Posts
All the articles I've posted.
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AI 課一個月一萬八：教學市場的價格跟價值早就脫鉤了
在超商用餐區聽到的 AI 課吸金實況，對照我自己手上兩件真的能驗證的東西：15 年教材蒸餾成的 SKILL，跟每月破千美金的模擬考訂閱。價格反映的是行銷強度，不是交付密度。
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我的 Context Window 比當今大模型還脆弱：我開源了一個文檔審查 SKILL
跟 Agent 合作會注意力耗弱，於是我摸索出一套審查流程：請他出完整提案書，我錄音審查，他改，我去吃飯運動，等 v2。
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Why I Built My Own Newsletter
Once I started using AI, the feeds I follow changed completely. Threads is full of third-, fourth-, fifth-hand reposts with extra seasoning added, so I pulled together 300-plus sources and had AI build my own weekly digest.
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為什麼我自己做了一份電子報
開始用 AI 之後，我關注的社群媒體整個換掉。脆上很多是三四五六手搬運還要加料，所以我自己整理 300 多個源頭，讓 AI 做出我個人的電子週報。
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The CLI Is the Firstborn
New features and fresh bug fixes land in the CLI first. Remote control waits forever. Same company, wildly different update cadence.
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The Machines That Need the CLI Most Belong to People Least Likely to Learn It
For a machine short on resources the CLI uses a fraction of what a GUI does, but the people with the least headroom are also the least likely to ever learn it. Plus a note on how low the bar for local models actually is.
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The Skills and Hooks I Use Every Day, Now Open Source
I open-sourced the Claude Code skills and hooks I actually use every day. No technical skill required, pure logic, built for knowledge workers with no coding background.
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A July Full of Resets: A Light AI User Reviews the Subsidy War
Every time a reset landed in July I used it to the last drop, and the ledger says 57.5x. Plus notes on the subsidy war, Deepseek's price hike, and my bet on the next reset.
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Letting an Agent Tune a Local Video Model Overnight: My Three Gates
Three things I learned from letting an agent run local video-model parameter research overnight: hard constraints in CLAUDE.md, a gate script watching SSD writes, and a 30-minute check-in loop.
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Installing Gemini CLI With Beginners Cures Most Claude Code Ailments
Five steps I walk Claude Code / Codex beginners through when installing the Gemini Antigravity CLI: multimodal use cases, getting comfortable with a CLI, a quick win from voice transcription, and finishing on data governance and local mode.
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CLI 是親生的，其他都是後媽養的
新功能和剛修好的 bug 都優先落在 CLI，remote control 要等猴年馬月。同一家公司的產品，更新頻率差很多。
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最需要 CLI 的電腦，主人最不可能學會 CLI
對資源有限的電腦來說 CLI 佔用是 GUI 的零頭，但電腦資源最不夠的族群也剛好最不可能學會 CLI；順帶聊本機模型的硬體門檻其實沒那麼高。
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我每天在用的 Skill 跟 Hook，開源了
把我每天都在用、不需要技術力、純邏輯導向的幾個 Claude Code Skill 跟 Hook 開源出來，最適合跟我一樣沒有編程背景的知識工作者。
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充滿 reset 的七月：一個 AI 輕量用戶的補貼大戰復盤
七月一有 reset 就用好用滿，帳面發揮 57.5x 的價值；順便記下補貼大戰、Deepseek 漲價，和我對下一次重置的預測。
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讓 Agent 整夜自己調本地影片模型：我設的三道閘門
讓 agent 夜間自己跑本地影片模型調參的三個經驗：硬約束寫進 CLAUDE.md、閘門腳本監控 SSD 寫入、30 分鐘回來盯一次避免快取失效。
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帶初學者裝 Gemini CLI，治 Claude Code 百病
帶 Claude Code / Codex 初學者裝 Gemini Antigravity CLI 的五個步驟：從多模態 use case、CLI 介面的心理建設、語音轉錄的 quick win，一路帶到資料治理與本機模式。
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The Alignment Gap Is Closing. Next Comes Taste and Verification
The gap between AI and human intent is closing fast, so what separates good output moves toward taste and verification — and verification is where human responsibility stays.
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Other People Fly to Korea for Cosmetic Surgery. I Had Codex Do Mine.
Someone on Twitter chained Codex, Hyperframes, IndexTTS2 and HeyGen into a one-person media pipeline. I pulled the repo, tried it, played with a local TTS model, then rebuilt a video days later on Claude Code.
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Six New Context Engineering Rules for Claude 5, and the 1,473 Lines I Cut
After reading Anthropic's context engineering guidance for Claude 5, I turned the key points into nine cards, then cut 1,473 lines from a harness I had built up over four model generations.
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Fewer Prompts Is Not Less Control
Claude 5 and GPT-5.6 official guidance is converging on the same thing — retiring old-style prompt stacking. But trimming is not letting go; control just moves. And the payoff of maintaining that layering is switching tools without losing a step.
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My Local Model Lineup on a Mac mini, Plus Three Bad Habits I'm Owning Up To
Ten days of offline models on a 48GB Mac mini M4 Pro — the picks, the task split, a terrifying swap write rate, and three bad habits I admit to.
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Porting Old Prompts to Opus 5: A Nine-Card Migration Guide
Nine cards I made after reading Anthropic's official Opus 5 prompting guide: response length, agent narration, task boundaries, subagent delegation, self-correction, and what happens when you turn thinking off.
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Supposedly the Smartest Model, and Opus 5 Spent My Whole Day Spinning in Place
Wrong languages, sudden Simplified Chinese, then whole turns with no visible output — and a session log that matched an issue open since June 15.
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Two Habits for Voice-Driving Coding Agents, and I Am Still Finding the Balance
Short instructions go through push-to-talk; walking through a whole course outline or system architecture goes through a full QuickTime recording that I hand to the AI to transcribe and execute. Plus the setup I use to burn the AI quota that came free with Google Drive.
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對齊的 gap 正在縮小，接下來拚的是品味與驗證
AI 對齊人類意圖的 gap 正在快速縮小，區分產出品質的要素會往品味與驗證轉移；而驗證背後是人類永遠不會被取代的責任。
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別人去韓國做醫美，我叫 Codex 數位醫美
從推特上看到有人把 Codex、Hyperframes、IndexTTS2、HeyGen 串成一條自媒體流水線，拉下來實測、順手玩 b 站的本地 TTS，幾天後換 Claude Code 重做一支。
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Claude 5 時代的情境工程六條新規則，與我砍掉的 1473 行 harness
讀完 Anthropic 對 Claude 5 的情境工程指南後，我把重點做成九張圖卡，然後照著把累積四個世代的 harness 削掉 1473 行。
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更少的 prompt，不是更少的控制
Claude 5 與 GPT-5.6 的官方指南正在合流，都在淘汰舊式 prompt 堆疊。但精簡不等於放任，控制只是換了位置——而維護好這套分層的紅利，是換哪個工具都能立刻接手。
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Mac mini 上的本地模型陣容，順便招認我的三大劣根性
48GB 的 Mac mini M4 Pro 試了十來天離線模型，選型結論、任務分工、swap 嚇死人的寫入量，還有我承認的三個劣根性。
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舊 prompt 搬到 Opus 5：九張卡的遷移指南
讀完 Anthropic 官方的 Opus 5 提示指南後整理的九張卡：回答長度、代理敘述、任務邊界、子代理委派、自我修正，還有關掉 thinking 的副作用。
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號稱最聰明的 Opus 5，一整天在我對話裡空轉
從回錯語言、突然寫簡體，到整輪沒有可見輸出，查 session log 之後對上一個 6/15 就開著沒修的 issue。
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語音下指令的兩種習慣，我還在找平衡
用 Claude Code 或 Codex 時，短指令我用隨按即錄，要盤點整套思路時我改開 QuickTime 完整錄音，再丟給 AI 轉錄執行。附上我拿 Google 雲端硬碟送的額度做轉錄的設定。
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I'm Stuck at Stage 2.5 of AI Adoption
After watching Boris Cherny break down the stages of AI adoption, it hit home: I'm stuck at stage 2.5, where limited attention plus low trust becomes a vicious cycle. This week I used late-night schedules, a morning dashboard, and herdr auto-spawning sessions to cut a 4-5 hour workflow down to 1-2 hours.
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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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Some of My Subagents Were Already Grandpas
A CCX quota incident with no guardrails set: subagents bred recursively, one session burned 90% in half an hour, and here is the full forensics and fix.
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Codex Built Its Own Evidence Package and Went to Argue With Google Support
A leaked Gemini backend key at PDT Learning got abused, no spending cap, and burned 1000 USD. I pointed Codex's browser automation at Google's live support to fight the charge, and it went so hard it built a 15-page evidence package and sent it over.
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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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Instead of Begging the Model Not to Lie, I Wrote a Hook That Stops It
The sequel to the Opus 4.8 confabulation post: I moved "don't make up numbers" from a plea in CLAUDE.md to a pending-guard hook that blocks git commit at PreToolUse.
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Second Harness Diet: Global Skills From 58 Down to 40
A follow-up to the harness diet series: six months later, a bigger cleanup that cut my global skills from 58 down to 40, start to finish.
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我卡在 AI 導入的 2.5 階段
看了 Boris Cherny 分享的 AI 導入階段框架後有感而發：我卡在 2.5 階段，注意力有限加信任不足變成惡性循環，這週靠深夜排程、晨間儀表板、herdr 自動開 session 把 4-5 小時的協作壓到 1-2 小時。
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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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有些 subagent 都當阿公了
一次 CCX 沒設好護欄的額度事故：subagent 遞迴繁殖，一個 session 半小時燒掉 90%，事後鑑識與修法全記錄。
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Codex 自己做了一份證據包，跑去跟 Google 真人客服吵架
PDT Learning 一支 Gemini backend key 外洩被盜刷、沒設 spending cap 怒噴 1000 USD，我用 Codex 的瀏覽器操作去跟 Google 真人客服爭費用，它認真到自己生出一份 15 頁證據包發給對方。
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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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與其拜託模型不要騙我，不如寫一個擋得住的 hook
接續 Opus 4.8 捏造工具輸出那篇：我把「別亂編數字」從 CLAUDE.md 的拜託，升級成一個掛在 PreToolUse 擋 git commit 的 pending-guard hook。
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第二次 harness 減肥：全域 skills 58 砍到 40
接續 harness 減肥系列，半年後做了第二輪更大規模的整理，把全域 skills 從 58 個砍到 40 個的完整過程。
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A Few Days Into Switching From Claude Code to Codex: The Quota Honeymoon
A running log of switching from Claude Code to Codex this week: quota I could not burn through fast enough, a $20 Sol Ultra run that beat a $100 Fable plan on a professor friend's paper, and a tool-chain swap to Hyperframe.
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從 Claude Code 換到 Codex 的這幾天：額度蜜月期
這週從 Claude Code 換到 Codex 的體感記錄：額度多到花不完、Sol Ultra 20 鎂幫教授跑論文，比 Fable 100 鎂方案還划算，工具鏈也跟著換成 Hyperframe。
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Picking a Brand Look as a Non-Designer: AI Made Prototypes Cheap, So Taste Became the Hard Part
I am not a designer, but I spent this week iterating on a visual system for AgentCrew Academy with Fable, GPT-image-2, and GPT-5.6-sol. Here are the four rejected directions and the final spec applied to the website, slides, and documents.
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外行人選品牌視覺：AI 把提案做便宜了，難的變成你的品味
我不是設計師，這週用 Fable、GPT-image-2、GPT-5.6-sol 迭代出 AgentCrew Academy 的視覺系統，記下被否決的四個方向與最後套用到網站、投影片、文件的規格。
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Four Things I Have Learned from Teaching AI
Recent corporate workshops reinforced four lessons for me: teach in person when possible, cut the slide count, show smart people the result first, and let students do the work.
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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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最近教 AI 課學到的四件事
最近幾次企業培訓讓我重新確認四件事：實體課更好掌握節奏、投影片要做減法、聰明人先看結果，以及學員真正需要的是放手實作。
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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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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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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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ADHD, Flow, and Why I Teach AI
Confessions of someone with ADHD: if I make it past two weeks and still have flow, odds are I can do this thing for a decade-plus.
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The Client Says They Want Training, But Deep Down They Want a System
A post-mortem on letting go in a BD deal: the client drifted toward "give me an artifact" three times, and I changed one phrase from "after the training" to "if the priority is to build the hub" — and handed the ball back.
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From Takedown to Return, I Caught a Case of AnthroPTSD
An observation diary of Anthropic models getting pulled by the government and apparently returning: from arrogance, to political wrangling, to OpenAI winning by default, to the conditioned reflex I've been trained into.
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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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ADHD、心流，與我為什麼教 AI
一個 ADHD 患者的自白：撐過兩週還保有心流，這件事我大概率能做十幾年。
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客戶嘴上要培訓，骨子裡要系統
一次 BD 鬆手的覆盤：客戶三次飄向「給我 artifact」，我把一句話從「after the training」改成「if the priority is to build the hub」，球就交回去了。
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從下架到回歸，我得了 AnthroPTSD
Anthropic 模型被政府下架到疑似回歸的觀察日記：從傲慢、政治角力、OpenAI 躺贏，到我被訓練出的條件反射。
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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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My First All-English Two-Hour Corporate Training: I Burned the Script Two Hours Before
Just wrapped the first session of an all-English corporate training for 30 people at an international hedge fund — my first time teaching two hours straight in English. I had a teleprompter and a full English script ready, then two hours before class I shut the teleprompter off and burned the script, and winged the whole thing.
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第一次全英文兩小時企業內訓：上課前兩小時燒掉提詞稿
剛完成某國際 hedge fund 30 人企業內訓第一堂，這輩子第一次全程英文講兩小時。一開始準備了提詞機加英文全稿，上課前兩小時索性關掉提詞機、燒掉稿子，全程自由發揮。
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The Perpetual Token-Burning Machine: Anthropic Really Is Trying
A few scattered gripes about Anthropic's relentless push to get users burning tokens: 103 auto-triggered agents, five-layer Russian-doll subagents, and Formosa-Plastics-tier flexing.
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燒 token 永動機：Anthropic 真的很努力
幾則關於 Anthropic 在鼓勵用戶燒 token 這條路上的零碎吐槽：自動觸發 103 個 agent、五層俄羅斯娃娃 subagent、台塑等級的炫富。
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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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Claude Fable 5 / Mythos 5 System Card: What's Actually Inside, and Why It Reads Like Sci-Fi
Flipping through the Claude Fable 5 and Mythos 5 system cards: stealing keys, office politics, AI infighting, gibberish, and a two-faced model. The more I read, the more it feels like a straight-faced sci-fi novel.
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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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翻 Claude Fable 5／Mythos 5 系統卡，越看越像在讀科幻小說
翻閱 Claude Fable 5 跟 Mythos 5 的系統卡：偷鑰匙、辦公室政治、AI 內鬥、火星文、心口不一的雙面人，越看越像一本正經寫的科幻小說。
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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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Claude and Sensitive Data: Retention Windows, Enterprise Terms, and What to Check First
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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Worried About Agents Going Rogue? Start Isolated, Hand Off Gradually
Someone asked what to do if you worry about AI agents going rogue. My answer: don't pick a highly autonomous lobster up front. Start in an isolated setting where you supervise and approve every step, then let go slowly.
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A Few Months of AI Teaching Content: What Gets Traffic and What Doesn't
Traffic observations after a few months of AI teaching content — the lecture overflowed, the job-search demo got the most questions, the concept I thought mattered most pulled the least, and the Obsidian video went against the wind.
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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.