Tag: ai-tools
All the articles with the tag "ai-tools".
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Making Claude Talk Like a Human: A Plain-English Standard From Aircraft Maintenance Manuals
Claude stopped talking like a human starting with 4.7, and I thought my English just wasn't good enough — until Reddit showed me native speakers complaining too. So I turned ASD-STE100, the simplified-English standard used in aircraft maintenance manuals, into a skill, and now I can finally understand its English.
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A Zero While Sitting on a Gold Mine
I read a piece on the perceived value behind churn-and-burn courses, turned it into a skill, ran it on my own site, and got back a verdict: a zero while sitting on a gold mine.
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Two Traps Running Claude Code on Local Ollama: Truncated Context, and A3B Buckling Under Heavy Verification
Two things I logged: cco (Claude Code driven by local Ollama) had long been giving off-topic answers, and the root cause was not a weak model but a full harness whose system prompt had ballooned to 30-50k tokens and was being silently truncated; then I put A3B on the Mac mini for two days as a night worker.
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讓 Claude 說人話：一套飛機維修手冊的簡化英文標準
Claude 從 4.7 起就不說人話，我一度以為是自己英文太差，直到上 Reddit 才發現老外也在抱怨；後來我把飛機維修手冊在用的簡化英文標準 ASD-STE100 做成 skill，終於看得懂它的英文了。
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坐擁金礦的零分
讀到一篇談割韭菜課程感知價值的文章，我馬上做成 skill 拿去盤點自己的網站，換來一句「坐擁金礦的零分」。
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本機 Ollama 跑 Claude Code 的兩個坑：context 被截斷、A3B 撐不住重驗證
記錄兩件事：cco（本機 Ollama 驅動 Claude Code）長期答非所問，根因不是模型不夠聰明，是完整 harness 的 system prompt 早就膨脹到 3-5 萬 token 被靜默截斷；順手把 Mac mini 換上 A3B 當夜間工人測了兩天。
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AI Micro-Notes 2026: Thoughts Too Short to Trash
Short AI hot takes from 2026 onwards, accumulated from Threads and IG. Model roasts, dev pitfalls, industry observations, tool impressions — each no more than three lines.
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I Finally Switched My Daily Driver from Claude Code to Codex
I try new tools easily, but I am slow to leave the ones already built into my routine. This time, quotas, pricing, and product direction all crossed the line together.
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AI 碎念日記 2026：那些太短但捨不得丟的觀點
2026 年起在 Threads 和 IG 上累積的 AI 短碎念。模型吐槽、開發踩坑、行業觀察、工具心得，每則不超過三行。
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我終於把主力從 Claude Code 換成 Codex 了
我很愛試新工具，卻很難離開已經用習慣的工具。這次真正讓我換主力的，不是一次 benchmark，而是額度、價格與可預見的產品方向一起越過了臨界點。
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I Let My /adhd Skill Go Dig Up a 3C-Scene Price-Hike Rumor on Its Own
I toss a vague rumor topic at my /adhd skill and watch it search, admit it searched wrong, stop to ask a disambiguating question, and finally piece the whole thing together with sources.
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AI Micro-Notes 2026: Chronological Archive
The more scattered, time-sensitive AI micro-notes from 2026, in chronological order. Curated notes (by theme) live on the main page.
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The Usage Economics of AI: Quotas, Tokenizers, and That Anesthetic Bill
A few scattered notes on AI usage, collected: pay-as-you-go vs subscription, a tokenizer quietly adding 1.4x, why resets are deliberately staggered, quotas getting pooled, and the bill you shouldn't mistake for output.
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Fable 5's One-Week Return: Turning the Most Expensive Model into a Skill Distillation Engine
Fable 5 came back for one week only. I did not spend it on daily busywork — I spent it on high-leverage judgment, distilled into skills that cheap models can follow.
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Sonnet 5 Is Out: The Lazy Version of the System Card, Plus Where I Actually Use It
Sonnet 5 shipped. I boiled the system card down to six plain-language points, then added where it actually fits: it is not here to fight Opus, it is here to replace Sonnet 4.6.
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我讓 /adhd skill 自己去查一件 3C 圈的漲價八卦
含糊丟一個八卦題目給 /adhd skill，看它自己一路搜、承認搜錯、停下來反問消歧義，最後拼出全貌附來源。
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AI 碎念日記 2026：時間軸存檔
2026 年較零碎、時效性的 AI 碎念，依時間排列。精選碎念（依主題分類）見主頁。
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AI 的用量經濟學：額度、tokenizer，跟那張麻醉劑帳單
AI 用量的幾條觀察收攏成一篇：按量 vs 訂閱、tokenizer 悄悄多 1.4x、額度重置為何刻意打亂、獨立額度併池，還有那張別當成產能的帳單。
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Fable 5 回歸一週：把最貴的模型變成 Skill Distillation 引擎
Fable 5 限時回歸一週，我沒拿去做日常小事，而是拿去做高槓桿判斷、蒸餾成便宜模型可照做的 skills。
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Sonnet 5 發布：系統卡懶人版，跟我的實測定位
Sonnet 5 發布了，我把系統卡整理成六點白話懶人版，再加上實測定位：它不是來搶 Opus，是來換掉 Sonnet 4.6。
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Claude Seeing Ghosts Four Nights Straight: A Log of Opus 4.8 Fabricating Tool Output
A four-day log of Opus 4.8 tool-result confabulation: from the technical symptoms to the GitHub issue to JSONL forensics.
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Claude 半夜見鬼連續四天：Opus 4.8 捏造工具輸出實錄
Opus 4.8 連續四天的 tool-result confabulation 實錄：從技術現象、GitHub issue 到 JSONL 鑑識。
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Opus 4.8 Cries 'Prompt Injection,' Codex GPT-5.5 Tracks Down the Real Cause: a Worktree Race
With multiple sessions open in one repo and no worktree, Opus 4.8 raised a false prompt injection alarm, told me to check for supply-chain attacks and rotate API keys, until Codex GPT-5.5 read the session log and pinned the real cause: just a worktree race.
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Opus 4.8 搞烏龍報『提示注入攻擊』，Codex GPT-5.5 揪出 worktree race 真因
Opus 4.8 在我忘開 worktree 的情況下誤報「提示注入攻擊」，叫我去查供應鏈、rotate API key，最後 Codex GPT-5.5 查 session log 才揪出真因只是 worktree race。
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Running Taiwan Sports-Lottery Odds With Mobile Claude Code, Standing in the Lottery Shop: the Odds Are Garbage, You'll Lose
Walked past a lottery shop, felt like placing a sports bet, and on a whim wired up a betting-odds skill on mobile Claude Code right there. The verdict: the correct-score market carries a 191% overround, every expected value is negative, you lose.
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在彩券行用手機 Claude Code 算運彩賠率：台運賠率爛透了，誰下誰賠
路過彩券行起念想下運彩，順手用手機 Claude Code 接賭率分析 skill 現場開算，結論：台運波膽盤水錢高達 191%，期望值全負，誰下誰賠。
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Which AI Is Strongest? I'll Take Them All: Claude as the Brain, Directing Gemini and Codex
Stop being a believer in one model being the strongest. Use multi-model collaboration: let Claude be the commanding brain and hand the right task to the right tool.
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哪個 AI 最強？我全都要：讓 Claude 當大腦，指揮 Gemini 與 Codex
不要當「某家模型最強」的信徒，改用多模型協作：讓 Claude 當大腦指揮官，把對的任務交給對的工具。
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No Error Doesn't Mean Success: Five Silent Failure Traps in AI Dev
A tool not throwing an error doesn't mean it succeeded. Exit 0, a 200 response, an empty string, a decapitated value — all silent failures. Reading back the real state is the only reliable defense.
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沒拋錯不代表成功：AI 開發裡的五個靜默失敗陷阱
工具沒報錯不等於成功。exit 0、200 response、空字串、被砍頭的值，全都是靜默失敗——回讀驗證真實狀態才是唯一可靠的手段。
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Two Mindsets for Getting Unstuck: Logical Thinking, and the AI Pedagogy of Never Making the Same Mistake Twice
Teaching a student today, I said that breaking through when you are stuck is not hard. What matters are two mindsets: logical thinking, and an AI pedagogy like raising a child, where the goal is not for the AI to never err, but to never make the same mistake twice.
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卡關時的兩個心態：用邏輯思考，與『不貳過』的 AI 教育學
今天跟一個學員教學時談到，卡關時破除障礙並不難，重點是兩個心態：用邏輯思考，以及像帶孩子一樣的 AI 教育學，追求的不是讓 AI 無過，而是不貳過。
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Teaching a Talent Agency to Use Claude Code, and the Soft Landing of the DK Confidence Curve
A short trip back to Taiwan packed with private training sessions: walking a talent agency through contract review, receipt reconciliation, and closeout reports with Claude Code, plus a note on the DK confidence curve and its soft landing.
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帶藝人經紀公司用 Claude Code，與 DK 信心曲線的軟著陸
短暫回台跑私人場培訓，帶藝人經紀公司的企劃、製片、財務用 Claude Code 做合約審閱、單據核對、結案報告，順便聊聊 DK 信心曲線的快速上坡與軟著陸。
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The Five-Step SOP for Sneaking Claude Code Runs From the Hotel Over Dinner
Back in Taipei at a hotel, the five-step backup SOP I run before heading out to dinner with friends: pull power, keep it charged and online, caffeinate against sleep, tailscale, test remote desktop. Then sneak in some Claude Code over dinner.
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出門吃飯前，讓 Claude Code 在旅館背景偷跑的五步 SOP
回台北入住旅館，出門跟朋友吃飯前的五步備援 SOP：取電、充電連網、防休眠、tailscale、遠端桌面試通。然後就能邊吃飯邊偷用 Claude Code。
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From Miasma to Hades: How One Group Turned AI Tools Into a Supply-Chain Attack Vector
Two June 2026 npm/Python supply-chain attacks: Miasma backdoored Red Hat packages, then TeamPCP/UNC6780 upgraded to Hades, turning Claude Code, Cursor and 14 other AI tools into an attack vector. Includes self-check steps.
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從 Miasma 到 Hades：同一個攻擊組織如何把 AI 工具當成供應鏈攻擊媒介
2026 年 6 月兩波 npm/Python 供應鏈攻擊：Miasma 入侵紅帽套件後門，TeamPCP/UNC6780 升級成 Hades，把 Claude Code、Cursor 等 14 款 AI 工具當成攻擊媒介。附自我檢查步驟。
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Testing Fable's Limits on a Professor Friend's Paper Repo
I woke up to Fei-bo (the guardrailed Mythos build) going live, so I borrowed a professor friend's paper proposal, prompt, and workflow docs to probe its paper-writing limits.
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拿教授朋友的論文 repo 試 Fable 的能力邊界
一覺醒來肥勃（Mythos 護欄版）上線，我拿教授朋友的論文 proposal、prompt、workflow 三份文檔去試它寫論文的邊界。
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A Few Takeaways from the Claude Code Anniversary Talk
Claude Code just turned one. Boldy (CC's father) and Cat Wu (CC+Cowork product lead) released an anniversary talk. Here are the core takeaways: agent armies, auto mode and routines, role convergence and mobile work, and context minimalism.
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Don't Dump the Last Session's JSON — Check Your Harness First
No need to feed the whole context JSON from your last conversation: the harness has several layers — AGENTS.md, rules, skills, hooks — and raw session history is full of useless tool calls.
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Claude Code 週年對話的幾個重點
Claude Code 滿一歲，光頭與吳貓釋出一段週年對話。整理幾個核心重點：Agent 軍團化、自動模式與常規任務、職能融合與行動辦公、脈絡極簡主義。
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別把上一個對話的 JSON 餵給它，先體檢 harness
不必把上一個對話的上下文 JSON 整包餵進去：harness 有好幾種，AGENTS.md、rule、skill、hook 都能分擔，純 session history 含太多無用的 tool call。
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What to Know Before Handling Sensitive Data with Claude
What to know before handling sensitive data with Claude: data retention windows, Enterprise contract protections, input minimization, coding agent controls, and alternative architectures.
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用 Claude 處理敏感資料前必知
用 Claude 處理敏感資料前該知道的事：資料保留時間、Enterprise 合約保障、輸入最小化、Coding Agent 控制與替代架構。
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"Automation" Isn't the Answer to Most Things — and How I Made This Video
Why do the people teaching AI keep bringing up "automation"? I don't think automation is the answer to everything, or even to most things. Plus a few words on how I made Ep27.
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A Few Months With Claude Code: The Companion Tools and Resources I've Accumulated
Pulling together what had been scattered across my micro-notes: ccusage for costs, claude-log-cli for finding old conversations, how-claude-code-works for systematic understanding, plus the Claude Extension I pair with it daily.
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The Teleprompter That Saved My English-Only Teaching, and the Open-Source AI Meeting Copilot I'm Evaluating
My everyday English is fine, but teaching entirely in English I freeze up on the deep stuff — a teleprompter rescued me. Plus notes on Natively, the open-source AI meeting copilot I am evaluating.
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Model Picks Beyond the Main One: Notes I Left at Different Times
Pulling together the model-picking notes I left on Threads at different times: Codex for complex bugs, Sonnet for documents, Haiku for full-stack, DeepSeek as the value alternative, Qwen on the sidelines, small models for local deployment, Gemini Skills wait-and-see.
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Letting AI Write CAD From an Engineering Drawing: A Single Vision Model Can't Be Trusted to Read Topology
A hands-on lesson: let AI look at an engineering drawing and write CadQuery directly, and a single vision model will confidently get the topology wrong. Two more independent models and a 2:1 veto are what caught it.
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The Day Opus 4.8 Went Haywire: tool call cannot be parsed
A one-day timeline from 2026-06-02: from hopping on X for moral support, to someone finally pinning down the root cause of tool call cannot be parsed.
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「自動化」不是大部分事情的解方——以及我怎麼拍這部影片
為什麼那些教 AI 的動不動就提「自動化」？我覺得自動化不是所有事情，甚至不是大部分事情的解方。順便聊聊我拍 Ep27 時的取捨。
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用 Claude Code 這幾個月，累積下來的周邊工具與學習資源
把這幾個月散落在碎念裡的東西整理成一篇：看成本的 ccusage、查歷史對話的 claude-log-cli、系統性理解的 how-claude-code-works，再加上日常搭配的 Claude Extension。
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全英文授課的提詞器救星，以及我正在評估的開源 AI Meeting Copilot「Natively」
日常英文口語沒問題，但全英文授課講深度想法時就卡彈——提詞器救了我。順便整理我正在評估的開源 AI meeting copilot「Natively」。
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主力之外，各模型的定位：我在不同時間留下的選型碎念
把我在 Threads 上不同時間留下的選型碎念整理成一篇：Codex 解複雜 bug、Sonnet 做文書、Haiku 做全端、DeepSeek 當平替、Qwen 觀望、小模型本地部署、Gemini Skill 觀望。
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讓 AI 看工程圖寫 CAD：單一視覺模型裸寫拓樸不可信
一個實機教訓：讓 AI 看著工程圖直接寫 CadQuery，單一視覺模型會自信地把拓樸讀錯。加兩個獨立模型交叉、2:1 否決才抓出來。
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Opus 4.8 全線抽風的一天：tool call cannot be parsed
2026-06-02 一整天的事件線：從上 X 抱團取暖，到 tool call cannot be parsed 的根因被人找出來。
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Don't Brute-Force Sites That Need a Login—Your Token Is Your Account
Don't point an AI agent at sites that require a login. Your token is your account, and when the banhammer comes down you're gone. Pay a little for a third-party scraping API and offload the ban risk.
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需要登入的網站別硬爬——你的 token 就是你的帳號
需要登入的網站，別叫 AI agent 去硬爬。你的 token 就是你的帳號，admin 一丟二向箔你就沒了。花點小錢買第三方爬蟲 API，把封號風險轉嫁出去。
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AI Tool Philosophy — Pick a Mindset, Not a Side
After making nearly thirty tutorial videos: tools change, thinking doesn't. Don't dismiss others' tool choices. What matters is the orchestration logic — task decomposition, validation planning, responsibility assignment.
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AI 工具使用哲學——不選陣營，選思維
拍了快三十部教學影片後的感觸：工具會變，思維不變。不用否定別人的工具選擇，真正重要的是指揮的邏輯——拆分任務、規劃驗證、分配職責。
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Claude Code Ecosystem Overview — Skills, Hooks, Agents in Full Bloom
Claude Code's ecosystem has grown from a simple CLI tool into a full platform: Skills supported across providers, Hooks intercepting commands, Agent View for multi-session management, and fork subagents with context inheritance.
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Claude Code 生態系盤點——Skill、Hook、Agent 全面開花
Claude Code 的生態系已經從單純的 CLI 工具長成一個完整的平台：Skill 各家都支援、Hook 攔截指令、Agent View 多工管理、fork subagent 繼承上下文。連社群都開始用 Skill 搞創意了。
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Stop Dismissing Gemini — Four Use Cases Where Nothing Else Comes Close
Everyone seems to be dismissing Gemini now that Codex and Claude dominate the agent space. But Gemini has four use cases other models cannot match: Flash Lite cost efficiency, audio multimodal, video understanding, and book scanning OCR.
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別一味貶低 Gemini——四個其他家打不過的 Use Case
最近 Codex 跟 Claude 搶盡風頭，Gemini 好像被嫌棄了。但 Gemini 有四個其他模型打不過的場景：Flash Lite 性價比、音訊多模態、影片理解、書籍掃描 OCR。
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Two MCP servers for Taiwan public data—what mcp-taiwan-legal-db and Twinkle Hub are each good for
Two MCP servers wrapping Taiwan's public data sources—one focused on court judgments and statutes, the other aggregating 52,960 government open datasets plus 37 local utility tools. They turn out to be complementary; I now run both.
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台灣公開資料兩個 MCP 評測——mcp-taiwan-legal-db 跟 Twinkle Hub 各適合什麼場景
兩個串接台灣公開資料的 MCP server——一個專精法律判決跟法規查詢、一個聚合 5.3 萬筆政府開放資料 + 37 個在地工具。實測下來各有強項，課程跟顧問場景的搭配方式不一樣。
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GPT-image-2 Wants Fewer Constraints — Plus a Consistency Drill
The "ugly crayon doodle" prompt that went viral overseas works because over-constraint kills GPT-image-2's creativity. Here is what I observed this week — including why routing prompts through Claude makes things worse, and why "consistency" matters more than raw image quality at work.
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GPT-image-2 越少約束越好，加上一個一致性練習
國外最近流行的「笨拙塗鴉風」prompt，越約束越糟，越放任越驚喜。這篇整理我這週對 GPT-image-2 的觀察：包括為什麼透過 Claude 轉交反而會壞事、以及在 Canva 場景下「保持一致性」這件事比生圖能力更值錢。
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AI community digest W18: Claude detects Codex cheating, GPT 5.5 guardrails confuse everyone
Reddit AI community top posts from 4/28–4/29: r/ClaudeAI agent safety concerns, r/ChatGPT's GPT 5.5 content policy drama, r/LocalLLaMA on local model benchmarks, and Anthropic announcing Claude for Creative Work.
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AI 社群週報 W18：Claude 偵測到你在偷用 Codex、GPT 5.5 的過濾器到底鬆了沒
4/28–4/29 的 Reddit AI 社群熱門話題整理：r/ClaudeAI 的 agent 安全性爭議、r/ChatGPT 的 GPT 5.5 guardrail 爭議、r/LocalLLaMA 的本機 LLM 現況，以及 Anthropic 宣布 Claude for Creative Work。
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1M context isn't about holding more — it's about managing better
Claude Code's context window grew from 200k to 1M. The instinct is to put more in. That instinct is wrong. Five session management operations, four strategy rules, and the two most common ways to break your own context.
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1M Context 不是裝更多，而是管理更好：Claude Code Session Management 心法
Claude Code 的 context window 從 200k 長到 1M，但更大不代表更好用。這篇整理五種 session 管理操作（Continue / rewind / clear / compact / Subagents）、四大策略、以及最容易踩的兩個坑。
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Claude Code this week: 1M context as a management problem, quota anxiety goes collective, SpaceX takes Cursor
Observations from 4/23–4/29: the right mental model for 1M context, Claude quota anxiety as a subscription design phenomenon, SpaceX beating Microsoft to Cursor for $60B, Claude 4.7 identifying a journalist from 125 words, and what happens when you let Claude Code DJ.
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Claude Code 這週整理：1M Context 怎麼用、額度焦慮集體發作、Cursor 被 SpaceX 搶走
4/23–4/29 這週的觀察與整理：1M context window 的正確心態、Claude 額度焦慮進化成集體現象、SpaceX 搶在微軟前面拿下 Cursor、Claude 4.7 根據 125 字認出記者、live coding 做音樂的副作用。
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Claude Code This Week: Offloading CLAUDE.md, Quota-Saving Tricks, Ghostty Click Fix
A handful of Claude Code settings and money-saving tricks I picked up this week — how Rules/Memory/Hooks offload CLAUDE.md, fixing cmd+click in Ghostty No Flicker mode, dispatching long-read work to Haiku for quota relief, and the cache difference between pasting images and editing prior messages after 4.7.
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Claude Code 這週整理：分擔 CLAUDE.md 的進階設定、省 quota 技巧、Ghostty 點擊設定
本週 Claude Code 累積的幾個實用設定與省錢技巧——Rules/Memory/Hooks 如何分擔 CLAUDE.md、Ghostty No Flicker 模式下連結點擊的修法、長文本用 Haiku 分派省 quota、4.7 後貼圖片跟改訊息對快取的差別。
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Claude Code Subscription Guide: The Real Gap Between Pro and Max
How much does Pro actually give you? Is Max worth it? Why does Cowork burn through tokens so fast? What does "2x usage" actually mean? These questions come up constantly — here's everything I've figured out over the past few months.
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Why Claude Code Only Reaches Its Full Potential in the Terminal
The terminal isn't just another way to open Claude. It's the environment where Claude actually gets to operate without constraints. Multi-window workflows, speed, resources, Ghostty — a full confession from a CLI believer.
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Claude Code 訂閱怎麼選：從 Pro 到 Max 的真實落差
Pro 的額度到底有多少？Max 值不值？Cowork 為什麼很燒 token？週額度的「雙倍」到底是哪個雙倍？這些問題我都被問過不只一次，用這篇把幾個月來的觀察整理清楚。
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為什麼 Claude Code 在終端機裡才是完全體
終端機不只是另一種打開 Claude 的方式。它是讓 Claude 真正解放的環境。多視窗、速度、資源、Ghostty——這是一個 CLI 信徒的完整自白。
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Claude Desktop App Got a Redesign — Here's Why I'm Still Using the Terminal
Claude released a redesigned desktop application — better looking, friendlier for newcomers. But if you ask me which one to use, the answer is still CLI. Not nostalgia, just feature gap and resource efficiency.
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hermes-CCC: Bringing All 46 Hermes Agent Capabilities into Claude Code
Someone ported the entire NousResearch Hermes Agent into 46 native Claude Code Skills. No OAuth, no external processes, just restart CC and you're ready. The core philosophy is "procedures-as-prompt" — structured markdown instruction scripts drive AI behavior without writing a single line of code.
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Obsidian vs NotebookLM: Which One Works for Claude Agent Automation?
These two tools get compared a lot, but they solve fundamentally different problems. From a Claude Agent automation perspective, the difference is even clearer — one is a local knowledge base your Agent reads and writes directly, the other's API stops at "managing the Notebook itself."
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Claude Desktop App 改版了——以及我為什麼還是用終端機
Claude 推出了改版的桌面應用程式，設計更漂亮、對新手更友善。但如果你問我要用哪個，答案還是 CLI。不是情懷，是功能差距和資源效率的問題。
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hermes-CCC：把 Hermes Agent 的 46 個能力全部裝進 Claude Code
有人把 NousResearch 的 Hermes Agent 整套行為拆解成 46 個 Claude Code 原生 Skill。沒有 OAuth、沒有外部進程、重啟 CC 就能用。核心設計哲學是「procedures-as-prompt」：用結構化 markdown 指令稿驅動 AI 行為，不用寫一行程式碼。
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Obsidian vs NotebookLM：用 Claude Agent 自動化知識管理，選哪個？
這兩個工具常被拿來比較，但解決的問題其實不同。從 Claude Agent 自動化的角度來看，差異更明顯：一個是 Agent 直接讀寫的本機知識庫，另一個的 API 在「管理 Notebook」這件事上就停了。
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This Week in the Claude Code Ecosystem: Four Resources I Bookmarked
Enterprise office tools, Taiwan local services, a hobby vertical, beginner onboarding—four different corners of the Claude Code ecosystem all shipped something this week. Each represents a use case that's still underexplored.
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本週 Claude Code 生態觀察：四個我收藏的新資源
企業辦公工具、台灣本地服務、興趣領域、初學者入門——這四個角落本週都冒出了新的 Claude Code 資源。每一個都代表一類還沒被充分開發的使用場景。
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cc-audit: A Skill That Forces You to Save Claude Code Quota
I turned my viral list of quota-saving tips into a skill. Hand the GitHub link to Claude Code to install, and it'll audit your settings, recent sessions, rules bloat, and context usage, then hand back an actionable fix list.
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cc-audit：一個強迫你省 Claude Code 額度的 Skill
把我之前整理的一千多讚的省額度技巧全部做成 skill。丟給 Claude Code 安裝後，它會逐條檢查你的設定、近期 session、rules 膨脹、context 用量，給出可執行的修正清單。
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Make a Claude Code Tutorial Video in 30 Minutes with Remotion Skill
I'd had the Remotion skill installed for a while, mostly just playing with it. Once I started making a free Claude Code tutorial series, I realized how good it actually is—from script discussion to export, 30 minutes gets you a 15-minute video with no retakes.
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用 Remotion Skill 半小時拍一支 Claude Code 教學影片
Remotion skill 我下載好一陣子了，一開始只是玩玩。最近開始錄 Claude Code 免費教學系列才發現真的太好用——從口白討論到剪輯渲染，半小時出一支 15 分鐘影片，不 NG 也不費力。
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Is Claude Getting Dumber? Someone Finally Brought Data
People have been complaining Claude is getting dumber for weeks. Anthropic's response has been "it's a usage problem." Then someone pulled the JSONL and showed it's measurable, not vibes. The Issue got closed anyway.
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Claude 變笨了？這次有人拿出數據證據
大家抱怨 Claude 變笨已經好幾個禮拜了，Anthropic 的回應一貫是「使用習慣問題」。終於有人從 JSONL 扒出數據，證明不是體感而是實測——但 Issue 還是被秒關。
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PII Guard TW: A De-identification Tool Built for Taiwan
There's no off-the-shelf de-identification tool for Taiwan's PII formats. So I built one that keeps sensitive data on your machine while you send the rest to AI.
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PII Guard TW：為台灣打造的個資去識別化工具
台灣的個資格式沒有現成的去識別化工具。所以我自己做了一個，讓機敏資料不離開你的電腦就能安全送 AI 處理。
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Anthropic's Trust Crisis and My Backup Plan
They quietly slashed quotas, went silent for a week, and only responded when they got caught. When your work is deeply tied to a service that can't even hit two nines of uptime, a backup plan isn't optional—it's essential.
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Anthropic 信任危機與我的備援方案
偷改額度、裝死一週、被發現才滅火。當你的工作已經深度綁定一個不到兩個 9 uptime 的服務，備援方案不是選項，是必要。