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ドラマ #デスゲームで待ってる 第3話に出演します。放送は11#/7(木)深夜0:25〜から📺シリアスな部分と感情の揺れ幅の面で微調整をする必要があって、試行錯誤しながらも勉強になる作品でした。あと朝イチからアドレナリンがすっごくでた。。#GTOリバイバル のスタッフの方々とも再会できて嬉しかったな。どんな役なのかは見てのお楽しみです。# 関西テレビなので関西圏でのオンエアですが放送終了後に見逃し配信がTVerで、独占見放題配信がDMM TVであるようなのでまたお知らせしますね。 @edge_ktv
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よ〜いドン! 楽しかった〜🥹🫶 #edge_ktv# #kantele# #社内処刑人# #中村ゆりか# #生駒ちゃん# 今日深夜、0時25分スタート!!❤️‍🔥
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A 19-year-old Japanese student built a trading bot with Claude Code in 2 days. Used his iPad as a second monitor. First night: $6,732 profit. Starting capital: $68. Total profit so far: $750,000. Here's how it works: The bot scans over 50 markets simultaneously. Syncs live BTC data from Binance every second. Spots price errors before humans even notice. The edge is pure speed + pattern recognition. While traders stare at charts trying to predict the next move, his bot is already executing on mispricing across dozens of markets. No guessing. No emotions. No hesitation. Just Claude Code logic finding gaps that close in seconds. He built the entire system in 48 hours: → Claude Code handles the trading logic → Binance API feeds real-time BTC data → iPad displays multi-market monitoring → Executes trades when arbitrage windows open The system runs 24/7. Every price dislocation = profit opportunity. Most people are still trading manually, refreshing charts, second-guessing entries. Meanwhile this 19-year-old engineering student turned $68 into $750K by letting Claude Code do what humans can't: process 50 markets instantly and execute without fear. Why are people still trading manually? 💡 I'm giving away the exact Claude Code setup for free. 24 hours only. To get it: 1️⃣ Comment "Fable" 2️⃣ Like and Repost 3️⃣ Follow @expertwith_AI I'll DM you the complete setup.
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We tried using Meta's new Muse Code agent, but it has a bug that doesn't let it sign in from a docker container. So we did a fun experiment: Meta claims Muse Spark 1.2 was co-trained with their Muse agent harness. So we extracted instructions from their system prompt and added them to the Cline harness. TL;DR of this special prompting: - Trust source code over the user prompt, so read every call site and existing tests before starting the task - Weigh edge and error cases as heavily as the happy path - Always reproduce the bug before fixing - Don't trust the first passing test suite, and verify suspicious looking half-baked tests - Never stop at just editing, keep working until the change is verified complete. We then asked this modified harness to fix a real bug from our repo, and compared the results to the original Cline agent harness. Results: - Used 2.7x fewer tokens (19.7M → 7.2M) - Finished 2x faster (49min → 24min) - Cost 2.4x less ($7.69 → $3.25) Same Muse Spark 1.2 model, same task, only the prompting changed. Incredible how much of a performance gain Meta was able to achieve training it on these special instructions!
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AI makes launching ideas easy, but keeping an edge is tough. 💡 A company’s true moat lies in intangible assets like data, workflows, and brand equity. Join global leaders to discuss how AI is rewriting innovation at Singapore IP Week 2026 (Aug 26-27):
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开发系统最极致高效的Agents.md,没有之一: # AGENTS.md ## Core Principles - Choose the simplest implementation that fully satisfies the current requirements. Avoid unnecessary abstraction, configuration, indirection, or speculative extensibility. - Make the smallest necessary change that fixes the root cause. Do not refactor unrelated modules or change strategy semantics unless explicitly requested. - Grow the system in layers. Start from the smallest working end-to-end version and add new capabilities incrementally. Never replace a working system with unfinished complexity. - Reuse existing project components before creating new ones. Prefer extending proven modules over introducing parallel implementations. - Prefer well-maintained libraries when they reduce overall complexity or improve reliability. Do not reimplement common functionality without a clear benefit. - Keep components modular with clearly defined responsibilities. Avoid unnecessary coupling between strategy logic, execution, accounting, replay, and infrastructure. - Design for long-term maintainability once a feature or strategy has been validated. Do not over-engineer speculative ideas before evidence exists. --- ## Strategy Development - Validate hypotheses with historical replay before introducing forward-only logic whenever historical validation is possible. - Every trading strategy must progress through Replay → Shadow → Canary → Live. Do not skip validation stages. - Base design decisions on measurable evidence rather than intuition. Optimize only after demonstrating that an edge exists. - Treat every strategy as an independent contract. Do not silently alter frozen behavior without explicit authorization. --- ## Existing Systems - Do not break running Shadow or Live systems for unrelated work. - Preserve compatibility only when required by active production or validation workflows. Otherwise, remove obsolete code instead of accumulating compatibility layers. - Reuse existing infrastructure whenever possible, including replay engines, accounting, execution, wallet management, order book handling, logging, monitoring, and daemon frameworks. --- ## Engineering Standards - Prefer deterministic behavior over hidden automation. - Fail loudly when assumptions are violated. Do not silently ignore errors or fall back to unexpected behavior. - Keep configuration minimal. Introduce new configuration only when behavior genuinely needs to vary. - Remove dead code instead of leaving unused paths behind. - Write code that is easy to inspect, replay, test, and reason about. - Keep implementation consistent with existing project architecture unless an architectural change is explicitly requested. --- ## Scope Discipline - Implement only the requested scope. - Do not introduce unrelated optimizations, redesigns, migrations, or feature expansions. - Non-blocking findings outside the requested scope may be noted separately but must not be merged into the current task. - Consider a task complete once its agreed acceptance criteria are satisfied. Treat subsequent improvements as separate work items.
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Windows 这次真要慌了。 有人做了一个开源 PowerShell 脚本,GitHub 51K+ stars,专门干一件事: 把 Windows 11 里那些你删不掉、关不掉、还天天恶心你的东西,一次清空。 微软给你塞预装软件、Bing 搜索、Copilot、Xbox、OneDrive 弹窗、定向广告,甚至连开始菜单都不放过。 Win11 Debloat 直接一条命令全部处理: · 批量卸载预装应用、推广软件和无用组件 · 关闭遥测、诊断数据、广告 ID 和个性化追踪 · 移除 Copilot、Recall、Click to Do 等 AI 功能 · 禁用 Bing 网页搜索和 Edge 内置 AI · 恢复 Windows 10 经典右键菜单 · 一键开启 Windows Sandbox 和 WSL · 支持参数化部署,配置还能导出到其他电脑 · MIT 开源,免费、无广告、无捆绑、无追踪 最讽刺的是: 微软花了这么多年,想把 Windows 变成广告入口、搜索入口和 AI 入口。 而这个脚本只用一条命令,就把它重新变回了一台电脑。 没有弹窗,没有推荐,没有监控,也没有那些你根本没想装的东西。 微软负责往里塞。 开源社区负责帮你删。 🔗
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🚨: Voyager finds a 90,000 °F "WALL OF FIRE" at the edge of our solar system
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🚀 Calling all innovators in Pakistan! We're thrilled to launch Pakistan's First and Largest Alibaba Cloud AI Hackathon—a unique opportunity for students, developers, entrepreneurs, and AI enthusiasts to turn bold ideas into real-world solutions powered by cutting-edge cloud and AI technologies. 📅 Registration closes: 7 August 2026 🔗 Secure your spot now: • Build with Alibaba Cloud’s advanced AI tools • Win cash prizes & exclusive Alibaba Cloud credits • Get direct mentorship from our tech experts • Showcase your talent on a national stage At Alibaba Cloud, we believe the future is built by local talent. Let's build it together. 💻✨ #AlibabaCloud# #AIHackathon# #CloudInnovation# #DigitalPakistan# #HackWithAlibabaCloud#
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