# System İlgili Makaleler

HTX Haber Merkezi, kripto endüstrisindeki piyasa trendleri, proje güncellemeleri, teknoloji gelişmeleri ve düzenleyici politikaları kapsayan "System" hakkında en son makaleleri ve derinlemesine analizleri sunmaktadır.

I Built a Bitcoin Buying System: $64,000, The Lower the Score, The More I Buy

Australian trader Jake Pahor shares his personal Bitcoin investment system. After losing money on altcoins in the last cycle, he now holds 100% Bitcoin, viewing it as the benchmark for the crypto asset class. His strategy centers on a dynamic dollar-cost averaging plan driven by the CSH Risk Score (a proprietary metric). He buys only when the score is between 10 and 30, purchasing more when the score is lower. Exit rules are also predefined. Currently, the CSH score is 25.6, indicating an "early cycle" phase, so his regular buying continues while larger purchases await a drop below 20. He emphasizes that a robust system, written calmly in advance, is crucial for withstanding market emotions. He also monitors key metrics like Bitcoin dominance and the TOTAL3/BTC ratio, noting that altcoin season hasn't begun yet based on historical patterns. The article's core message is that the right answer to "Should I buy now?" is not a specific recommendation but a personalized system that fits one's life and risk tolerance.

marsbit07/27 11:59

I Built a Bitcoin Buying System: $64,000, The Lower the Score, The More I Buy

marsbit07/27 11:59

Claude Code Slashes 80% of Prompt Tokens, But Opus 5 Just Adds Them Right Back In

Claude Code, the AI coding assistant from Anthropic, recently announced a massive reduction of over 80% in its system prompt content for models like Opus 5 and Fable 5. The goal was to remove verbose, often conflicting, rules (like strict commenting and documentation requirements) and replace them with a simpler directive: write code that matches the style of the surrounding project. This "pruning" aims to make the model more efficient by reducing internal conflict from overlapping instructions, with no measurable performance drop reported. However, a developer's (@chenchengpro) investigation revealed a twist. While the prompt was drastically cut from 15,225 characters in Opus 4.7 to 4,467 in Opus 4.8, it *increased* by approximately 72% to 7,694 characters in Opus 5. This isn't a contradiction. The "over 80% cut" refers to the overall shift from the old, detailed rulebook-style prompts to a new, streamlined system. The 72% increase for Opus 5 represents new, targeted instructions added to manage the model's enhanced capabilities. Opus 5 is more proactive—it likes to report progress, generate longer outputs, use sub-agents, and expand task scope. The added prompt content (roughly 3,755 characters) primarily provides guidelines for "Delivering work" (controlling task scope, progress reporting) and "Corrections" (limiting excessive self-correction). These new rules are necessary to curb potential over-engineering on simple tasks, ensuring efficiency even as the model becomes more independent. In short, the old, restrictive manual was deleted, but new guidelines were written to harness the model's newfound initiative.

marsbit07/27 11:37

Claude Code Slashes 80% of Prompt Tokens, But Opus 5 Just Adds Them Right Back In

marsbit07/27 11:37

TradFi in One Minute: What is TradFi?

"TradFi in a Minute: What is TradFi?" provides an introductory explanation of TradFi, or Traditional Finance. It describes TradFi as the foundational system that drives the flow of funds and market operations. The article emphasizes that even the cryptocurrency (Crypto) market must operate within the rules established by this traditional financial framework. The content is presented alongside an introductory video, framing this as the first episode in a series called "TradFi 101" aimed at exploring the underlying logic of the traditional financial system.

marsbit07/18 04:09

TradFi in One Minute: What is TradFi?

marsbit07/18 04:09

The Scriptures Chanted by OpenAI and Anthropic Might Be Crooked

In the current AI landscape, "Harness-style" Multi-Agent Systems (MAS)—where multiple AI agents with temporary roles collaborate under a central workflow for task efficiency—dominates the conversation, championed by players like OpenAI and Anthropic. However, the author argues this approach, focused on orchestration and software engineering, may be misguided. A more transformative, yet less discussed, alternative is the "Protocol-Native Agent System." Here, the core unit shifts from task-specific agents to persistent "Personal Agents" or "unmanned companies" that represent individuals. These agents possess sovereignty, long-term memory, identity, resources, and relationships. This paradigm change transforms MAS from a distributed software system into a digital society. Collaboration can no longer rely on shared prompts or context, but must be built on protocols governing identity, trust, incentives, reputation, and value exchange—essentially, "Protocol as Organization." The future's true challenge lies not in improving single-agent capabilities, but in enabling long-term coordination among autonomous entities with differing goals, world models, and values. The author suggests that future organizations might themselves be dynamic alliances of such sovereign agents, leading to an "intelligence-native civilization."

marsbit05/28 05:32

The Scriptures Chanted by OpenAI and Anthropic Might Be Crooked

marsbit05/28 05:32

How to Become a Pro Claude User in 30 Days?

"How to Become a Claude Power User in 30 Days" outlines a structured month-long program to transform from a casual user into someone who leverages Claude as a core productivity system. The first week focuses on mastering prompt structure (Role, Context, Task, Format, Constraints), understanding context windows, and setting up foundational Projects and Memory for personalized context. The second week involves building reusable workflows for research, writing (using a two-step outline-first process), and decision-making. The third week shifts to automation: using Claude Cowork for autonomous file tasks, connecting tools like Google Drive and Slack, and setting scheduled automation. The final week is for compounding gains: optimizing all workflows based on feedback, building a personal knowledge repository, teaching the system to a colleague, and designing a complete, ideal "Claude Operating System." By day 31, the user operates with an autonomous assistant that handles routine tasks with deep context, freeing them for high-value creative and strategic work. The core message is that consistent, systematic configuration over 30 days creates a powerful, personalized productivity advantage.

marsbit05/20 08:06

How to Become a Pro Claude User in 30 Days?

marsbit05/20 08:06

Only Work 2 Hours a Day? This Google Engineer Uses Claude to Automate 80% of His Work

A Google engineer with 11 years of experience automated 80% of his work using Claude Code and a simple .NET application, reducing his daily work from 8 hours to just 2–3 hours while generating $28,000 in monthly passive income. The key to this transformation lies in three core elements: First, using a structured CLAUDE.md file based on Andrej Karpathy’s principles—Think Before Coding, Simplicity First, Surgical Changes, and Goal-Driven Execution—reduces Claude’s rule violations from 40% to just 3%. Second, the "Everything Claude Code" system acts as a full AI engineering team, with 27 pre-built agents for planning, reviewing, and executing tasks across multiple AI platforms. Third, a hidden token consumption issue in Claude Code v2.1.100 was identified, where 20,000 extra tokens were silently added, diluting instructions and reducing output quality. A quick fix using npx downgrades the version to avoid this. The automated system enables code generation, testing, and review to run autonomously in 15-minute cycles. The engineer now only reviews output, saving 5–6 hours daily. The setup takes less than 20 minutes, and the return on time investment is significant—potentially saving $10,000–$12,000 monthly for those valuing their time at $100/hour. The article emphasizes that managing AI systems, not just using them, is the new critical skill, enabling a shift from doing work to overseeing automated processes.

marsbit04/15 04:10

Only Work 2 Hours a Day? This Google Engineer Uses Claude to Automate 80% of His Work

marsbit04/15 04:10

Apple at 50: The Genius Exits, The Machine Lives Forever

Apple's 50-year journey is a garage startup story that began with Ronald Wayne, the co-founder who sold his 10% stake for $800 to avoid personal financial risk. His departure set a pattern: Apple evolved from a company driven by visionary genius to a risk-averse system prioritizing certainty over innovation. Under Tim Cook, Apple shifted from product-driven growth to financial engineering, spending over $700 billion on stock buybacks to boost earnings per share and please Wall Street. Its supply chain strategy also changed, moving significant iPhone production to India to mitigate geopolitical risks and reduce dependency on any single region. Meanwhile, in the AI era, Apple leverages its App Store dominance, collecting billions in "Apple tax" from AI apps like ChatGPT without leading in AI innovation itself. As Cook’s potential successor, John Ternus—a pragmatic operator—rises, Apple solidifies its identity as a machine optimized for stability, control, and execution. The era of charismatic founders has ended; the system now reigns supreme.

marsbit03/31 03:06

Apple at 50: The Genius Exits, The Machine Lives Forever

marsbit03/31 03:06

Behind the Gold's Pullback Lies a More Significant Issue: The Loosening of the Old System

Gold's recent pullback has drawn superficial comparisons to the 1979 cycle, but the underlying global dynamics have fundamentally shifted. In 1979, gold fell due to extreme Fed rate hikes under Volcker and a renewed belief in U.S. credit stability, which attracted capital back to dollar assets. Today, the situation is inverted. The U.S. faces massive debt, uncontrolled deficits, and a financial system hypersensitive to interest rates. The critical change is the structural challenge to the dollar-centric system itself, particularly the petrodollar cycle. The ongoing Middle East conflict is not an isolated event but a self-reinforcing crisis that disrupts energy flows, elevates costs, and strains fiscal capacities—undermining the dollar’s role in global energy trade. This suggests that the recent gold sell-off is a short-term profit-taking move after a strong rally, rather than a loss of long-term value. The broader narrative is one of a deteriorating monetary order: the U.S. can no longer easily suppress inflation with high rates or assert global dominance as before. As the world reassesses the entire credit system, gold is poised to assume a new role as a hedge against systemic fragility.

Odaily星球日报03/23 12:13

Behind the Gold's Pullback Lies a More Significant Issue: The Loosening of the Old System

Odaily星球日报03/23 12:13

Using AI for Weather Prediction: Earn $200 a Day While Doing Nothing?

Using AI for Weather Prediction: Can You Really Earn $200 a Day? This article explores how to leverage AI and data analysis to profit from weather prediction markets like Polymarket, focusing on Shanghai’s temperature forecasts. The system relies on Shanghai Pudong Airport (ZSPD) weather station data, sourced via Wunderground, rather than general city forecasts. Key insights include: - Temperature data is reported in whole Fahrenheit values in METAR format, not Celsius, affecting precision. - Historical data shows daily high temperatures most frequently occur between 11:00-13:00, peaking at 12:00 in summer (27.6% of days). Three effective prediction methods were implemented: 1. **Integrated Forecasting**: Combines Weather Company (WC) and ECMWF model data, weighted by weather conditions (e.g., sunny days favor WC). 2. **Real-Time Correction**: Uses morning temperature rise data and historical patterns to extrapolate the daily high, adjusted for cloud cover and wind. A Kalman filter dynamically weights real-time data vs. forecasts. 3. **Temperature Trend Model**: Predicts whether the day will be warmer/cooler than the previous day using pre-dawn data (pressure changes, wind, cloud cover, recent trends). It performs best in winter (clear signals) but poorly in autumn (63.7% accuracy). Two failed methods—Fourier analysis (systematic underestimation) and ERA5 peak-time prediction (insufficient precision)—were discarded. Case studies demonstrate the system identifying mispriced market opportunities, such as recognizing nighttime warming from moist air during rainfall, when public sentiment lagged. Limitations include autumn inaccuracy, lack of real-time pressure data, and unresolved coastal wind effects. Ultimately, the goal isn’t perfect accuracy but leveraging informational edges when odds are favorable.

marsbit03/18 12:18

Using AI for Weather Prediction: Earn $200 a Day While Doing Nothing?

marsbit03/18 12:18

Epic Blunder: South Korean Exchange "Slip-up" Sends Out $44 Billion in Error

In a major operational error, South Korean cryptocurrency exchange Bithumb mistakenly distributed Bitcoin worth over $44 billion to users, causing a sharp drop in the platform’s Bitcoin price and triggering a regulatory review. The incident occurred when Bithumb intended to issue a promotional cash payment of 2,000 won (approx. $1.4) per user. Due to a system error, 695 users each received at least 2,000 Bitcoin instead. The exchange restricted trading and withdrawals within 35 minutes and has since recovered 99.7% of the wrongly distributed Bitcoin. As a result, Bitcoin prices on Bithumb temporarily plunged by 17% before partially recovering. South Korea’s Financial Services Commission described the incident as exposing "the vulnerability and risks of virtual assets" and announced plans to examine internal controls and operations at Bithumb and other exchanges. If violations are found, on-site inspections will follow. Bithumb attributed the mistake to an internal operational error and emphasized that it was not caused by external hacking or security breaches. Approximately 0.3% of the Bitcoin, worth around $132 million, remains unrecovered. The error occurred when the system incorrectly substituted "Bitcoin" for "Korean won," amplifying the reward amount by billions of times. As South Korea’s second-largest crypto exchange, Bithumb’s incident may lead to stricter industry-wide risk management and technical reliability standards.

华尔街日报02/08 00:59

Epic Blunder: South Korean Exchange "Slip-up" Sends Out $44 Billion in Error

华尔街日报02/08 00:59

活动图片

Project Updatesright-arrow