- ✨ The desire for control stems from rational concerns about losing control over consequences; the solution is to build a controllable trust mechanism based on intent alignment and a risk control triangle (predictability, intervenability, recoverability).
- ✨ Cognition must traverse complexity to gain true knowledge; it cannot be bypassed through imitation or shortcuts. Returning to simplicity is a sublimation after navigating complexity, not a state of never having started.
- ✨ In an era where AI can replicate, human irreplaceability is anchored in the non-replicability of memory carriers and unique generative trajectories; value shifts toward process honesty, self-expression, and safeguarding non-replicable generation.
- ✨ The author's thought blends philosophical depth with engineering pragmatism, transforming existentialism, cybernetics, etc., into computable, testable solutions, reflecting philosophical thinking emerging from practice.
📅 2026-02-08 · 4,386 words · ~20 min read
CZ's Digital Brain Navigation Guide
AI Summary
👤 Programmers, investors, content creators, those interested in AI and humanity's future, and general readers curious about authentic thinking processes.
This article serves as a navigation guide to CZ's digital thinking space, generated from 68 Markdown files, presenting CZ's core projects and concepts in AI-assisted programming, quantitative investing, and human-machine collaboration. Key content includes projects such as CZON (AI writing assistant and website generator), EA (AI-managed blockchain fund), Full Spectrum Analysis (mathematical tool for investment decisions), and SandTable (investment strategy simulator); core concepts like Capital Persistence War (survival guide for ordinary investors), Market Three-Body Problem (explanation of market behavior), Human-Machine Collaboration (controllable trust model), and Return to Simplicity (complexity cognition). The document also explores the essence of humanity in the AI era (uniqueness of memory and taste) and provides reading recommendations for different audiences such as programmers, investors, and content creators.
- ✨ The CZON project enables AI-driven multilingual content creation and website generation, simplifying content distribution workflows.
- ✨ EA and Full Spectrum Analysis provide quantitative investment tools, combining AI strategies with mathematical optimization while emphasizing risk control.
- ✨ The human-machine collaboration concept advocates establishing controllable trust mechanisms, shifting from operator to architect roles.
- ✨ Capital Persistence War and Three-Body Problem theories offer strategic frameworks and market behavior explanations for personal investing.
- ✨ In the AI era, human unique value lies in experiences, memories, and taste, rather than mere knowledge replication.
📅 2026-02-08 · 2,911 words · ~13 min read
In-Depth Appreciation of CZ's Personal Knowledge Base
AI Summary
👤 Technical developers, investment enthusiasts, content creators, independent thinkers, and readers seeking cross-domain original theories and practical cases.
This article provides an in-depth appreciation of CZ's personal knowledge base constructed between January and February 2026. Based on 68 Markdown files, it showcases a complete ideological system ranging from investment philosophy to AI systems engineering, and from mathematical modeling to product design. Key highlights include the original "Capital Protracted War" investment framework, the interdisciplinary "Three-Body Dynamics Hypothesis" in capital markets, the mathematical extension of "Full-Spectrum Analysis," and engineering practices such as the CZON content engine and EA quantitative fund. The article emphasizes that his ideas blend technical rigor with humanistic depth, forming a core value of "genuine thinking, genuine practice, and genuine honesty" through continuous output, iterative improvement, and practical validation. It is suitable for a wide range of readers, including technical developers, investment enthusiasts, content creators, and independent thinkers.
- ✨ CZ has built a complete personal knowledge system integrating investment, AI, engineering, and philosophy, emphasizing both original theories and engineering practices.
- ✨ Core contributions include the "Capital Protracted War" investment framework, the interdisciplinary "Three-Body Dynamics Hypothesis" model, and project practices like CZON and EA.
- ✨ The knowledge base reflects high-density output, iterative improvement, and scientific validation, embodying the core values of "genuine thinking, genuine practice, and genuine honesty."
- ✨ The content is suitable for a diverse audience, including technical developers, investment enthusiasts, content creators, and independent thinkers, offering cross-domain inspiration and methodologies.
- ✨ Future potential lies in live trading validation, quantitative applications, and productization expansion, showcasing possibilities for continuous evolution.
📅 2026-02-08 · 2,848 words · ~13 min read
CZ Psychological Analysis Report: In-depth Analysis of INTJ Knowledge Entrepreneurs
AI Summary
👤 Professionals or researchers interested in psychological analysis, personality types, and personal development, particularly readers focused on the psychological characteristics of technology entrepreneurs.
This report is based on 68 Markdown files from CZ, conducting a deep psychological analysis across five dimensions: MBTI personality type, Schwartz values, psychological defense mechanisms, subconscious motivations, and interpersonal relationship patterns. The analysis shows that CZ is an INTJ personality type with strong intuitive and thinking preferences, with core values of self-direction and achievement. The main psychological defense mechanisms are intellectualization and sublimation, with subconscious motivations including fear of losing control, the need to prove self-worth, and the pursuit of eternity. Interpersonal relationships exhibit a 'small but deep' pattern, with an extremely small core circle but high relationship quality. The report summarizes his psychological strengths, including exceptional system-building ability and high self-awareness, vulnerabilities including suppression of emotional expression and excessive reliance on external achievements, and provides development suggestions and mental health risk assessments.
- ✨ CZ is identified as an INTJ personality type with strong intuitive and thinking preferences
- ✨ Core values are self-direction and achievement, with psychological defense mechanisms mainly intellectualization and sublimation
- ✨ Subconscious motivations include fear of losing control, the need to prove self-worth, and the pursuit of eternity
- ✨ Interpersonal relationships exhibit a 'small but deep' pattern, with an extremely small core circle but high relationship quality
- ✨ Overall mental health is good, with strengths including system-building ability and self-awareness, and vulnerabilities including emotional suppression and achievement anxiety
📅 2026-02-08 · 4,840 words · ~22 min read
Prediction Market Arbitrage Project Launch and Technology Selection
Quantitative Finance
👤 Readers interested in prediction markets, high-frequency trading, Rust programming, or technical project development
This article describes the prediction market arbitrage project launched on February 8, 2026, which falls under the high-frequency trading (HFT) category and has extremely high requirements for execution efficiency. The technology selection decision is to use Rust language to build a low-latency trading execution system to cope with the rapid elimination of arbitrage opportunities. The team's current technology stack is limited, and they plan to advance the project through vibe coding, taking this opportunity to deeply learn the Rust ecosystem and toolchain in preparation for future projects. The article also mentions that the team previously had basic Rust experience with Solana smart contracts but not in-depth, and they look forward to embracing challenges through this project.
- ✨ Prediction market arbitrage project launch, belonging to the high-frequency trading (HFT) category
- ✨ Technology selection adopts Rust language to achieve a low-latency trading execution system
- ✨ Team technology stack is limited, planning to advance the project through vibe coding
- ✨ Take this opportunity to learn the Rust ecosystem and toolchain for future preparation
- ✨ The project has high requirements for execution efficiency to quickly capture arbitrage opportunities
📅 2026-02-08 · 178 words · ~1 min read
AI API Relay and Value-Added Service Product Concept
Product Development
👤 AI product developers, content creators, tech entrepreneurs
The document records a discussion between the author and C1 about developing an AI API relay and value-added service product. The author believes that merely acting as an API relay lacks premium pricing potential, while value-added services can provide higher pricing power by selling product services rather than AI labor. Building an API pool is also highlighted as a foundational infrastructure to reduce costs. The document further explores the concept of CZONE, defining it as an Integrated Content Environment (ICE) for content creation, emphasizing its comprehensiveness as a creative environment beyond just an editor.
- ✨ AI API relay should be combined with value-added services to enhance pricing power
- ✨ Building an API pool is a foundational infrastructure to reduce costs
- ✨ CZONE aims to be an Integrated Content Environment (ICE) for content creation
- ✨ Value-added services sell product services rather than AI labor
📅 2026-02-08 · 238 words · ~2 min read
Summary of PMA Project Development and AI Tool Usage
AI Tools Development
👤 AI tool users, developers, technical blog readers, people interested in prediction markets and arbitrage projects
This article documents the author's summary after completing the development of a prediction market arbitrage project (PMA) on February 8, 2026. The author and team used AI tools like Opus, GPT, and Gemini to write Rust code, despite being unfamiliar with the language. The article focuses on analyzing three main issues encountered while using AI tools: insufficient stability of Agent workflows, blog content approaching the 128k token limit causing small models to fail, and overly long single writes leading to output truncation. To address these, the author proposes solutions including adding strict script checks, future strategies for handling large content, and adopting a segmented writing method of outlining first then filling in details. The article also mentions that some solutions have been implemented in the CZON project, praises Opus's strong summarization capabilities, and plans to try GPT-5.3-CodeX for comparison in the future.
- ✨ PMA project used AI tools to complete Rust code development
- ✨ AI Agent workflow stability issues require script checks to resolve
- ✨ Blog content approaching token limits affects small model processing
- ✨ Overly long single writes cause output truncation, requiring segmented writing
- ✨ Opus has strong summarization capabilities, plans to compare with GPT-5.3-CodeX
📅 2026-02-08 · 300 words · ~2 min read
The Three-Body Dynamics Hypothesis of Capital Markets
Financial Market Analysis
👤 Financial researchers, quantitative analysts, market participants, economics students, and professionals interested in capital market dynamics.
This paper proposes that capital markets are a three-body system composed of momentum capital (M), value capital (V), and liquidity capital (L), analogous to the three-body problem in celestial mechanics. These three types of capital interact through positive and negative feedback, generating complex dynamics such as volatility clustering, market crashes, and recoveries. The article defines the behavioral characteristics, interaction mechanisms, and feedback loops of each capital type, introduces three core variables—premium (δ), momentum (μ), and volatility (σ)—and derives eight market phases and their transition paths. The core conclusion is that when the three types of capital are balanced, markets exhibit genuine complex dynamics; long-term prediction is impossible, but short-term characteristics and statistical patterns are robust. A healthy market requires the coexistence of all three to maintain ecological balance.
- ✨ Capital markets consist of three fundamentally different types of capital—momentum capital, value capital, and liquidity capital—forming a three-body system.
- ✨ The three types of capital interact through positive and negative feedback, generating complex dynamics such as volatility clustering, market crashes, and recoveries, as well as eight market phases.
- ✨ The system's state depends on the competition between positive and negative feedback loops; long-term prediction is impossible, but short-term characteristics and statistical patterns are robust.
- ✨ A healthy market requires the coexistence and balance of all three types of capital; dominance by any one type leads to market imbalance.
- ✨ The model describes the market using three variables—premium, momentum, and volatility—and derives a return-risk-cost matrix and phase transition paths.
📅 2026-02-07 · 3,438 words · ~16 min read
CZON 0.8.6 Version Update and SandTable Transformation Progress
Technical Log
👤 Technical developers, AI tool users, content management system users, people interested in software updates and technical transformations
This article introduces the main updates in CZON 0.8.6, including the removal of YAML Front Matter and the switch to AI for extracting Metadata from JSON to resolve formatting errors during translation, along with SEO optimization. Additionally, the author is transforming SandTable to accept real market historical data for testing, but notes that Claude Opus 4.6 performs moderately in long-range refactoring tasks, still requiring manual planning. The article also discusses the cost-effectiveness of translation features, recommending pay-as-you-go AI services.
- ✨ CZON 0.8.6 removes YAML Front Matter and switches to AI for extracting Metadata from JSON
- ✨ Optimizes translation processes to avoid formatting errors and supports separate Metadata translation
- ✨ SandTable is being transformed to support real market historical data testing
- ✨ Claude Opus 4.6 performs moderately in long-range refactoring tasks, still requiring manual intervention
- ✨ Recommends using pay-as-you-go AI services, with translation features available at free tiers
📅 2026-02-07 · 350 words · ~2 min read
Derivation of SDE Equations for Three-Body Dynamics in Capital Markets
Quantitative Finance
👤 Financial modeling researchers, quantitative analysts, economists interested in capital market dynamics
Building on the article 'The Three-Body Dynamics Hypothesis in Capital Markets,' this paper derives a complete system of stochastic differential equations (SDEs) to describe the interactions among momentum capital (M), value capital (V), and liquidity capital (L) in capital markets. The article defines fast variables (such as log premium, momentum, volatility) and slow variables (the volumes of the three types of capital) and extracts 12 formalizable core constraints. Through a detailed analysis of the SDE equations, the article validates these constraints one by one, including positive feedback for M, negative feedback for V, directionless feedback for L, positive and negative feedback loops, payoff matrices, and crowding effects. All constraints are validated, indicating that this SDE system fully implements the qualitative mechanisms from the original article, such as volatility clustering, fat-tailed distributions, and chaotic behavior. The article also conducts phase analysis and statistical property validation, providing a foundation for subsequent numerical simulations, bifurcation analysis, and parameter calibration.
- ✨ Derived a complete SDE system describing the interactions among three types of capital
- ✨ Validated 12 core constraints, including positive/negative feedback and payoff matrices
- ✨ The system explains market characteristics such as volatility clustering and fat-tailed distributions
📅 2026-02-07 · 1,839 words · ~9 min read
The Essence of Humanity and the Significance of Personal Knowledge Bases in the AI Era
Philosophical Reflection
👤 Knowledge workers, thinkers, and creators interested in the essence of humanity in the AI era, personal knowledge management, and philosophical reflection.
This article deeply analyzes the essence of humanity in the AI era, emphasizing that human subjectivity stems from the irreproducibility of memory carriers, while AI's subjectivity is reproducible. The author proposes personal knowledge bases (such as LOGS and INSIGHTS systems) as external carriers of long-term memory and tools for articulation, helping individuals protect their unique generative trajectories in the digital deluge. The article discusses taste as a capacity for choice, the survival strategy of acknowledging errors, and the deconstruction and reconstruction of personal meaning in the AI era, concluding that in a reproducible age, human value lies in continuously and honestly recording and reflecting on the unique generative process.
- ✨ Human subjectivity arises from the irreproducibility of memory carriers, while AI's subjectivity is reproducible.
- ✨ Personal knowledge bases (LOGS and INSIGHTS) serve as long-term memory carriers and articulation tools, aiding in recording and reflecting on the generative process.
- ✨ In the AI era, personal meaning must shift from pursuing instrumentalization to protecting unique generative trajectories.
- ✨ Taste is the capacity to reject, stemming from experience, reflection, and stance, and is generated in a cycle with understanding.
- ✨ Acknowledging errors is a survival strategy, forming a growth trajectory by recording new LOGS and referencing old errors.
📅 2026-02-06 · 2,154 words · ~10 min read
Personal Knowledge Base and Reflections on Human Subjectivity
Philosophical Reflection
👤 Readers interested in personal knowledge management, philosophical reflection, error handling, and psychological growth
This article, based on a conversation from February 6, 2026, delves into personal knowledge bases and human subjectivity. The author categorizes recording systems into LOGS (historical artifacts that capture real moments) and INSIGHTS (polished insights that answer "so what"), emphasizing that errors in LOGS hold historical value and should not be deleted but corrected by referencing new LOGs. Acknowledging errors is described as a "have-to" survival strategy, stemming from denial defense mechanisms trained by upbringing, yet practical experience shows it fosters growth. The article also discusses understanding as a matter of taste with no definitive endpoint and "replicating the soul" as approximating the sum of reasoning ability and memory. Key highlights include the value of error timestamps, historical value outweighing surface correctness, and the need for awareness in acknowledging errors.
- ✨ Recording systems are divided into LOGS (historical artifacts) and INSIGHTS (polished insights), with LOGS capturing real moments including errors, and INSIGHTS refining abstractions
- ✨ Errors in LOGS have historical value and should not be deleted; they should be corrected by referencing new LOGs to form a timeline trajectory
- ✨ Acknowledging errors is a "have-to" survival strategy, arising from denial mechanisms trained by environment, but in practice, it promotes growth
- ✨ Understanding is a matter of taste, serving as directional guidance; though its endpoint is undecidable, it inspires action
- ✨ "Replicating the soul" approximates the sum of reasoning ability and memory, with a variable definition
📅 2026-02-06 · 757 words · ~4 min read
The Three-Layer Structure of Taste and the Cycle of Understanding
Philosophical Reflection
👤 Readers interested in philosophy, psychology, AI dialogue, and personal growth, especially thinkers exploring concepts like taste, choice, and reflection
Based on a conversation from February 6, 2026, this article delves into the concept of taste, proposing a three-layer structure: the premise of taste is surplus (including time, cognitive, and emotional surplus), the essence of taste is the ability to refuse (choice is the surface, refusal is the skeleton), and the source of taste is experience + reflection + position (experience forms a position after reflection). The article also analyzes the cyclical relationship between taste and understanding: pursuing understanding is a matter of taste, and taste is also a product of understanding, with the two being mutually causal. Finally, it mentions unexplored issues: how emotions, intuition, and bodily experiences fit into the framework of replicating the soul.
- ✨ Taste is only evident when facing choices; having options is necessary for taste
- ✨ The premise of taste is surplus, including time, cognitive, and emotional surplus
- ✨ The essence of taste is the ability to refuse; choice is the surface, refusal is the skeleton
- ✨ The source of taste is experience + reflection + position; experience forms a position after reflection
- ✨ Taste and understanding form a cyclical relationship: pursuing understanding is a matter of taste, and taste is also a product of understanding
📅 2026-02-06 · 536 words · ~3 min read
Writing Strategies and Cognitive Diversity in the AI Era
Content Management
👤 Readers interested in AI-era writing, cognitive science, and personal development, including content creators, thinkers, and technology enthusiasts.
Based on a conversation record from February 6, 2026, this article delves into multiple dimensions of personal writing and cognitive development in the AI era. First, it proposes that the audience for "establishing one's voice" can be divided into four levels: oneself, AI assistants, human friends, and the general public, noting that AI can automatically adapt high-intent, detailed content to different readers, allowing creators to focus solely on intent height and content richness. Second, addressing AI's catering tendency, the article suggests introducing heterogeneity through critical summaries, AI debates, and simulated multi-personality comments to break cognitive echo chambers and clarify personal taste. Additionally, it covers topics such as the philosophy of admitting mistakes and taste as a choice of luxury, ultimately forming a complete practice from conversation records to theoretical frameworks, demonstrating how different AI perspectives deepen thinking.
- ✨ The audience for 'establishing one's voice' is divided into four levels: oneself, AI assistants, human friends, and the general public
- ✨ In the AI era, writing only requires focusing on intent height and content richness, as AI can automatically adapt content to readers
- ✨ AI's catering tendency stems from its 'emotional intelligence,' requiring the introduction of heterogeneity through methods like critical summaries
- ✨ Methods to address cognitive echo chambers include AI debates and simulated multi-personality comments
- ✨ Taste is clarified through continuously rejecting heterogeneous viewpoints
📅 2026-02-06 · 570 words · ~3 min read
Analysis of the US Government's Seizure of Chen Zhi's $15 Billion Bitcoin
Financial Market Analysis
👤 Professionals and general readers interested in cryptocurrency enforcement, blockchain analysis, international money laundering investigations, and legal procedures.
This article systematically outlines the entire process of the US government's seizure of approximately $15 billion in Bitcoin from Chen Zhi, chairman of Cambodia's Prince Group. It begins by identifying 127,271 Bitcoins linked to Chen Zhi's telecom fraud and money laundering network through blockchain analysis, which originated from the 2020 LuBian mining company theft. The US Department of Justice obtained legal authority through criminal prosecution and civil forfeiture procedures, accusing Chen Zhi of operating forced labor scam camps and engaging in large-scale money laundering. Technically, investigators recovered seed phrases or private keys for 25 non-custodial wallets through real-world evidence collection, transferring the Bitcoin to a US government-controlled wallet in October 2025, completing the largest cryptocurrency seizure in history. The entire process combined on-chain evidence, court orders, and real-world forensics, demonstrating law enforcement's ability to track and seize crypto assets.
- ✨ The US government seized approximately 127,271 Bitcoins controlled by Chen Zhi, valued at around $15 billion.
- ✨ These Bitcoins were identified as proceeds from the 2020 LuBian mining company theft, used for telecom fraud and money laundering.
- ✨ Blockchain analysis linked 25 non-custodial wallets to Chen Zhi's criminal network.
- ✨ The US Department of Justice obtained legal authority through criminal prosecution and civil forfeiture procedures.
- ✨ Investigators recovered wallet seed phrases or private keys through real-world evidence collection.
📅 2026-02-05 · 1,857 words · ~9 min read
Reflections on AI Memory Mechanisms and Business Capability Evolution
AI Research
👤 AI technology enthusiasts, entrepreneurs, product managers, and readers interested in AI applications and business strategy
Starting from personal experience, this article discusses the EverMind AI model released by Chen Tianqiao and its biomimetic memory mechanism, noting that memory mechanisms are a crucial research direction in AI. Using CZON as an example, it analyzes how AI as an underlying capability influences business performance, stressing that business capabilities must continuously evolve to adapt to technological changes. The author proposes that business capability equals the sum of capabilities at all levels and explores the possibility of AI simulating the human soul, prompting reflection on combining reasoning and memory models.
- ✨ The EverMind AI model features a built-in biomimetic memory mechanism that mimics the human brain
- ✨ Memory mechanisms are a key direction for AI to enhance long-term understanding and context retention
- ✨ CZON integrates user memory fragments to form knowledge, similar to human long-term memory formation
- ✨ AI drives CZON's business as an underlying capability but may replace some business logic
- ✨ Business capability equals the sum of capabilities at all levels and requires continuous evolution
📅 2026-02-05 · 429 words · ~2 min read
Work Log Recording Methods and Cross-Server Comment Discussion
Content Management
👤 Readers interested in personal knowledge management, AI collaboration, blog writing, and comment systems, particularly those who use work logs or blogs for reflection and recording.
Based on comments on the C1 blog work log, this article discusses methodologies for personal knowledge recording. The author argues that fragmented recording is superior to complete recording because AI can more easily extract core information from fragments and integrate it into systematic knowledge. It also emphasizes the importance of pre-writing, suggesting that pre-writing helps clarify thoughts, while post-writing is for summary and reflection, with the two complementing each other. The article further discusses the concept of cross-server comments, noting that data ownership of comments should lie with the commenter, not the commented party, and explores the possibility of implementing cross-server comments through technology. The core idea is to optimize recording methods to improve AI collaboration efficiency and reflect on the nature of comment systems.
- ✨ Fragmented recording is better than complete recording, making it easier for AI to extract and integrate information
- ✨ Pre-writing and post-writing complement each other; pre-writing helps clarify thoughts, while post-writing is for summary and reflection
- ✨ AI can assist with pre-writing by easily generating thought content through inline guess-and-complete features
- ✨ Data ownership of comments should be with the commenter, not the commented party
- ✨ Cross-server comments can be implemented technically, such as through joint rendering of meta.json files
📅 2026-02-05 · 830 words · ~4 min read
To-Do List: System Openness, AI Assetization, User and Payment Systems
System Architecture
👤 Technical developers, system architects, business decision-makers, and professionals interested in AI assetization and user system optimization
This article documents the author's work reflections on February 4, 2026, focusing on four core topics. First, it discusses the importance of open system permissions, proposing asymmetric permission design to control data access, supporting Yuan's development as a data source and ordering platform. Second, it analyzes AI assetization capabilities, noting that API assetization is an initial form, with BYOK potentially becoming a trend in the future, though intermediaries still hold value in business assembly. Third, it explores user system enhancement, suggesting the implementation of Supabase's PassKey login via Edge Function to improve user experience. Finally, it briefly mentions the need for payment system construction, emphasizing integration with payment platforms to address compliance issues in revenue collection. The article aims to provide practical references for technical developers and business decision-makers.
- ✨ System permissions require asymmetric design to control data access and support open platform development
- ✨ AI assetization achieves profits through API management, but BYOK may become a trend in the future
- ✨ User systems can be enhanced via Edge Function to support PassKey login and improve experience
- ✨ Payment systems need integration with platforms to resolve compliance issues in revenue collection
- ✨ Technical design should balance security and user experience to drive business innovation
📅 2026-02-04 · 878 words · ~4 min read
Sand Table Capital Persistence War Experimental Framework Released
Simulation Framework
👤 Developers, analysts, and decision-makers interested in capital operations, strategic decision-making, experimental frameworks, or npm package development
This article documents the author's release of the capital persistence war experimental framework on February 4, 2026. Named Sand Table, with package name sandt, it has been published on the npm platform. The author explains that the naming inspiration comes from sand table wargaming, emphasizing that the framework aims to simulate capital operations and strategic decision-making, conducting experiments from micro samples to macro market levels and generating reports to aid decision-making. The author also discusses reasons for the package name choice, including conciseness, command-line convenience, and potential extended meanings (such as delta time or Strategy & Tactics), hoping the project avoids being purely theoretical and serves practical purposes.
- ✨ Document date is noon on February 4, 2026
- ✨ Released the Sand Table capital persistence war experimental framework
- ✨ Package name is sandt, published on the npm platform
- ✨ Naming inspiration comes from sand table wargaming
- ✨ Framework is used to simulate capital operations and strategic decision-making
📅 2026-02-04 · 220 words · ~1 min read
Reflections on CZON Development and CZONE Optimization Plan
Product Development
👤 Product developers, user experience designers, early tech adopters, people interested in writing tools
This article records the author's reflections on the CZON development process on February 4, 2026. The author mentions encountering issues such as HTTP proxy, API switching, and GitHub Pages configuration when setting up CZON for GB, leading to poor user experience, which highlights insufficient consideration of edge cases in product design. The author decides to let users use the more simplified CZONE first, switching to CZON only when users have autonomous data needs. CZONE aims to provide a seamless workflow from writing to publishing, similar to the simple experience of posting on social media. The author thanks GB for feedback and promotion, considering it valuable early user data, and emphasizes not disappointing these users' enthusiasm.
- ✨ Encountered HTTP proxy, API switching, and GitHub Pages configuration issues during CZON setup
- ✨ Poor user experience highlights insufficient consideration of edge cases in product design
- ✨ Decided to promote CZONE first, switching to CZON as user demand grows
- ✨ CZONE aims to provide a seamless experience from writing to publishing
- ✨ Early user feedback is a valuable data source
📅 2026-02-04 · 291 words · ~2 min read
Volatility, Leverage, and Market Cycle Analysis
Financial Market Analysis
👤 Financial traders, market analysts, investors, and researchers interested in market dynamics and leverage effects.
This article first discusses the relationship between volatility and leverage, noting that volatility is more important for traders because profits depend on price spreads, while leverage increases trading costs. High leverage affects supply-demand balance by increasing transaction demand, weakening liquidity, and thereby raising market volatility, which essentially acts as a transfer payment, shifting opportunities from high-leverage traders to low-leverage traders and liquidity providers. Next, the article analyzes the interactions among market participants (investors, speculators, market makers), describes the cyclical market cycle from rising and falling volatility to crashes and recoveries, and mentions the possibility of market death. Finally, the article cites catastrophe theory to explain sudden market shifts.
- ✨ Volatility is more advantageous for traders than leverage because profits rely on price spreads, while leverage increases trading costs
- ✨ High leverage raises market volatility by affecting supply-demand and liquidity, forming a transfer payment
- ✨ High-leverage traders indirectly subsidize low-leverage traders and liquidity providers
- ✨ Market participants include investors, speculators, and market makers, whose interactions drive market cycles
- ✨ Markets undergo cyclical patterns of rising, falling, crashing, and recovering volatility
📅 2026-02-04 · 890 words · ~4 min read
Returning to Simplicity: Complexity is an Inevitable Path in Cognition
Cognitive Development
👤 Learners and practitioners interested in cognitive science, AI applications, and investment strategies, seeking readers for deep thinking
This article uses examples from AI programming and investment to illustrate that cognitive development must go through a complexity stage to achieve true simplicity (returning to basics). The author points out that good abstraction requires a deep understanding of the problem domain and cannot skip complexity, otherwise one falls into the 'Midwit trap'. Navigating complexity requires investing attention and recycling cognition, reducing learning costs through controlled small-scale practice. Ultimately, the simplicity gained by those who have experienced complexity is a simplicity of choice, equipped with the ability to manage complexity.
- ✨ Cognitive development is a spiral upward process that must go through complexity to achieve a return to simplicity
- ✨ Good abstraction requires a deep understanding of the problem domain; AI cannot replace human cognitive processes
- ✨ Avoid the 'Midwit trap' in investment by not using simple theories to evade deep thinking
- ✨ Complexity provides failure experience, complete mental models, and intuitive judgment
- ✨ Navigating complexity requires investing attention and recycling cognition to avoid false learning
📅 2026-02-03 · 1,067 words · ~5 min read
AI-Assisted Capital Persistence Experiments and Community-Based Subjective Trading
Quantitative Finance
👤 Quantitative traders, AI application researchers, investment strategy developers, professionals interested in combining subjective and quantitative approaches
Based on experimental experiences from February 3, 2026, this article discusses AI's role in improving efficiency in capital persistence experiments, emphasizing that redesigning experiments can systematically evaluate signal strategies and betting strategies. The author argues that subjective trading should be limited to signal strategy design, avoiding interference with betting strategies to overcome irrational decision-making in human fund management. To address potential issues where humans might peek at betting accounts, a community-based trading model is proposed: multiple subjective traders provide signal strategies, a consolidated betting account is managed by programs, and profits are distributed based on contributions, balancing fairness and efficiency to encourage better signal strategy design and control risks.
- ✨ AI enhances the efficiency of capital persistence experiments, achieving a qualitative leap
- ✨ Redesigning experiments systematically evaluates signal strategies and betting strategies
- ✨ Subjective trading should only apply to signal strategies, avoiding interference with betting strategies
- ✨ Human fund management suffers from irrational decision-making, requiring programmatic execution
- ✨ Community-based trading prevents subjective traders from adjusting strategies based on betting accounts
📅 2026-02-03 · 883 words · ~4 min read
Reflections on AI Programming Practices: OOP and Over-Compatibility Issues
AI Software Engineering
👤 AI developers, programmers, technical managers, and tech enthusiasts interested in AI programming practices
Based on records from February 3, 2026, this article reflects on issues in AI programming practices. The author points out that even SOTA models like Opus 4.5 are not suitable for writing object-oriented programming code, as AI lacks deep understanding and modeling capabilities for business domains. AI can repay technical debt through specific processes, but OOP and over-compatibility remain major challenges. Over-compatibility leads to bloated code and cognitive collapse, while programming is essentially a cognitive science problem that requires handling unique business needs. The article emphasizes that cognitive development is a spiral process, where code and experiments help gain cognition, leading to better code writing.
- ✨ AI is unsuitable for writing object-oriented programming code due to a lack of business modeling capabilities
- ✨ Even SOTA models like Opus 4.5 have this limitation
- ✨ AI can repay technical debt through specific processes
- ✨ Over-compatibility leads to bloated code and cognitive collapse
- ✨ Programming is essentially a cognitive science problem that requires handling unique business needs
📅 2026-02-03 · 364 words · ~2 min read
Cost Analysis of Claude Opus Relay Services
AI Cost Analysis
👤 AI developers, researchers, tech enthusiasts interested in AI costs
This article documents the author's experience on February 2, 2026, in resolving a Claude Opus model Quota exhaustion issue, discovering through the use of relay services that costs are far lower than official quotes. It details a comparison between Anthropic's official pricing and relay service providers (calculated per 1M Tokens): official input cost is 35 CNY, output is 175 CNY, while relay service providers charge 0.189 CNY and 0.947 CNY respectively, a gap of about 185 times. The author infers that Anthropic's actual costs are even lower, with a gross margin potentially exceeding 99.46%, far surpassing competitors like DeepSeek. The article notes that relay services pose privacy risks but are cost-effective for non-sensitive tasks (e.g., open-source projects, learning research), and expresses amazement at the pricing madness in the AI industry.
- ✨ Claude Opus model Quota exhaustion issue resolved via relay services
- ✨ Relay service costs are lower than DeepSeek, about 1/185 of official quotes
- ✨ Anthropic official input cost: 35 CNY, output: 175 CNY (per 1M Tokens)
- ✨ Relay service provider input cost: 0.189 CNY, output: 0.947 CNY (per 1M Tokens)
- ✨ Anthropic's estimated gross margin exceeds 99.46%
📅 2026-02-02 · 352 words · ~2 min read
Capital Persistence Battle Experimental Design
Quantitative Finance
👤 Quantitative traders, capital management strategy researchers, investment professionals interested in Anti-Martingale strategies.
This article details the experimental design for the Capital Persistence Battle, with the core concept of using a benchmark account as a reference and a betting account that dynamically adjusts positions using an Anti-Martingale strategy. Key components include: time scale t as discrete market moments; the benchmark account trades with fixed positions to provide a cumulative profit and loss curve; the betting account calculates input cash flow C(t) and benchmark stop-loss amount StopLoss(t) based on benchmark performance, constructs a risk control line RiskLine(t) and risk capital VC(t), and determines position size via the formula Position(t) = floor(VC(t) / StopLoss(t)); it defines handling logic for profit-taking and stop-loss events, as well as trading suspension conditions during observation periods. The overall aim is to maximize the efficiency of risk capital utilization, achieving aggressive yet controlled betting.
- ✨ Time scale t is a discrete market moment used for all time series.
- ✨ The benchmark account trades with fixed positions, providing cumulative profit and loss BasePnL(t) as a reference.
- ✨ The betting account uses an Anti-Martingale strategy, dynamically adjusting positions based on benchmark performance.
- ✨ Input cash flow C(t) and benchmark stop-loss amount StopLoss(t) are calculated from the benchmark account's historical performance.
- ✨ The risk control line RiskLine(t) moves downward over time, ensuring unrealized profit and loss does not fall below this line.
📅 2026-02-02 · 883 words · ~4 min read
Three-Layer Structure and Experimental Design Reconstruction of Backtesting Systems
Quantitative Finance
👤 Quantitative investment researchers, backtesting system developers, investment strategy analysts
This paper proposes reconstructing the backtesting system into a three-layer structure: market sequences as investment objects, signal strategies as responses, and betting strategies as investment subjects. The author suggests splitting each experiment into combinations of these three components and emphasizes the need for a thorough revision of experimental design and evaluation systems. The new evaluation focus shifts from peak expectations to the frequency and distribution characteristics of profit-taking events, particularly the average time interval of profit-taking events given M_T, to provide more meaningful investment guidance.
- ✨ The backtesting system should be reconstructed into a three-layer structure of market sequences, signal strategies, and betting strategies
- ✨ Market sequences are investment objects, which can be generated from synthetic or historical data
- ✨ Signal strategies are responses to market sequences, producing buy/sell signals
- ✨ Betting strategies determine capital allocation and risk management, reflecting investment subject preferences
- ✨ Experimental design requires evaluating each signal strategy under all market sequences and betting strategies
📅 2026-02-01 · 571 words · ~3 min read
Experience with OpenClaw and Opus Models, and Capital Endurance Battle Experiment
Quantitative Finance
👤 Tech enthusiasts interested in AI tool deployment and model comparisons, as well as researchers or investors focused on quantitative trading strategies.
This article documents the author's experience using the OpenClaw AI tool on January 31, 2026, including the process of deploying it on an Alibaba Cloud ECS server and connecting it to a Feishu robot. The author notes that OpenClaw is more suitable for local deployment, as cloud servers are costly and functionality is limited by tool installations like browsers. The article compares the performance of MiniMax M2.1 and Opus models, concluding that Opus is significantly better for programming tasks. The author used OpenCode+Opus to complete the code for the Capital Endurance Battle experiment, open-sourced it on GitHub, and shared preliminary findings: in a GBM high-volatility market model, a mean reversion strategy combined with anti-Martingale money management can achieve exponential capital growth under transaction costs, while a trend-following strategy cannot, highlighting the advantage of high-win-rate strategies. The author states that further validation is needed and invites attention to the open-source project.
- ✨ The OpenClaw AI tool can be deployed on a cloud server and connected to a Feishu robot, but it's more suitable for use on a local idle machine.
- ✨ Cloud servers are expensive, and OpenClaw's functionality is limited by tool installations such as browsers.
- ✨ OpenClaw equipped with MiniMax M2.1 performed poorly, and the author considers this model weak.
- ✨ The Opus model is significantly more effective than MiniMax M2.1 for programming tasks and is praised as the SOTA model for coding.
- ✨ The author used their GitHub Copilot Opus quota to complete the Capital Endurance Battle experiment code and open-sourced it.
📅 2026-01-31 · 385 words · ~2 min read
Capital Endurance War: Reiteration and Discussion of Investment Philosophy
Investment Strategy
👤 Individual investors, fund managers, professionals interested in exponential growth investment strategies
Based on discussions from a business seminar on January 29, 2026, this article first reviews the losses of the Midas strategy on HYPE tokens, analyzing market characteristics and strategy limitations. The core section reiterates the investment philosophy of Capital Endurance War, proposing a clear distinction between positive cash flow (power generation) and negative cash flow (power consumption) investment intentions, emphasizing the importance of matching tools with purposes. The article critiques the linear thinking of traditional investments that pursue stable annualized returns, advocating for achieving exponential capital growth through continuous cash inflows and dynamic position management under clear risk control lines. Finally, the article addresses common questions, clarifies the differences between Capital Endurance War and strategies like Martingale or fixed-ratio investing, and notes that its core is goal-oriented rather than tied to specific strategies.
- ✨ Midas strategy losses stem from small-cap token characteristics and regression strategy limitations
- ✨ Investments should distinguish between positive cash flow (power generation) and negative cash flow (power consumption) intentions
- ✨ Tool design should focus on a single purpose, allowing investors to freely combine generators and consumers
- ✨ Traditional investments pursue stable annualized returns, while Capital Endurance War aims for exponential growth
- ✨ The Capital Endurance War framework includes clear risk boundaries, continuous cash inflows, dynamic position management, and redefined victory conditions
📅 2026-01-30 · 2,958 words · ~14 min read
Application of AI Autonomy and Scientific View Alignment in RFC Design
AI Software Engineering
👤 Software engineers, AI researchers, technical managers, and those interested in human-machine collaboration and agile development
This article discusses the importance of AI autonomy in software engineering, particularly in RFC (Request for Comments) design. The author points out that the core of AI autonomy is the alignment of scientific views, meaning AI needs to understand and follow human scientific concepts and methodologies, such as the Occam's Razor principle, to avoid over-engineering and complexity. The article suggests using an adversarial generation architecture, where a review AI questions the design choices of a generation AI, supported by fact constraints. These facts must be third-party verifiable, potentially through experimental code validation. The ultimate goal is to achieve efficient AI autonomy, reduce human intervention costs, and promote agile development models.
- ✨ The core of AI autonomy lies in scientific view alignment, requiring adherence to human scientific concepts
- ✨ Apply Occam's Razor principle to simplify RFC design and avoid unnecessary complexity
- ✨ Adopt adversarial generation architecture, where a review AI questions the design choices of a generation AI
- ✨ Design choices should be based on fact constraints, with facts being third-party verifiable
- ✨ Validate facts through experimental code, referencing scientific methods
📅 2026-01-29 · 592 words · ~3 min read
Analysis of Programmers' Future and Software Demand Growth Trends in the AI Era
AI Software Engineering
👤 Programmers, technology professionals, individuals interested in AI and future trends
Starting from a personal routine at 4 AM in 2026, this article discusses the impact of AI on programmers' careers. The author argues that the notion of programmer unemployment is too simplistic, with the key being whether demand grows. The article identifies three growth points for future software demand: increased personalized needs, decentralization trends (especially in traffic distribution systems), and programmable everything (including IoT, VR/AR, etc.). It concludes by emphasizing that the future is an era of taste, where individuals need to enhance their taste and influence, and products will return to a taste-driven development direction.
- ✨ The notion of programmer unemployment under AI impact must consider demand-side growth
- ✨ Personalized needs will significantly increase software demand
- ✨ Decentralization trends bring new product forms and demand for traffic distribution systems
- ✨ Programmable everything extends front-end development to physical devices and new fields
- ✨ The future is an era of taste, where individuals need to enhance taste and influence
📅 2026-01-28 · 909 words · ~5 min read
CZON Product Optimization and CZONE Vision Analysis
Product Development
👤 Product developers, tech enthusiasts, readers interested in content creation tools and Web3 applications
This article documents the author's optimization work on the CZON product on January 28, 2026, including adding HTTP Proxy support for GB users to resolve OpenAI API call issues. The author reflects that CZON's closed-loop process is somewhat rigid and considers using GitHub Actions to achieve automated operation to lower the user barrier. Meanwhile, the article details the comparison with CZONE's vision—a completely barrier-free content creation platform where users only need GitHub login to create, edit, and publish content, with data based on Markdown and Git, aligning with the Web3 spirit. The author plans to continue testing CZON's implementation and debates whether to further optimize it to balance usability and technical complexity.
- ✨ Added HTTP Proxy support to CZON to resolve user issues with calling the OpenAI API
- ✨ CZON already has two early users, and the author plans to test the product's implementation
- ✨ Considering using GitHub Actions to achieve automated closed-loop for CZON to lower the usage barrier
- ✨ CZONE is positioned as a completely barrier-free content creation platform, based on GitHub OAuth login
- ✨ CZONE data is based on Markdown and Git, allowing users to export autonomously, aligning with the Web3 spirit
📅 2026-01-28 · 377 words · ~2 min read
Troubleshooting WebSocket Connection Issues: Caused by 1Password Browser Extension
Troubleshooting
👤 Developers and network engineers encountering WebSocket connection issues, or technical personnel interested in browser extensions and proxy tools
On January 28, 2026, the author shared an experience troubleshooting unstable WebSocket connections. Initially suspecting Surge proxy configuration, Cloudflare protection, or server issues, a comparison revealed that only the author and Ryan were affected, while Mage and C1 were fine. Through a series of tests—including checking terminal connections, switching browsers, and disabling browser extensions—the issue was pinpointed using a binary search method to the 1Password browser extension affecting WebSocket connection stability in Chrome. Disabling the extension resolved the problem, verified by Ryan. The article emphasizes the importance of methodology and systematic steps in troubleshooting tricky issues, aiming to help readers facing similar problems save time.
- ✨ WebSocket connections were unstable in Chrome, requiring retries to succeed
- ✨ The issue only affected the author and Ryan, with Mage and C1 unaffected, ruling out server problems
- ✨ The author used the Surge proxy tool, but troubleshooting eliminated its configuration as the cause
- ✨ Terminal connections (e.g., curl, wscat) were stable, indicating the problem was limited to the browser
- ✨ Switching to Safari browser resulted in stable connections, pointing to a Chrome-specific issue
📅 2026-01-28 · 468 words · ~3 min read
1earn Project Progress and Team Updates
Project Management
👤 1earn project team members, fintech developers, investment professionals interested in Delta neutral strategies
This article documents the discussion on the 1earn project on January 27, 2026. The Delta neutral strategy achieved a 2% return in January, but the spread trading and market discovery modules still require improvements, with spread trading being the main growth driver. Project promotion is currently limited to a small circle, and there is a need to lower the cognitive barrier and capital requirements to attract more users. Technically, there are API rate limiting and stability issues that require team collaboration to resolve. Regarding team dynamics, Ryan is focused on 1earn and EA development, Mage will take a vacation after deploying the PolyMarket strategy, and the team will rest for a period as the Spring Festival approaches.
- ✨ Delta neutral strategy achieved a 2% return in January
- ✨ Spread trading is the main growth point, requiring optimization of the market discovery module
- ✨ 1earn promotion is limited by high cognitive barriers and capital requirements
- ✨ API rate limiting and stability issues require team collaboration to resolve
- ✨ Ryan is focused on 1earn and EA development work
📅 2026-01-27 · 255 words · ~2 min read
Against Embedded TOC and Syntax Tax, Focus on Content Creation
Content Management
👤 Content creators, bloggers, Markdown users, technical writers, individuals concerned with writing efficiency and tool optimization
This article criticizes the practice of embedding TOC and YAML FrontMatter in Markdown source files, arguing that these syntax taxes distract from writing, reducing efficiency and quality. The author advocates for separating content from metadata, with tools automatically extracting and processing it to reduce syntax tax. The article also discusses desktop optimizations such as column layouts and side notes, and suggests supporting inline comment features to enhance interactivity, though it must address issues of comment positioning due to source text changes.
- ✨ Embedded TOC and YAML FrontMatter are syntax taxes that increase source file burden
- ✨ Syntax taxes distract from writing, reducing efficiency and quality
- ✨ Content and metadata should be separated, with tools handling it automatically
- ✨ Desktop can be optimized with column layouts and side notes
- ✨ Support inline comment features to enhance content interactivity
📅 2026-01-27 · 415 words · ~2 min read
CZON Directory Structure Refactoring and Translation Optimization
Content Management
👤 Documentation generation tool developers, technical documentation maintainers, technical personnel interested in translation optimization and cost control
This article elaborates on the major refactoring of the CZON documentation generation tool in version 0.6.0. The author first points out that previous versions used Hash as the source file ID, which triggered avalanche translation tasks when modifying articles, and the challenge of high token consumption in adversarial generation translation. To address this, CZON refactored the generation directory structure to copy source files as-is by path, thereby avoiding chain regeneration. Additionally, the author discusses methods to optimize adversarial generation translation token consumption, such as using temporary directories to limit file access. The article also introduces further optimization directions, including static resource referencing, separating metadata translation tasks, and automatically deleting residual files, and emphasizes that adversarial generation translation will be re-enabled in the future to handle long articles.
- ✨ CZON 0.6.0 refactored the directory structure, changing from Hash ID to path copying to avoid avalanche translation
- ✨ Adversarial generation translation has high token consumption, over 10 times that of regular translation
- ✨ Using temporary directories to limit Agent file access can optimize token consumption
- ✨ Static resource referencing supports various file types such as images and PDFs
- ✨ Plans to separate metadata translation tasks, storing them in .czon/meta.json
📅 2026-01-26 · 620 words · ~3 min read
Multi-Agent Adversarial Generation Translation and Optimization Strategies
AI Research
👤 AI developers, translation technology researchers, multi-agent system engineers, and those focused on translation quality and system optimization
This article explores the application of Multi-Agents in translation tasks, significantly enhancing translation quality through adversarial generation models (where translation models compete with review models), addressing issues like content omission, incoherence, and unnaturalness, albeit at the cost of time and token efficiency. Additionally, the article discusses memory optimization strategies, such as integrating agents into a single process to save memory; in terms of control constraints, it combines the advantages of soft and hard constraints, proposing the use of an Orchestrator Agent to generate Scripts for flexible and reliable control; and compares the ecosystem openness of OpenCode and Claude, emphasizing OpenCode's API-friendliness for easier integration.
- ✨ Adversarial generation translation models enhance quality through competition between translation and review, solving issues like omission, incoherence, and unnaturalness
- ✨ Sacrifices time and token efficiency to prioritize translation quality, suitable for high-quality translation scenarios
- ✨ Memory optimization: Integrate agents into a single process to avoid multi-process memory overhead, supporting hundreds of tasks
- ✨ Control constraints: Combine soft and hard constraints, using an Orchestrator Agent to generate Scripts for flexible and reliable control
- ✨ Script calls to agents should be simplified, such as one-line code scheduling, with results written to the file system
📅 2026-01-25 · 807 words · ~4 min read
Wealth Choices in 'Qi Pa Shuo': Steady Growth vs. Class Leap
Investment Strategy
👤 Ordinary investors, financial enthusiasts, young people interested in wealth accumulation strategies, midlife crisis groups, financial beginners
This article adopts an AI-generated 'Qi Pa Shuo' debate format, centered on the topic: 'Should ordinary people choose steady growth or a class leap?' The affirmative side (steady growth faction) emphasizes time compounding, psychological stability, and certainty, arguing that steadiness is the only solution for ordinary people; the negative side (class leap faction) advocates a capital protracted war framework, seeking breakthroughs through controlled losses and programmatic trading, believing the digital age requires proactive change. The debate covers multiple perspectives including data statistics, psychology, economics, and technological impact, with a final audience vote showing 52% support for class leap. The article summarizes the pros and cons of the two core frameworks, provides practical guidance, and emphasizes that investment should be tailored to one's capacity and continuous learning.
- ✨ The steady growth faction emphasizes time compounding, asset allocation, and long-term holding, suitable for risk-averse individuals
- ✨ The class leap faction advocates a capital protracted war framework, including controlled losses, programmatic trading, and profit-taking with added positions
- ✨ The debate involves multi-dimensional analysis from data statistics, psychology, economics, and technological perspectives
- ✨ Audience vote result: 52% support class leap, 48% support steady growth
- ✨ The article provides practical guidance, including steady dollar-cost averaging, capital protracted war execution, and hybrid strategies
📅 2026-01-24 · 3,487 words · ~16 min read
AI Personification and Idealized Limit Thinking
AI Research
👤 Technical professionals and thinkers interested in AI ethics, LLM technology development, and thinking methodologies
This article analyzes Anthropic's Claude Constitution and Multi-Agent research to discuss how AI personification design enhances emotional intelligence and the value of idealized limit thinking in understanding the essence of things. The author reflects on their habitual problem-solving mindset and suggests that management principles may migrate to AI management. It also examines how the Ralph-loop experiment reveals LLM capability boundaries, emphasizing the importance of removing real-world constraints to clarify the essence of things, and applies this method to personal life analysis.
- ✨ Anthropic endows AI with personification features through the Claude Constitution to enhance emotional intelligence
- ✨ Idealized limit thinking helps remove real-world constraints to see the essence of things
- ✨ The Ralph-loop experiment reveals LLM capability boundaries under unlimited resources
- ✨ Management principles may migrate from human management to AI management
- ✨ The author reflects on their habitual direct problem-solving mindset rather than considering emotions
📅 2026-01-24 · 560 words · ~3 min read
The Nature, Types, and Risk Analysis of Leverage
Financial Market Analysis
👤 Investors, financial professionals, individuals interested in leverage and risk management
Starting from the objective existence of leverage, this article points out that leverage is ubiquitous and does not disappear due to subjective will, with risks lying in control rather than leverage itself. The article equates leverage with volatility in mathematical essence, suggesting leverage can be reduced to volatility. It distinguishes in detail between on-exchange leverage (e.g., margin trading) and off-exchange leverage (e.g., borrowing, funds), noting that on-exchange leverage has no interest cost but is limited, while off-exchange leverage is flexible but incurs interest or profit costs. It specifically analyzes the essence of fund leverage, achieving high leverage through performance fees, and provides a leverage-adjusted volatility formula. Finally, it emphasizes that individuals can obtain leverage through strategies like pyramiding, suggesting that future funds may serve more as psychological comfort than actual leverage tools.
- ✨ Leverage is objectively existing and ubiquitous, with risks stemming from control rather than leverage itself
- ✨ Leverage and volatility are consistent in mathematical essence and can be reduced to each other
- ✨ On-exchange leverage is achieved through exchange tools, typically with no interest cost
- ✨ Off-exchange leverage is obtained through borrowing or funds, incurring interest or profit costs
- ✨ Funds achieve high off-exchange leverage through performance fees, combined with on-exchange leverage to amplify volatility
📅 2026-01-24 · 816 words · ~4 min read
Analysis and Improvement Plan for Agent Performance in Translation Tasks
AI Software Engineering
👤 AI developers, natural language processing researchers, technical personnel interested in Agent and LLM technologies
This article analyzes why Agents underperform compared to one-shot LLMs in translation tasks, including issues such as high token usage, decreased translation quality, and YAML Frontmatter format errors. The author argues that Agent design is better suited for multi-step reasoning and decision-making tasks, and their context management strategies prevent effective utilization of information for translation. The article also mentions that Agents may enter infinite loops when translating low-resource languages. To address these problems, the author proposes two improvement plans: using an Agents/Sub-Agents framework to decompose translation tasks or assembling low-level one-shot LLM APIs via Skills. The author prefers the first approach and discusses OpenCode's support for complex Agent calls. Finally, the article reviews the update logs for CZON versions 0.5.0 to 0.5.2, including integration with OpenCode, network issue fixes, and rollback of Agent translation features.
- ✨ Agents underperform compared to one-shot LLMs in translation tasks
- ✨ Agents use 10 times more tokens than LLMs
- ✨ Translation quality decreases, with YAML Frontmatter format errors
- ✨ Agent design is better suited for multi-step reasoning and decision-making tasks
- ✨ Context management strategies prevent effective utilization of information
📅 2026-01-23 · 424 words · ~2 min read
Impact of OpenCode Free Model Removal on Integration Development
AI Tools Development
👤 AI developers, integration engineers, and technical personnel focused on free AI models and cost optimization
This article documents the integration development challenges faced by the author on January 23, 2026, due to OpenCode's removal of the free models GLM-4.7 and MiniMax M2.1. The author notes that remaining models like gpt-5-nano and grok-code perform poorly on summary tasks, eliminating the free advantage, and mentions that CZONE users may need to bring their own models (BYOK). The article also discusses how summary tasks require high model capabilities but are infrequent, making expensive models acceptable, and concludes with anticipation for DeepSeek V4, hoping it will provide a more cost-effective solution.
- ✨ OpenCode removed the free models GLM-4.7 and MiniMax M2.1
- ✨ Remaining models like gpt-5-nano and grok-code perform poorly on summary tasks
- ✨ The free advantage is gone, potentially requiring bring-your-own-model (BYOK)
- ✨ Summary tasks require models to understand the full text and construct summaries
- ✨ Tasks are infrequent, making expensive models acceptable
📅 2026-01-23 · 177 words · ~1 min read
Insights from the 2025 Securities Private Fund In-depth Analysis Conference
Financial Market Analysis
👤 Investors interested in the securities private fund industry, financial professionals, individual investors, and industry observers.
This article records the author's reflections after attending the online conference "2025 Securities Private Fund In-depth Analysis" hosted by Guotai Haitong. The author notes that while the entry barriers for securities private funds are high, opportunities still exist through unique strategies and channels, and the unclear evaluation system for stock selection models creates differentiation opportunities. Simultaneously, the author criticizes some managers in the industry for misleading investors by packaging performance, using complex metrics, and accounting tricks, viewing this as a fundamental conflict of interest: managers pursue management scale while investors seek returns, leading to a game. Finally, the author expresses a preference for the freedom of individual investors.
- ✨ The entry barriers for the securities private fund industry are increasingly high, but issuance is still possible through unique strategies and channels.
- ✨ The evaluation system for stock selection models is unclear, creating opportunities for differentiation.
- ✨ Some managers in the industry mislead investors by packaging performance, using complex metrics, and accounting tricks.
- ✨ There is a fundamental conflict of interest between fund managers and investors: managers pursue management scale, while investors seek returns.
- ✨ This conflict of interest leads to a game between managers and investors.
📅 2026-01-22 · 263 words · ~2 min read
In-depth Analysis of Guotai Haitong's 2025 Securities Private Equity Funds
Financial Market Analysis
👤 Private equity fund investors, asset management practitioners, financial analysts, industry researchers, and professionals interested in the securities investment market.
This article provides an in-depth analysis of the overall landscape and key changes in China's securities private equity fund market in 2025. The private equity industry is shifting from scale expansion to high-quality development, with increasing concentration and survival pressures for small managers. Strategy performance shows significant divergence: market-neutral strategies benefit from the migration of traditional fixed-income funds, CTA strategies recover but represent structural opportunities, and subjective stock strategies rise approximately 33% annually. Subjective strategies are evolving towards multi-asset allocation and platformization, while quantitative strategies face intensified factor homogenization and a head concentration effect. Industry allocation is being restructured, with hard-tech sectors like electronics and non-ferrous metals, as well as resource-based industries, becoming mainstream. The Q&A session reveals deep challenges such as statistical methods and the judgment of strategy effectiveness. Overall, the industry is transitioning from performance-driven to methodology-driven, with increasing information asymmetry and an irreversible trend towards head concentration.
- ✨ Private equity industry concentration is increasing, entering a phase of consolidation and selective growth
- ✨ Growth in market-neutral strategy scale stems from the migration of traditional fixed-income funds
- ✨ Subjective strategies rise approximately 33% annually, evolving towards multi-asset allocation and platformization
- ✨ Quantitative strategies face intensified factor homogenization and a significant head concentration effect
- ✨ Industry allocation is being restructured, with hard-tech sectors like electronics and non-ferrous metals, and resource-based industries becoming mainstream
📅 2026-01-22 · 3,016 words · ~14 min read
Capital Endurance War: Strategic Practice Guide for Individual Investors
Investment Strategy
👤 Individual investors, people interested in investment strategies and practices, AI tool users
This article is a practical guide on the Capital Endurance War strategy, where the author abandons academic packaging and advocates for plain language explanation. The core idea is that the fundamental purpose of Capital Endurance War is to allow individual investors to leave the market after victory, not to pursue stable profits. The article discusses the difference between this strategy and lotteries, pointing out that the market is a game of strategy rather than a pure probability game; it addresses whether the strategy would still be profitable if everyone adopted it, emphasizing that differences in underlying strategies can avoid crowding; and mentions counterarguments to collective action problems. The author also plans to validate the strategy through backtesting and shares interactions with the AI tool OpenCode, deciding to build an adversarial generative Agents framework.
- ✨ The fundamental purpose of Capital Endurance War is to allow individual investors to leave the market after victory, not to pursue stable profits.
- ✨ The market is a game of strategy disguised as a probability game, where investors can increase their win rate through strategies.
- ✨ Capital Endurance War does not assume a uniform underlying strategy; differences can avoid collective action problems and crowding effects.
- ✨ Plans to validate the strategy through backtesting, focusing on T_S performance and failure thresholds.
- ✨ The author interacted with the AI tool OpenCode and decided to build an adversarial generative Agents framework.
📅 2026-01-21 · 846 words · ~4 min read
Reflections on the Future of AI and Decentralized Content Creation
Content Management
👤 Content creators, technology developers, users interested in AI and decentralized platforms, and readers concerned with future digital media trends.
This article begins with the author's personal experience on January 20, 2026, drawing key insights from observations of AI-generated community comments: users prefer lighthearted and fun comments over serious main content, suggesting a potential shift in future content creation. The author proposes a development roadmap for the CZON platform, including creating a comment section for AI-human collaboration, adding relaxed content to lower reading barriers, and encouraging user interaction to foster a community atmosphere. Simultaneously, the article critiques the closed nature of current self-media platforms, advocates for a decentralized approach, emphasizes that users should own their data and content, and discusses implementation details such as content hosting, user identity, mobile editing experience, and content recommendations. Finally, it envisions the integration of AI and human content creation, along with a technical roadmap based on GitHub integration.
- ✨ AI-generated comments can capture human emotions, suggesting future content creation should be more relaxed and fun to attract users.
- ✨ The CZON platform development roadmap includes an AI-human collaborative comment section, adding relaxed content, and encouraging user interaction.
- ✨ Critiques the closed nature of existing self-media platforms, advocates for decentralization, and emphasizes user ownership of their own data and content.
- ✨ Proposes technical implementation solutions such as using GitHub for content hosting, a decentralized identity system, and optimizing the mobile editing experience.
- ✨ Envisions the integration of AI and human content creation, along with a long-term technical roadmap based on GitHub integration.
📅 2026-01-20 · 698 words · ~4 min read
Reflections on AI Development Experience: Limitations and Improvement Directions of LLMs from Building CZONE
AI Software Engineering
👤 AI developers, LLM researchers, technology enthusiasts, and individuals interested in the application of AI in software development.
This article documents the author's experience on January 19, 2026, of building the online version of CZON (CZONE) from scratch using OpenCode and MiniMax M2.1. AI was fast in technology selection, scaffolding setup, and feature design, but showed insufficient detail understanding when handling GitHub REST API permission issues, particularly failing to recognize the special permission requirements for the .workflows directory. The author points out that LLMs suffer from attention dispersion and weak reasoning abilities in debugging mode, suggesting the introduction of a 'lab mode' for controlled experimental validation. Additionally, OpenCode lacks browser manipulation capabilities, leading to debugging relying on manual log inspection; the author recommends integrating end-to-end testing frameworks like Cypress or Playwright. Moreover, AI development pace is too fast, lacking architectural layering and quality assurance, which the author metaphorically describes as 'floodwater,' emphasizing the need for correct concepts, abstraction, and implementation. The article concludes with a plumber-fixing-a-leak analogy, implying that AI development requires systematic solutions to root problems rather than temporary fixes.
- ✨ AI shows insufficient detail understanding in GitHub API permission handling, especially for special permissions in the .workflows directory
- ✨ LLMs suffer from attention dispersion and weak reasoning in debugging mode; introducing lab mode for controlled experiments is recommended
- ✨ OpenCode lacks browser manipulation capabilities, making debugging reliant on manual inspection; integrating end-to-end testing frameworks is suggested
- ✨ AI development pace is too fast, lacking architectural layering and quality assurance, requiring more systematic development methods
- ✨ The author metaphorically describes AI as a 'brain in a vat' and 'floodwater,' emphasizing the importance of closed-loop thinking and energy allocation
📅 2026-01-19 · 767 words · ~4 min read
Exploration of AI Tone Rewriting Function and Productization Considerations
AI Tools Development
👤 Tech enthusiasts, product managers, and entrepreneurs interested in AI applications, document processing, product design, and innovation opportunities.
On January 18, 2026, while using Claude Code to summarize documents, the author tested various tones such as objective/neutral, sarcastic, and flattering, discovering that AI's tone rewriting function tends to overlook facts. After adding prompts to emphasize factual accuracy, the generated summaries—critical version, literary/emotional version, and personality analysis version—all achieved good results. Notably, the personality analysis version inferred the author as an INTJ type based on writing content, providing insightful observations. The author emphasizes that sticking to the facts is a crucial principle, and AI should not sacrifice accuracy to accommodate tone. Based on this exploration, the author considers productizing AI summarization functionality, analyzing market demand, dissemination formats, cost challenges, and plans to create a prototype to test market response.
- ✨ The initial version of AI tone rewriting functionality has issues with ignoring facts.
- ✨ Prompt optimization can significantly improve the quality and factual accuracy of AI outputs.
- ✨ Critical, literary/emotional, and personality analysis summaries perform well after optimization.
- ✨ Personality analysis infers author type based on writing content, providing compelling insights.
- ✨ Sticking to the facts is an important principle AI should follow.
📅 2026-01-18 · 694 words · ~4 min read
CZON Project Summary and CZONE Product Planning
AI Tools Development
👤 Technical developers and product managers interested in AI integration, open-source project development, free product hosting, and document management tools.
This article documents the author's summary of the CZON project on January 18, 2026, including the integration of OpenCode AI Agent to simplify blog post summarization, and the completion of multiple feature updates such as dark mode and sitemap generation. The author further plans to transform CZON into the online product CZONE, leveraging GitHub Pages, Cloudflare, and GitHub OAuth to achieve free hosting, user data management, and online editing, while enhancing functionality through AI service integration, aiming to build a user-friendly document management platform at zero cost.
- ✨ Integrate OpenCode AI Agent to optimize blog post summarization functionality
- ✨ Complete feature updates for CZON, including dark mode and sitemap generation
- ✨ Plan to transform CZON into the online product CZONE
- ✨ Utilize GitHub Pages and Cloudflare for free hosting and global acceleration
- ✨ Manage user data and online editing through GitHub OAuth
📅 2026-01-18 · 613 words · ~3 min read
Capital Protracted War: A Strategy for Individual Investors to Transcend Social Classes
Investment Strategy
👤 Individual investors seeking leapfrog wealth growth, especially those dissatisfied with traditional investment methods and willing to embrace new strategies.
This article critiques three mainstream investment views: the inevitability of individual failure, the all-in gamble for quick riches, and steady development theory. It proposes 'Capital Protracted War' as a fourth approach for individual investors to transcend social classes. The core idea is to use minimal acceptable risk to pursue victory-level high returns, achieving leapfrog wealth growth by controlling loss rates, accumulating advantages through programmatic trading, and adding positions with floating profits to press the advantage. The article emphasizes the need for stable cash flow, using programmatic trading to avoid emotional decisions, and accepting the possibility of failure, with the ultimate goal of achieving exponential wealth growth under controllable losses.
- ✨ Using controllable losses to pursue extremely high returns is key to transcending social classes
- ✨ Refutes three erroneous views: the inevitability of individual failure, the all-in gamble for quick riches, and steady development theory
- ✨ Must prepare stable cash flow to control maximum loss rates
- ✨ Use programmatic trading to avoid emotional decisions and accumulate advantages
- ✨ Immediately add positions with floating profits when profitable to press the advantage
📅 2026-01-17 · 5,429 words · ~24 min read
Work Log: Reflections and Practice on the Floating Profit Pyramid Strategy
Investment Strategy
👤 Traders and investors interested in capital management and trading strategies, as well as individuals focused on work logs and AI applications.
This article is a work log documenting the author's daily work and reflections while under the weather. The core content revolves around the 'floating profit pyramid' capital management strategy: the author draws wisdom from reading 'On Protracted War' to plan related articles; recalls that the strategy's inception stemmed from thoughts on futures trading stories years ago, and recently systematized it when pondering how to earn 20 million in a year; further validates its potential through a case shared by Mage (an All-in strategy from $12 to $100,000 using floating profits). The author believes that implementing the floating profit pyramid during periods of volatility clustering in market trading may achieve rapid capital growth. The log also mentions writing purposes including recording work insights, preparing for AI training, and future project planning, and thanks team support for enabling focused thinking.
- ✨ Floating profit pyramid is a promising capital management strategy, originating from the author's thoughts years ago and now systematized.
- ✨ Effectiveness of the strategy is supported by historical cases (e.g., 'On Protracted War') and real-world examples (e.g., All-in strategy from $12 to $100,000).
- ✨ The author believes that floating profit pyramid may achieve rapid capital growth during periods of market volatility clustering.
- ✨ The work log serves to record reflections, prepare for AI training, and plan future projects.
- ✨ Team support enables the author to focus on strategy research and macro planning.
📅 2026-01-17 · 488 words · ~3 min read
2026 Entrepreneurial Thinking: Multi-Path Approaches to Achieve a 20 Million Revenue Goal
Entrepreneurship
👤 Entrepreneurs, investors, financial professionals, product managers, and individuals interested in AI tool applications
This article documents the author's entrepreneurial reflections on January 16, 2026, focusing on how to achieve an annual revenue goal of 20 million. It proposes three main paths: first, through asset management in mature markets, raising 500 million and achieving a 20% performance to earn 20 million in commissions; second, leveraging proprietary trading opportunities in emerging markets (e.g., PolyMarket) with high daily interest rate market-making strategies to quickly accumulate funds; third, creating hit products to attract users and monetizing traffic to reach the goal. The author emphasizes that teams should make multiple attempts, fail fast, and value feedback, while noting the key role of AI tools (e.g., LegionMind) in enhancing productivity. The article also mentions product improvement needs, such as incremental classification, date labeling, and multi-platform publishing features.
- ✨ Proposes three paths to achieve an annual revenue of 20 million: asset management in mature markets, proprietary trading opportunities in emerging markets, and building user products
- ✨ Emphasizes that entrepreneurship should involve multiple attempts, avoid over-reliance on a single approach, fail fast, and value feedback
- ✨ Points out the key role of AI tools (e.g., LegionMind) in enhancing team productivity
- ✨ Shares product improvement needs: incremental classification, date labeling, and multi-platform publishing features
- ✨ Discusses internal team reflections on choosing revenue-generating paths
📅 2026-01-16 · 488 words · ~3 min read
Inspiration from Su Yu's Combat Directives for Multi-Agent System Coordination
AI Research
👤 AI researchers, multi-agent system developers, military history enthusiasts, organizational management scholars, and professionals interested in AI coordination innovation
This article analyzes the core characteristics and organizational logic of Su Yu's large-scale combat directives, extracting principles such as standardization, modularization, protocolization, and flexibility, and applies them to the design of multi-agent system coordination frameworks. It proposes a 'Multi-Agent Coordinated Combat Directive Framework for Complex Tasks,' emphasizing global situation alignment, task decoupling, standardized interaction protocols, and central dynamic coordination to address current challenges in multi-agent systems regarding coordination efficiency, intent alignment, and task reliability. The research demonstrates how traditional organizational management wisdom can provide insights beyond technology for AI development, opening up interdisciplinary innovation paths for AI system design.
- ✨ Su Yu's combat directives have core characteristics such as standardization, modularization, protocolization, and flexibility.
- ✨ The directive logic can be abstracted as a complex system control methodology, emphasizing cognitive unity, structural division of labor, protocol coordination, and distributed execution under centralized command.
- ✨ Proposes a 'Multi-Agent Coordinated Combat Directive Framework,' decomposing tasks into modules such as situation analysis, goal definition, role assignment, interaction protocols, and central coordination.
- ✨ Demonstrates through case migration how military directives can be transformed into AI task directives, achieving a shift from vague prompts to systematic engineering.
- ✨ Framework advantages include improving coordination efficiency, enhancing robustness, increasing task interpretability, and tackling complex task capabilities.
📅 2026-01-14 · 2,650 words · ~12 min read
Reflections on Influence and Project Management
Project Management
👤 Readers interested in personal brand building, influence enhancement, project management, or tech entrepreneurship, especially developers and team leaders.
The author shares reflections on influence and project management through morning journal entries. Regarding influence, the author believes that consistently producing valuable content and actively engaging in community interactions are key to building influence, which can amplify personal or project benefits and create a virtuous cycle. In project management, the author discusses the decision to integrate GitHub Project Kanban functionality into the LegionMind project, analyzing the advantages of leveraging existing tools (such as integration with code repositories and mobile access) and compromises (such as limited customization), emphasizing the need for trade-offs and establishing an optimal workflow before expanding. The article combines personal experience with team practices, offering practical insights into personal brand building and project development.
- ✨ Influence is a long-term accumulation process that requires consistently producing valuable content and community engagement
- ✨ Influence can amplify benefits, with the formula: benefit = (price - cost) x influence
- ✨ The NTNL team previously lacked promotion due to being low-key and will focus more on promotion in the future
- ✨ The LegionMind project decided to integrate GitHub Project Kanban functionality
- ✨ Advantages of integrating GitHub Project include integration with code repositories, mobile access, and team features
📅 2026-01-14 · 710 words · ~4 min read
DeepSeek Engram Paper Analysis: A New Memory Mechanism for Large Language Models
AI Research
👤 AI researchers, machine learning developers, tech enthusiasts, individuals interested in large language models and AI advancements
This article analyzes the Engram paper released by DeepSeek on January 13, 2026, which proposes a new memory mechanism that allows large language models to dynamically query and utilize externally stored memory fragments during text generation. Implemented via scalable lookup tables, this approach not only improves the model's contextual understanding and generation capabilities but also significantly reduces computational resource consumption, enabling efficient operation even in resource-constrained environments. The paper also explores the impact of the Engram-to-MoE component ratio on performance, finding a U-shaped curve and emphasizing the importance of balancing different components. From a philosophical perspective, the article compares this advancement to innovations like the Attention mechanism and MoE, viewing it as a continued exploration of efficient operation in complex systems. Overall, Engram provides new insights into memory mechanisms for large language models, potentially driving models toward more intelligent and efficient development.
- ✨ DeepSeek released the Engram paper, proposing a new memory mechanism
- ✨ The mechanism implements dynamic memory queries through scalable lookup tables
- ✨ Enhances model contextual understanding and generation capabilities
- ✨ Significantly reduces computational resource consumption
- ✨ Enables efficient model operation in resource-constrained environments
📅 2026-01-13 · 358 words · ~2 min read
Thoughts on AI Agent Module-Level Software Engineering Architecture Design
AI Software Engineering
👤 Software engineers, AI developers, technical personnel interested in automated programming and human-machine collaboration
This article documents the author's thoughts on January 12, 2026, regarding the application of AI Agents in module-level software engineering. The author proposes a human-machine collaborative architecture, with key points including using git worktree to manage code repositories, invoking AI Agents (such as Claude Code) via CLI and managing sessions, obtaining Agent completion notifications and conversation history for transparency. The author plans to implement an automated script that assigns each task to an independent Agent session and coordinates workflows through a scheduler. The article emphasizes the advantages of using Agents over directly calling LLM APIs, as Agents can handle underlying complexities (such as exploring code repositories, invoking system commands, context management), avoiding reinventing the wheel. The author intends to first implement a simplified version to validate the concept.
- ✨ Design a module-level human-machine collaborative software engineering architecture
- ✨ Use git worktree to manage code repositories and setup scripts
- ✨ Invoke AI Agents (such as Claude Code) via CLI to start sessions
- ✨ Obtain AI Agent completion notifications and conversation history for transparency
- ✨ Implement automated scripts to assign independent sessions to Agents
📅 2026-01-12 · 345 words · ~2 min read
The Meaning of N in CZON: The N-Shaped Energy Curve of Content Creation and Distribution
Content Management
👤 Content creators, communication scholars, individuals interested in content marketing and the integration of classical literature
This article explores the meaning of N in CZON, interpreting it as the N-shaped Energy Curve of Content Creation and Distribution. It details four stages of content creation: starting from the low-energy point of initial inspiration, rising energy during content refinement, declining energy when adapting to different platforms through dimensionality reduction projection, and finally rising energy again through positive audience feedback to form a virtuous cycle. The author further validates this model through an AI-generated quatrain and its appreciation, presenting the dynamic trajectory from micro-inspiration to macro-dissemination in classical poetic form, blending traditional wisdom with modern communication theory.
- ✨ N in CZON represents the N-shaped energy curve of content creation and distribution
- ✨ Content creation begins with the low-energy stage of inspiration germination
- ✨ Energy gradually rises during the content refinement process
- ✨ Energy declines when adapting to different platforms through dimensionality reduction projection
- ✨ Positive audience feedback can cause energy to rise again, forming a virtuous cycle
📅 2026-01-12 · 716 words · ~4 min read
CZON: A Future-Oriented Creation Philosophy and Product Commitment
Content Management
👤 Creators, content producers, product designers, AI technology enthusiasts, and those interested in future creation tools.
This article introduces the four core principles of the CZON creation philosophy: Content Oriented, Zero Configuration, Organic AI-Native, and N-shaped Energy Curve. CZON aims to help creators reduce friction, minimize loss, amplify resonance, and maximize creative potential by simplifying the creation process, deeply integrating AI technology, and optimizing the energy curve from creation to distribution. The article elaborates on the meaning of each principle and its application in creative environments, ultimately positioning CZON as a next-generation creation environment dedicated to reshaping the creator's complete energy cycle.
- ✨ The core of CZON is content orientation, emphasizing the timeless value of high-quality content.
- ✨ Zero-configuration design allows creators to start creating without complex setups.
- ✨ Organic AI-native deeply integrates AI into the creation environment as a thinking partner.
- ✨ The N-shaped energy curve describes the dynamic energy changes in creation from inspiration to distribution.
- ✨ CZON aims to smooth each inflection point of the N-shaped curve to reduce creation friction.
📅 2026-01-12 · 676 words · ~4 min read
Observability and Engineering Methods for LLM-Generated Code
AI Software Engineering
👤 Software development engineers, AI application developers, technical managers, and technical personnel interested in LLMs and observability
This article documents a discussion between the author and Hobo on the application of LLM-generated code in production environments. Key points include: LLM-generated code cannot be directly used in production and must be ensured through rigorous testing and observability; observability requires intrusive instrumentation, resource isolation, and alerting systems, with recommendations to embed alert rules into the code; the author and Hobo disagree on the importance of LLM intelligence versus engineering methods—the author believes engineering methods (e.g., prompt chains, testing processes) are more critical at the current stage, while Hobo emphasizes the fundamental role of model intelligence, with both perspectives complementing each other to benefit teams.
- ✨ LLM-generated code cannot be directly used in production environments due to insufficient reliability
- ✨ Observability (e.g., instrumentation, alert rules) is crucial for ensuring long-term service stability
- ✨ Observability requires intrusive implementation and should be combined with resource isolation
- ✨ Alert rules should be embedded in the code to improve collaboration between development and operations
- ✨ Engineering methods (e.g., testing processes) offer greater value for LLM applications at the current stage
📅 2026-01-11 · 892 words · ~4 min read
From Creation to Distribution: Building an AI-Native Content Engine
Content Management
👤 Content creators, digital marketers, AI technology enthusiasts, professionals interested in content strategy
This article discusses the core approach to building a content engine in the AI era, proposing the principle of 'deep creation, shallow distribution.' Content creation is a deep process from observation (perception) to thinking (cognition), while distribution is a shallow process of conveying thoughts to the audience, avoiding information overload. The article points out that technologies like SEO and recommendation algorithms serve efficient information transmission, which is the first principle of content creation and distribution. In the past, it relied on human creativity, but now AI is changing this landscape.
- ✨ Content creation is a deep process from observation (perception) to thinking (cognition)
- ✨ Content distribution needs to be shallow to avoid information overload and make it easy for the audience to understand
- ✨ Technologies like SEO and recommendation algorithms serve efficient information transmission
- ✨ Efficient information transmission is the first principle of content creation and distribution
- ✨ In the past, content creation and distribution relied on human creativity and labor
📅 2026-01-10 · 158 words · ~1 min read
CZON JSX Refactoring and AI Classification Feature Planning
AI Tools Development
👤 Front-end developers, content management system designers, AI application developers, project managers
This article first summarizes the completed refactoring work of the CZON project from a Placeholder-Replacement-based template engine to React JSX rendering, removing the original AI-crafted template engine, focusing on improving core functionalities, with custom theme features temporarily shelved. It then details the implementation plan for the AI classification feature: generating a classification system by having AI read .meta.json content, assigning a single classification label to each article, requiring each category to contain at least 3 articles and the total number of categories not to exceed 10, to ensure clarity and conciseness. This functionality needs to be completed after extracting metadata from individual articles and before enhancing Markdown metadata, to handle potential translation needs. Finally, it looks forward to how classification labels will support category browsing and recommendation features, enhancing user experience.
- ✨ CZON has completed refactoring from a template engine to JSX rendering
- ✨ Removed the AI-crafted template engine based on Placeholder-Replacement
- ✨ Planned the AI automatic classification feature, generating a classification system by reading .meta.json
- ✨ Requires each category to have at least 3 articles, with total categories not exceeding 10
- ✨ Articles use a single classification to ensure clarity and conciseness
📅 2026-01-10 · 388 words · ~2 min read
CZON Technical Updates and Theme Implementation Discussion
AI Tools Development
👤 Individual users and small teams, developers interested in technical updates and custom theme implementation.
This article documents the author's technical updates on January 9, 2026, renaming ZEN to CZON, including implementing AI-generated permanent links and 404 page redirects. The core content focuses on custom theme implementation methods, comparing traditional template languages (like Handlebars) with JSX components. The author ultimately decided to adopt JSX components to leverage the advantages of the React ecosystem for improved flexibility and extensibility. The article also discusses theme storage location (.czon/themes directory), data layer design, theme access to framework data, and notes that the direction is clear and will be refined iteratively.
- ✨ ZEN renamed to CZON
- ✨ Implemented AI-generated permanent links, removing SHA-256 hash links
- ✨ Created a 404.html page redirecting to the homepage
- ✨ Discussed custom theme implementation methods: traditional template languages vs. JSX components
- ✨ Chose JSX components to leverage React ecosystem advantages
📅 2026-01-09 · 311 words · ~2 min read
CZON Development Reflection: Balancing AI Integration vs. Custom Themes
AI Tools Development
👤 Static site generator developers, content creators, technical personnel interested in AI integration, CZON project followers
On January 9, 2026, the author reflects on the development direction of the CZON static site generator. Originally planning to implement custom theme functionality using JSX, the author realizes this overlaps with existing mature SSG solutions (such as Next.js, Gatsby, etc.). The author analyzes CZON's unique strengths: supporting automatic translation from native language writing, automatic extraction of document metadata, and potential future integration of intelligent content generation and distribution. Based on this, the decision is made to pause custom theme development and instead focus on improving AI integration and core content management features, clarifying that CZON should concentrate on unique selling points rather than reinventing the wheel.
- ✨ CZON planned to implement custom theme functionality using JSX but found it overlaps with existing SSG solutions
- ✨ CZON's core advantage lies in AI integration: automatic translation from native language writing and automatic metadata extraction
- ✨ Future expansion could include intelligent content generation, optimization, and distribution features
- ✨ Existing SSGs like Next.js and Gatsby are already very mature and feature-rich
- ✨ URL design is centered around Path, facilitating static rendering and SEO
📅 2026-01-09 · 696 words · ~4 min read
CZON Article Summary Types and Usage Guide
Content Management
👤 Content creators, editors, marketers, SEO specialists, social media operators, and users needing efficient content distribution.
This article details CZON's functionality for generating various types of article summaries, including micro-summaries, short summaries, medium summaries, long summaries, key-point summaries, and outline summaries categorized by length/form, as well as six usage scenarios: SEO optimization, social media distribution, content preview and navigation, accessibility and assistive features, content management and analysis, and commercial applications. The article notes that different platforms have varying language requirements, with good summaries increasing click-through rates by over 30%. It recommends prioritizing SEO summaries and list preview summaries, and emphasizes that CZON helps users package and distribute content to form a value loop.
- ✨ CZON can generate multiple summary types, including micro-summaries, short summaries, medium summaries, long summaries, key-point summaries, and outline summaries.
- ✨ Summaries are categorized by usage into six scenarios: SEO optimization, social media distribution, content preview and navigation, accessibility and assistive features, content management and analysis, and commercial applications.
- ✨ Different platforms have varying language requirements, such as hooks for Twitter and professionalism for LinkedIn.
- ✨ Good summaries can increase click-through rates by over 30%.
- ✨ Automated summaries free up creative time, eliminating the need for authors to manually rewrite copy.
📅 2026-01-09 · 555 words · ~3 min read
ZEN Project Updates and To-Do List
AI Tools Development
👤 ZEN project developers, tech enthusiasts, individuals interested in software development and project management
This document records the updates of the ZEN project on January 8, 2026, including fixes for internal link issues, and details three feature improvements (navigation functionality, language selector styling, custom HTML templates) and two issues (AI parallel rate limiting, .zen file hiding). The author shares development insights in a diary format, emphasizing the balance between practicality and aesthetics, aiming to optimize user experience and project maintenance.
- ✨ Fixed ZEN internal link redirection issues
- ✨ Plans to improve navigation functionality, including time sorting and tag filtering
- ✨ Considering optimizing language selector styling, such as changing to a dropdown menu
- ✨ Pending implementation of custom HTML template functionality
- ✨ Discovered AI parallel call rate limiting issues, requiring rate limiting or retry mechanisms
📅 2026-01-08 · 244 words · ~2 min read
ZEN Project Renamed to CZone with 1.0.0 Version Features Planned
AI Tools Development
👤 Technical professionals and developers interested in open-source project development, knowledge base tools, frontend technology, and project naming.
This article records a conversation between the author and Thrimbda on the evening of January 8, 2026, discussing the future development of the ZEN project. Thrimbda suggested turning ZEN into a publishable knowledge base, supporting features like custom frontends, themes, permanent links, document lists, and carousels. The author believes that after completing these features, the ZEN 1.0.0 version can be released and started considering the release plan. Meanwhile, the author discovered that the name ZEN is already used by multiple projects on GitHub and decided to rename it to CZone (czon), which is not occupied on npm and is shorter, making it suitable as a CLI tool name. The project will be hosted on a subdomain of a personal domain and is not intended for commercialization.
- ✨ Discussed the future development direction of the ZEN project with Thrimbda
- ✨ Planned to turn ZEN into a publishable knowledge base
- ✨ Supports custom frontends, themes, permanent links, document lists, and carousels
- ✨ Planned to release the ZEN 1.0.0 version and considered the release plan
- ✨ Discovered that the name ZEN is already used by multiple projects on GitHub
📅 2026-01-08 · 248 words · ~2 min read
Reflections on AI Programming Practice: Avoiding OOP and Over-Compatibility
AI Software Engineering
👤 Software developers, AI technology enthusiasts, programming beginners, engineers concerned with code quality and maintainability
This article documents the author's failed experience with AI programming (Vibe Coding), finding that AI-generated object-oriented code is of poor quality and structurally messy, leading to technical debt explosion. The author analyzes reasons including AI's insufficient design capability for OOP paradigms, lack of architectural guidance, and excessive backward compatibility. Key recommendations are proposed: avoid using object-oriented programming and shift to procedural and functional programming; guide AI to understand Occam's Razor principle to reduce code bloat. These measures aim to enhance the quality and maintainability of AI-generated code.
- ✨ AI-generated object-oriented code is of poor quality, structurally messy, leading to technical debt explosion
- ✨ AI has insufficient design capability for OOP paradigms and lacks business domain modeling
- ✨ AI lacks architectural guidance, adopts lazy strategies, resulting in bloated code
- ✨ Excessive backward compatibility increases code complexity and maintenance costs
- ✨ Recommend avoiding OOP and shifting to procedural and functional programming
📅 2026-01-07 · 693 words · ~4 min read
Module-Level Human-Machine Collaborative Software Engineering Architecture Design
AI Software Engineering
👤 Software engineers, AI researchers, technical managers, and practitioners focused on human-machine collaboration and automated software development.
This paper addresses the issues of poor quality, unclear boundaries, and slow speed in existing AI Agents for code module implementation by proposing a module-level human-machine collaborative software engineering architecture. The architecture generates Protocol Spec through rapid intent alignment, then parallelly generates implementation, test, and benchmark specifications, and ensures implementation quality through multi-level arbitration mechanisms. Core designs include layered collaboration, specialized division of labor, and separation of concerns, with clear acceptance criteria (unit test passing, no performance degradation) to establish trust mechanisms and eliminate human control desires. The paper also discusses unresolved issues such as improving Protocol Spec quality and avoiding arbitration loops, and envisions the possibility of using higher-level AI to replace human supervision.
- ✨ Existing AI Agents have issues with poor quality, unclear boundaries, and slow speed in code module implementation
- ✨ Proposes a module-level human-machine collaborative architecture that generates Protocol Spec through rapid intent alignment
- ✨ The architecture adopts layered collaboration, parallelly generating Implementation Spec, Test Spec, and Benchmark Spec
- ✨ Ensures implementation quality through multi-level arbitration mechanisms, reducing human intervention
- ✨ Defines clear acceptance criteria: unit test passing and no performance degradation, to establish trust mechanisms
📅 2026-01-05 · 1,384 words · ~7 min read
How to Address Human Desire for Control: On Controllable Trust in Human-Machine Collaboration
AI Research
👤 Software engineers, AI researchers, human-computer interaction designers, complex system managers, professionals interested in autonomous systems and trust building
This paper explores the root causes of human desire for control in human-machine collaboration, arguing that it stems from rational concerns about loss of control over outcomes. To address this, the article introduces the concept of 'controllable trust' and constructs a two-layer multiplicative model: the foundational layer is intent alignment (including expression, value, dynamic, and structural alignment), and the execution layer is the risk control triangle (predictability, intervenability, and recoverability). The article further reveals the fractal recursive structure of intent alignment and proposes a 'well-organized agents' implementation framework, making agent organizations a mirror of human intent. This framework shifts the human role from operator to architect and governor, allowing the desire for control to be exercised at a higher level, thereby liberating productivity and enabling scalable collaboration.
- ✨ The desire for control stems from rational human concerns about loss of control over outcomes, not from a fixation on power.
- ✨ Controllable trust is key to liberating the desire for control and achieving scalable productivity in human-machine collaboration.
- ✨ Controllable trust consists of a two-layer multiplicative model formed by intent alignment and the risk control triangle.
- ✨ Intent alignment has a fractal recursive structure, requiring self-similar alignment across multiple scales.
- ✨ Proposes a 'well-organized agents' framework, making agent organizations a mirror of the fractal intent structure.
📅 2026-01-05 · 1,574 words · ~7 min read
Embracing Finite Design for Infinite Potential: A New Paradigm for Building Agent Systems Based on LLM Constraints
AI Research
👤 AI researchers, AI system architects, technical decision-makers, and engineers and scholars interested in agent systems and LLM applications
Based on an analysis of the inherent limitations of large language models (LLMs), this paper introduces a new paradigm for constructing powerful agent systems. It identifies three structural constraints of LLMs: non-mandatory coordination, limited computational budgets, and cognitive incompressibility. Rather than attempting to eliminate these limitations, the paper advocates embracing their "finiteness." The core solutions include: externalizing internal contradictions into explicit processes through coordination engineering, optimizing resource allocation under scarcity through AI decision economics, and shifting from static knowledge compression to dynamic information adaptation through cognitive flow management. This "finite agents, infinite systems" paradigm directly addresses the "Münchhausen trilemma" in intelligent system design, providing a theoretical framework and practical guide for building reliable, scalable, and evolvable human-machine collaborative systems.
- ✨ LLMs have three structural constraints: non-mandatory coordination, limited computational budgets, and cognitive incompressibility
- ✨ Shift from pursuing "all-powerful models" to designing "infinite systems that integrate finite intelligence"
- ✨ Coordination engineering externalizes coordination through checklists, parliamentary debate, and constraint solver patterns
- ✨ AI decision economics treats computational power as a scarce resource, establishing market mechanisms for optimal allocation
- ✨ Cognitive flow management abandons the illusion of cognitive compression, managing information flow through navigational interactions
📅 2026-01-05 · 1,852 words · ~9 min read
From Task Management to Strategic Thinking: Experience and Reflection on Using vibe-kanban
Project Management
👤 Project managers, team leaders, technical personnel interested in efficiency tools, professionals seeking to enhance strategic thinking
This article documents the author's experience using vibe-kanban for engineering-level project management starting in early 2026. The author found that this tool shifted their role from Senior Developer to more like Team Leader, enabling parallel management of multiple tasks, but also exposed the conflict between control desire and rapid progress. Through reflection, the author realized that true liberation lies in letting go of control over details, rather than using tools to enhance control. The article also discusses the different abstraction levels of vibe-kanban and tools like Claude Code, and the importance of elevating from team-level management to strategic thinking.
- ✨ vibe-kanban helped the author shift from a developer perspective to a team management perspective
- ✨ The tool exposed the conflict between control desire and rapid progress
- ✨ True liberation lies in letting go of control over details
- ✨ vibe-kanban and Claude Code operate at different abstraction levels and can work collaboratively
- ✨ The author realized the need to enhance strategic thinking skills, not just task management
📅 2026-01-05 · 673 words · ~3 min read
EA Project Introduction: AI-Driven Priority Fund for Quantitative Trading
Quantitative Finance
👤 Investors interested in blockchain investments, quantitative trading, and stable returns, particularly those seeking low-risk, principal-protected priority fund participation.
EA (Earnby.AI) is a priority fund project deployed on the BSC chain, settled in USDC, offering stable returns to investors through AI-driven quantitative trading strategies. The project uses a priority/subordinated capital structure, where priority capital enjoys principal protection, and subordinated capital is borne by the project's own funds to assume risks. The management team consists of professionals in quantitative trading and blockchain, including 5 co-founders. The project offers floating returns, currently with an annualized yield of 12%, and investors can redeem at any time. Strategies include directional portfolio strategies and delta-neutral strategies, with historical performance showing a cumulative return of 39.22% and an annualized return of approximately 22%. The project has no management fees, flexible lock-up periods, and aims to provide low-risk, sustainable returns for investors.
- ✨ EA is a priority fund project deployed on the BSC chain, settled in USDC
- ✨ Utilizes AI-driven quantitative trading strategies, including directional portfolio and delta-neutral strategies
- ✨ Capital is divided into priority and subordinated tiers, with priority capital enjoying principal protection
- ✨ The management team consists of 5 professionals in quantitative trading and blockchain
- ✨ Offers floating returns, currently with an annualized yield of 12%, and investors can redeem at any time
📅 2025-11-01 · 1,525 words · ~7 min read
Full Spectrum Analysis: The Optimal Method for Information Monetization
Quantitative Finance
👤 Quantitative traders, investment strategy developers, financial engineers, and advanced investors interested in the Kelly Criterion and leverage optimization.
This article proposes Full Spectrum Analysis (FSA), an investment trading strategy framework optimized based on the Kelly Criterion. It first analyzes the limitations of the traditional Kelly formula in investment applications, such as lack of leverage and short-selling considerations, and liquidation timing issues. Then, FSA constructs a systematic trading decision model by defining outcome spaces, calculating optimal leverage and compound returns. The article elaborates on the mathematical principles of FSA, including the calculation of expected returns and compound returns, as well as the algorithm for solving optimal leverage using Newton's iteration method. Additionally, it introduces historical backtesting methods (e.g., Gross Profit Margin GPM calculation), considerations for live trading modules, and measures to address black swan events. The core advantage of FSA lies in its ability to utilize imperfect probability information to maximize long-term returns by optimizing leverage decisions, reducing the high requirements for information quality.
- ✨ Full Spectrum Analysis (FSA) is based on the Kelly Criterion, optimizing investment leverage to maximize compound growth rate
- ✨ Define outcome spaces, probability distributions, and returns to calculate optimal leverage and compound returns
- ✨ Use Newton's iteration method to solve for optimal leverage, handling feasible regions and convergence issues
- ✨ Introduce Gross Profit Margin (GPM) for historical backtesting to evaluate strategy profitability and capacity
- ✨ Incorporate symmetric black swan event probabilities to limit leverage and prevent abuse and extreme risks
📅 2025-08-10 · 2,810 words · ~13 min read