Archives
All the articles I've archived.
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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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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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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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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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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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Do Not Grade AI by Its Own Summary
I hit the same failure in several forms this week: an agent denied changing files, a commit message overstated the diff, and a transcript reassigned a speaker ID halfway through.
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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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不要用 AI 的摘要驗收 AI
這週反覆踩到同一類錯誤：agent 說沒改檔卻留下檔案、commit message 與 diff 不符、逐字稿說話人中途漂移。驗收必須回到原始狀態。
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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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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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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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Reading the Claude Fable 5 / Mythos 5 System Card Feels Like a Sci-Fi Novel
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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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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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.
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Claude Code To-Do Tiering: Auto / Review / Collaborate / Manual
A small discovery from using Claude Code: sort to-dos by repo, then into four tiers — auto, review, collaborate, manual. Stuff that used to drag on all day now finishes in an hour.
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Digital Nomadism Is Something You Stumble Into, Not a Goal to Chase
As someone who has been traveling the world and working remotely since 2016, I can say this with full confidence: digital nomadism is something you stumble into, not a lifestyle goal to chase.
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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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A Week of Firestore / Cloud Functions Footguns — Same GMAT Question Bank
Eight bugs I hit in one week on the same Firebase project (a GMAT question bank): Firestore rules, composite indexes, error_logs spam, TPA scoring, App Check tokens, and a browser-translation DOM crash — symptom, root cause, fix for each.
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Three Real Lessons From Going Freelance, Plus the Pros Who Hide in Plain Sight
Three honest lessons from going freelance: don't undercut your own price, cut clients who keep testing scope, and higher-margin clients are easier to deal with. Plus an observation: the real pros hide in plain sight, invisible online.
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Eight Days of Silent Failure: launchd Fired on Schedule, Nothing Happened
A local pipeline that auto-publishes a video every day at 09:00 failed for eight straight days. launchd fired on schedule, zero alerts. Notes from tracing a path desync down to exit 127.
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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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A Week of Making Tutorial Videos With Claude Code: Remotion Animation and ffmpeg Pitfalls
Production pitfalls from a week of making two tutorial videos: subtitle restraint, font size, animation anchor auditing, Remotion render crashes, normalizing quiet narration, and opencc over-localization.
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A Proposal Is Not a Deployment: Why One Quick Win Sat Dead for Five Weeks
I had an SEO weekly report running on autopilot for five weeks, and one page's Quick Win just kept sitting there doing nothing. The root cause wasn't a wrong optimization — it was that the nice optimization proposal was never actually deployed.
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I Built a "Tinghao SKILL" — Distilling a Finance YouTuber's Perspective Into AI
I spent my leftover Claude quota building a Tinghao SKILL: 17 finance episodes distilled, 3-4 rounds of blind testing, and a curious difference in how AI and humans deploy dirty jokes.
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擔心 agent 失控？先在隔離環境逐步放手
有人問擔心 AI agent 失控怎麼辦。我的回覆是：別一開始就選高度自主的龍蝦，先在你親自監督放行每一步的隔離環境裡操作，再慢慢放手。
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做 AI 教學內容幾個月：什麼有流量、什麼沒有
做 AI 教學內容幾個月下來的流量觀察：講座爆滿、求職示範片最多人問、重要的進階觀念反而流量差、逆風發 Obsidian 影片。
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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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Claude Code 待辦分級制：自動／審核／協作／手動四級分流
一個用 Claude Code 的小發現：把待辦先分 repo 再分成自動／審核／協作／手動四級，原本拖一整天的事 1 小時內就做完了。
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數位遊牧是可遇不可求，不要把它當成追求目標
從 2016 年就開始世界各地旅遊加遠端工作的我可以負責任地說：數位遊牧是可遇、但不可求，不要把它當成 life style 的追求目標。
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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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一週 Firestore / Cloud Functions 踩坑合輯——同一個 GMAT 題庫系統
一週內在同一個 Firebase 專案（GMAT 題庫系統）連環踩到的 Firestore 權限、composite index、error_logs 洗版、TPA 計分、App Check token、瀏覽器翻譯 DOM crash 八個坑——每坑現象、根因、解法。
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出來接案的真實感受三條，還有高手大隱隱於市
出來接案的三條真實感受：不要自降身價、會試探 scope 的客戶斷就是斷、毛利越高的客戶越好溝通。外加一個觀察：真正的高手大隱隱於市，網路上看不到蹤跡。
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靜默連敗 8 天：launchd 照常觸發，卻什麼都沒發生
一條每天 09:00 自動發片的本機 pipeline 連敗 8 天，launchd 照常觸發、零告警。記一次從搬檔到 exit 127 的脫鉤排查。
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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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用 Claude Code 做教學影片一週踩到的坑——Remotion 動畫與 ffmpeg 後製
這一週做兩部教學影片踩到的製作坑：字幕克制、字級、動畫錨點稽核、Remotion render crash 拆段、安靜旁白正規化、opencc 過度在地化。
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提案不等於部署：一個 Quick Win 掛了五週的根因
我有一個 SEO 週報自動跑了五週，某一頁的 Quick Win 一直掛著沒效。根因不是優化方向錯，而是那份漂亮的優化提案從頭到尾從來沒被真正部署上線。
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我做了一個「庭皓 SKILL」——把財經 YouTuber 的觀點蒸餾成 AI
用沒燒完的閒 token 做了一個庭皓 SKILL：蒸餾 17 部財經速解讀、3-4 輪盲測驗證，還發現 AI 跟人類講黃段子的邏輯不太一樣。
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The Blind Spot in AI Self-Verification — Why You Need an Uninformed Agent to Audit
AI is great at "looking done." To catch its blind spots, you can't rely on it checking its own work — you bring in an auditor that knows nothing, inherits no context, and gets only the rules and the output.
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AI 自我驗證的盲點——為什麼要請一個不知情的 agent 來稽核
AI 很會「看起來完成了」。要抓出它的盲點，不能靠它自己回頭檢查——得引入一個不知情、不繼承上下文、只拿到原則與產出的稽核者。
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Better Context Beats a Stronger Model — repowise's Five-Layer Architecture
I came across repowise, a tool that inserts a layer of context between your codebase and the model. It is a good excuse to talk about a bigger idea: when a model breaks things, the first instinct is to reach for a stronger model, but the real cause is usually too little context.
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給 LLM 更好的 context，勝過換更強的模型——repowise 的五層架構
看到 repowise 這個在 codebase 與模型之間插一層 context 的工具，想聊一個更大的觀念：模型改壞東西時，第一反應常常是換更強的模型，但真正的根因往往是 context 不夠。
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Two Reminders for Vibe Coders: Learn System Architecture First, the Value Is in the Thinking
Two great posts I found on Reddit: one says vibe coders should learn system architecture before rushing to code, the other says what you build with Claude is useless to others — the real value is the thinking.
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給 Vibe Coder 的兩個提醒——先學系統架構，價值在思維不在工具
從 Reddit 撈到的兩篇好文：一篇講 Vibe Coder 該先學系統架構而不是急著寫程式，一篇講你用 Claude 做的東西對別人沒用、真正有價值的是思維。
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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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A Student's Seven-Agent Setup That Wouldn't Run — A Cautionary Tale About Harness First
A student built seven agents on an M5 Max and kept hitting timeouts. The problem wasn't a weak model — it was skipping the basics: harness, context management, task routing.
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學員自建七個 agent 跑不動——一個 harness 為重的反面教材
一個學員在 M5 Max 上自建七個 agent 卻一直 timeout，問題不在模型不夠強，而在沒先把 harness、上下文管理、任務分派這些基本功打好。
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Leveling Up the iPad Workflow — Surviving Internet and Power Outages, and Why I Ditched the Magic Keyboard
A follow-up to the full iPad-runs-Claude-Code guide. This one is not about setup, it is about robustness: home internet in Bangkok drops, the rainy season kills the power, so how does the host machine survive? Plus why I gave up the Magic Keyboard for my mouth and some gestures.
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iPad 工作流進階——斷網斷電的備案，與我為什麼放棄妙控鍵盤
iPad 跑 Claude Code 全攻略的續篇：談的不是安裝，是穩健性——曼谷家用網路會斷、雨季會停電，主機端怎麼撐住；以及我為什麼放棄妙控鍵盤、改用一張嘴加手勢。
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Love-Hate With Anthropic — Sneering at the Elitism While Devouring Their Engineering Blog
I have a love-hate thing with Anthropic: I hate the smug elitism and the black-box token-burning, but their engineering blog is some of the best out there, especially the security and permissions stuff.
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又愛又恨 Anthropic——一邊嫌精英心態，一邊狂讀他們的技術部落格
我對 Anthropic 又愛又恨：恨那股噁心的精英心態跟燒 token 的黑箱操作，愛他們數一數二高品質的技術部落格，尤其資安權限那塊。
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Racing for the Fastest Summary — Opus 4.8's 244-Page System Card, and How I Read It With 20 Agents in Half an Hour
The night Opus 4.8 launched, I split the 244-page system card into 20 chunks, handed them to 20 gemini agents to summarize in parallel, and pieced together the fastest rundown online. Plus a digest of Reddit's hands-on reactions within two hours of launch.
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拼全網最速——Opus 4.8 系統卡 244 頁重點，外加我怎麼用 20 個 agent 半小時讀完
Opus 4.8 發布當晚，我把 244 頁系統卡切成 20 份、丟給 20 個 gemini agent 並行摘要，拼出全網最速重點。附上發布兩小時內的 Reddit 實測整理。
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The More Rules You Add, the Less Claude Listens — I Sent a Team of Agents to Trim My Setup and Cut 36% of Always-On Context
Late at night I got Opus 4.8, and my weekly quota happened to reset. The first thing I did was put my harness on a diet. A COO student who had burned through 88% of his 1M context made me face one thing squarely: the more rules you add, the less the model listens.
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規則越加，Claude 越不聽話——派一隊 AI 重整設定，常態上下文省 36%
半夜拿到 Opus 4.8、額度剛好重置，我做的第一件事是減肥我的 harness。一個 COO 學員把 1M 上下文用到 88% 的案例，讓我認真面對一件事：規則加越多，模型反而越不聽話。
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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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Turning Street Smarts into an AI Skill — When the Numbers Are Clear, You Stop Flinching
After turning Norm Brodsky's Street Smarts into a Claude Code Skill, every partnership opportunity gets a margin analysis first. Many appealing deals turn out to be money losers. When you know the numbers, you stop flinching.
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把《街頭智慧》做成 AI Skill——算出來的數字就在那邊，波瀾不驚
把 Norm Brodsky《街頭智慧》做成 Claude Code Skill 後，每個合作案都先算毛利。看似很好的機會，算下去常常是賠錢。心中有底，對方再怎麼跑火車都不慌。
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Every AI Leader Starts Cutting Corners — The GPT, Claude, Gemini Cycle
GPT image generation degrading, Claude quietly shrinking rate limits, Gemini Flash hiking prices. Every model provider starts cutting corners once they reach the top. Annual subscriptions are the worst bet.
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坐上第一就開始拿翹——GPT、Claude、Gemini 的降智循環
GPT 生圖降智、Claude 額度縮水、Gemini Flash 漲價。三家輪流坐莊，坐上去就開始偷料。按年訂閱是最傻的事，沒消息才是最好的消息。
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Running Claude Code on iPad — tmux + Tailscale + Moshi Setup Guide
A complete setup for running Claude Code on an iPad 11-inch: tmux for persistent sessions, Tailscale for NAT traversal, and Moshi as the SSH terminal. The goal is rebuilding 90% productivity, not just fixing bugs.
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iPad 跑 Claude Code 全攻略——tmux + Tailscale + Moshi
用 iPad 11 吋成功運行 Claude Code 的完整方案：tmux 保持 session、Tailscale 穿 NAT、Moshi 做 SSH 終端。目標是重建九成生產力，不只是修 bug。
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Cross-Model Review — Stop Letting AI Grade Its Own Homework
AI reviewing its own output has inherent blind spots. Using Codex for independent review or the Review Council skill to orchestrate a three-model expert team is the most pragmatic solution right now.
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跨模型互審——讓 AI 不再自己審自己
AI 自己審查自己的產出，盲點難以避免。用 Codex 做獨立審查、或用 Review Council skill 組三模型 expert team，是目前最務實的解法。
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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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Gemini 3.5 Flash Reddit Reviews — 3x Price, Vision Regression, Tool Calling Disaster
Reddit user reviews after Gemini 3.5 Flash launch: 3x price increase over 3 Flash, vision regression, tool calling running 32 calls before forced stop. Speed is genuinely fast, but overall reception skews negative.
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Gemini 3.5 Flash Reddit 實測彙整——貴三倍、Vision 退步、Tool Calling 災難
Gemini 3.5 Flash 上線後 Reddit 用戶實測回報彙整：價格比 3 Flash 貴三倍、Vision 退步、Tool Calling 跑到 32 次被中斷。正面是速度快且程式碼風格好，但整體評價偏負面。
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Have Claude scan an MCP before you install it—it found 7 vulnerabilities and still said it's safe to install
This week AgentCrew Academy shipped a video about why you should run /security-scan before installing any MCP / npm / pip package. Tested a third-party MCP, Claude flagged 7 findings, then said "install is fine." This is the written companion to the video.
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裝 MCP 之前先讓 Claude 幫你掃——找到 7 個漏洞，但說這個可以裝
講座當週我拍了一支影片，講「裝任何 MCP / npm / pip / clone 之前先跑 /security-scan」這件事。實測了一個三方 MCP，Claude 掃出 7 個漏洞，但綜合評估後說「可以裝」。這篇是影片的補充文字版。
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Scope Discipline: five rules—client small talk ≠ scope expansion authorization, must go into every future contract
A 5/12 admin class contracted for 1.5 hours ran 2.5 hours (+67%). Root cause: I misread the client's stated topic preference as authorization to expand scope. The lesson became five Scope Discipline rules that must appear in every future enterprise / 1-on-1 / tutoring contract.
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Scope Discipline 五條——客戶閒談 ≠ scope 擴張授權，未來合約必含
5/12 行政班合約 1.5 小時被自己做成 2.5 小時（+67%），追根究底是把客戶閒談的主題偏好誤解為 scope 擴張授權。教訓寫成五條 Scope Discipline，未來企業案 / 1-on-1 / 家教合約必含。
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YouTube Data API large-file upload tested: 216 MB succeeds, 257 MB hangs—threshold around 220-250 MB
Two 5/13 uploads via YouTube Data API: 216 MB legal MCP demo succeeded, 257 MB AI job-search clip hung indefinitely. Same googleapiclient resumable upload pipeline. The difference is file size and resolution. The practical threshold sits around 220-250 MB.
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YouTube API 大檔上傳卡死實測——216 MB 過 / 257 MB 不過，門檻約在 220-250 MB
5/13 兩支影片用 YouTube Data API 上傳實測：216 MB 的法律 MCP 示範片成功、257 MB 的 AI 求職示範片卡死。同樣的 googleapiclient resumable upload，差別在檔案大小跟解析度。門檻約在 220-250 MB 之間。
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MBA × AI Case Method—avoiding HBS licensing risk, finding open case materials, training seed instructors
2026-05 investigation into doing case-based AI teaching for business courses. HBS / HBR cases carry licensing risk. Maps the open alternatives (UBC Open Case Studies, OpenCaseStudies.org, World Bank), what's off-limits, and the direction of training MBA-background seed instructors.
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MBA × AI Case Method——避開 HBS 授權風險、找開源案例素材、訓練種子教師
想做商業 AI 課程的案例教學，但 HBS / HBR cases 有授權風險。這篇整理 2026-05 調查的開源案例來源（UBC Open Case Studies、OpenCaseStudies.org、World Bank）、不能用的清單，以及訓練 MBA 背景種子教師的方向。
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Three moves to firepower-demo Agentic AI at your company—desktop cleanup, conflicting meeting notes, multi-version emails
If you want to make your manager or coworkers feel Agentic AI in one second—and then open the door to an internal training engagement—my three go-to moves are cleaning up messy desktops, reconciling conflicting meeting notes and emails, and producing multi-version drafts for different recipients. These three hit office workers right in the pain.
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在公司火力展示 Agentic AI 的三招——桌面整理、會議紀錄、信件多版本
想在公司讓主管同事一秒有感、進而開內訓案的話，我自己最常用的三招是：整理桌面亂檔、整理相互衝突的會議紀錄跟信件、迅速生成不同版本的信件給主管同事客戶廠商。這三招對辦公室的人就夠有感了。
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Reflection after a 200-person online AI lecture—the energy of the classroom 10 years ago, back again
This morning I ran a 200-person free online AI lecture. So happy. 450+ signups, attendance around 45%, but landing on Mother's Day midday and still hitting that—Zoom data showed average seat-time over 75%, and FAQ ran so long I answered for an extra half hour.
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200 人線上 AI 講座結束後的感言——10 年前實體教室那種時光，又回來了
今天早上辦了一場 200 人的免費 AI 線上講座，好開心。報名人數 450+，出席率大概 45%，但是撞到母親節中午還能有這種成績，Zoom 數據拉下來發現留座時間平均超過 75%，FAQ 踴躍到多回答了半小時問題。
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Why Obsidian is something special to me, and why I only made this video now
I'd been wanting to make this video for a long time, but kept putting it off. Obsidian's flexibility is so high that it grows into a different shape in every person's hands. The payoff isn't immediate either—it's only after the vault has grown for a while that you realize you can't go back.
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Obsidian 為什麼是個特別的存在——我為什麼到現在才拍這部影片
這部影片我想做很久了，但是卻一直沒做，直到今天。Obsidian 的自由度太高，所以在每個人的手上會長成不同的樣子。他的成效又不是立刻就能看到的，而是越長越大你才會發現離不開它。
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Seven gotchas from running Resend and Gmail email workflows—HTML templates, scheduled_at, Cloudflare, open-rate alignment
Two weeks of heavy use across Resend batch sends and Gmail draft creation for course notifications, lecture thank-you emails, and BD outreach. Over 1,400 emails sent. Seven lessons worth writing down.
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Resend 跟 Gmail 寄信工作流踩坑七連——HTML 模板、scheduled_at、Cloudflare、開信率對齊
這兩週密集用 Resend 批次寄信跟 Gmail draft 兩條路徑做課程通知、講座感謝信、BD outreach。整理七個踩坑：HTML inline style、scheduled_at 不生效、Cloudflare 1010、Click tracking、bad-recipients、Gmail thread 漏看、客製 vs 通用開信率對齊。
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Covey's time management matrix, now with Claude Code—how each quadrant shifts
Covey's time management matrix from The 7 Habits of Highly Effective People splits time on two axes: important × urgent. Drop Claude Code into the picture and each quadrant's time allocation shifts. The long-term compounding from AI isn't in Q1, it's in Q2.
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Covey 七個習慣的時間矩陣放上 Claude Code 之後——每一格的時間分配怎麼變
Covey《高效能人士的七個習慣》的時間矩陣是兩軸切四象限，重要 × 緊急。把 Claude Code 放進去之後，每一格的時間分配會被重新洗牌。Q1/Q3 被 AI 吃掉，多出來的時間搬到 Q2 才是 AI 協作的長期複利。
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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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What I only learned after taking on enterprise AI training—prep time, the client liaison, instructor flexibility, and how to pick a consultant
Four things I learned after running a handful of enterprise AI training sessions. Prep time is 3-5x the session itself. The client liaison decides everything. The instructor has to handle wildly different skill levels. And if you're looking to hire a trainer, the signals are like picking a pop star.
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親自接 AI 企業培訓之後才知道的事——準備時間、甲方對接、講師應變、選顧問訊號
接了幾場企業 AI 培訓之後整理出來的四件事：準備時間是上課時間的 3-5 倍以上、甲方對接者決定一切、講師要能應付各種程度跟提問、想找講師的話訊號跟追星很像。
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How to tune Opus 4.7's effort, and why I still keep non-coding tasks on Sonnet 4.6 medium
Opus 4.7's default adaptive effort is a disaster—it turns into a lazy emperor. You have to crank it up to high or xhigh to avoid that, but token consumption goes nuts. After testing, Sonnet 4.6 medium is the sweet spot for non-coding work.
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Opus 4.7 的 effort 怎麼調，跟為什麼我非編程任務還是停在 Sonnet 4.6 medium
Opus 4.7 預設的 adaptive effort 是場災難，會變成偷懶摸魚皇帝。要開到 high 或 xhigh 才能避免，但 token 就開始狂燒。實測下來，非編程任務停在 Sonnet 4.6 medium 反而是最好的選擇。
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Claude Code Desktop vs CLI right now—why I think beginners should just start with the desktop app
Two or three weeks ago Anthropic overhauled the desktop app. Over 90% of the features now match the CLI. If you're a beginner who's scared of the terminal, starting with the desktop app is fine.
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Claude Code 桌面版跟終端機現在差在哪——我為什麼覺得初學者直接從桌面版開始就好
兩三週前 Anthropic 把桌面 App 大翻新，90% 以上功能跟終端機同步。初學者對終端機有恐懼，現在從桌面版開始完全沒問題。
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2026 Model Personality Watch: Gemini, Claude, Codex Compared
A year in, the three flagships have developed very visible "personalities" — Gemini 3 is the dramatic PhD, Claude 4.7 is the slick veteran, and GPT-5.5 turns out to be the most pragmatic colleague of the wave. Plus a fun trick for guessing the version from "sass density."
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2026 模型脾氣觀察：Gemini、Claude、Codex 的個性對比
用了一整年下來，三家的旗艦模型各自有很明顯的「脾氣」——Gemini 3 像戲精博士、Claude 4.7 像油條前輩、GPT-5.5 反而是這波最務實的同事。把累積的觀察整理成一篇對比，順便講一個從「貧嘴密度」反推版本號的玩法。
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Why You Keep Hitting Limit: Six Observations on Claude's Subscription Economics
From W18 to W19 I accumulated half a dozen observations about Claude quota — reset times deliberately scattered, the 5x→20x math trap, hitting limit in one hour during US East peak, and somehow free GPT never running out. String them together and a real subscription economics emerges.
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為什麼你會一直 hit limit：Claude 訂閱經濟學的六個觀察
從 W18 到 W19 累積了好幾條關於 Claude 額度的觀察——重置時間打散、5x→20x 的數學陷阱、美東尖峰一小時就滿、免費 GPT 反而打不滿。把這些連起來，會看到 Claude 訂閱的真實經濟結構。
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Three Channels for Tracking Anthropic
Since March 2026 I have been jotting down ways to follow Anthropic — official sources, employee accounts, third-party teardowns. Consolidating into one piece, with notes on the recent Mythos system-card controversy and the curious silence of Anthropic employees on social media.
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追蹤 Anthropic 動態的三條管道
從 2026 年 3 月開始我陸續記了一些追 Anthropic 的方法——官方來源、員工帳號、第三方拆解。整理成一篇，順便聊近期的 Mythos 系統卡爭議跟員工社群媒體沉寂的訊號。
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Jack Dorsey Cut 40% and Rebuilt: The Shape of Companies in the AI Era
Block / Square / Cash App's Jack Dorsey did an interview about why he laid off 40% of the company and rebuilt from scratch. Plus Sequoia's Roelof on the "three things a good CEO needs" — once AI can do 80%, the remaining 20% is where humans live.
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Jack Dorsey 把公司裁掉 40% 重建：AI 時代的組織形狀
Block / Square / Cash App 的 Jack Dorsey 接受訪問，聊他為什麼把公司裁員 40% 然後從頭重建。順便整理 Sequoia 投資人 Roelof 講的「好 CEO 三件事」——在 AI 可以做出 80% 之後，剩下那 20% 才是人類的價值。
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Judging AI Risk on Two Axes: Reversibility × Environment Isolation
A common question in corporate trainings — "can I let AI do this automatically?" I answer with two axes: reversible vs irreversible, isolated vs production. This 2x2 prevents more incidents than any prompt-engineering tutorial.
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判斷 AI 風險的兩個維度：可逆性 × 環境隔離
企業內訓裡常被問的一題——「我可以讓 AI 自動做這件事嗎？」我用兩個維度回答：可逆 vs 不可逆、隔離環境 vs 生產環境。這個 2x2 矩陣比任何 prompt 教學都更能避免事故。
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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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Moving from Claude Code to Codex: I Built a Skill to Handle It
Migrating an entire personal harness from Claude Code to Codex is not trivial — claude.md / agents.md, MCP, hooks, settings each need their own translation. I packaged the workflow as a Skill on GitHub. Plus a note on why I keep reaching for Codex these days.
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從 Claude Code 搬家到 Codex：我做了一個 Skill 自動處理
把整套個人 harness 從 Claude Code 遷移到 Codex 不容易——claude.md / agents.md、MCP、hooks、settings 各自要對齊。我把流程包成一個 Skill 放在 GitHub，順便聊聊為什麼最近越來越常用 Codex。
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You're mass-applying with AI. They're mass-screening with AI. Who wins?
Something slightly absurd is happening in the job market — candidates using AI to generate hundreds of tailored applications, HR using AI to filter them. In a bilateral arms race, who actually benefits?
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你用 AI 海量投履歷，他用 AI 海量篩履歷：最後誰贏了？
北美職場正在發生一件有點荒謬的事：求職者用 AI 大量產出履歷，HR 用 AI 大量過濾履歷。在這場雙邊軍備競賽裡，最後是誰在受益？
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Is your AI subscription worth it? A night market steak framework
A $7 night market steak versus a $70 restaurant steak — the expensive one isn't ten times better. AI subscriptions work the same way. A framework for deciding whether you're actually getting value.
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AI 訂閱費值不值？夜市牛排思考框架
兩百塊夜市牛排 vs 兩千塊餐廳牛排，差十倍的價格未必差十倍的體驗。AI 訂閱也一樣。一個判斷 AI 訂閱費有沒有在「賺」的框架。
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Lost 10 kg After Ten Years of Failure — Because of Claude's Quota
Lost 10 kg, complexion improved — a result I had failed to hit for ten years, finally achieved without willpower. Not from health drugs. From Claude burning my quota faster than I could finish my work. A half-joking but completely real chronicle of the silliest side effect of 2026.
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Teaching non-technical people AI: five things the tech world assumes everyone knows
One student was a seasoned HR consultant who managed all her files across several USB drives and had never heard of an API. Here are five knowledge gaps that show up constantly when teaching AI tools outside the tech world — and what actually works.
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睽違十年瘦了 10 公斤——竟然是因為 Claude 額度不夠
體重減掉 10 公斤、氣色變好——睽違十年都沒達成的成果，竟然不是靠猛健樂，而是靠 Claude 把我額度燒完。這篇半開玩笑的記下這個荒謬但真實的副作用。
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帶麻瓜學 AI：技術圈習以為常、但他們從來不知道的五件事
一位企業人資顧問、USB 隨身碟管理所有檔案、從來不知道 API 是什麼。這是在技術圈外推廣 AI 工具時，你會真實碰到的起點。五個知識落差，以及我現場用的方法。
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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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Knowledge base deep clean: using AI to find months-old problems
Rules trimmed from 13,020 to 7,590 tokens. 92 broken wikilinks. Five root causes behind a failing todo system. Four days of cleanup, one quarterly SOP.
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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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Two Worlds of Web-Based Claude Code Setup
Web Claude Code has two completely different runtimes — cloud VM and remote-control. Here is what I learned setting up both, the small bugs I hit, and why some user-level configs simply cannot be lifted to the cloud as-is.
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See the Outside, Think the Inside: Two Claude Skills That Pair
I saw a competitor selling well and my first reaction was anxiety. But before letting anxiety win, I wanted to actually understand what it was. Lately I have been pairing two Claude Skills for this — H/V analysis to see the outside, first-principles to see the inside.
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Three design mistakes I keep seeing in enterprise AI training
After running AI adoption training for several companies — manufacturing to services, 20 to 100+ people — three mistakes come up almost every time.
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Nine video production bugs I hit in April 2026
Running a fully automated video pipeline with Remotion, ffmpeg, yt-dlp, SiliconFlow ASR, and the YouTube API — here are nine specific bugs from April, in the order I hit them.
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2205% subscriber growth in two weeks: how one video opened the algorithm
Real analytics breakdown of how EP.18 went viral — not through SEO, but retention triggering subscriber activation, then spreading via sidebar. Plus what I actually did to make it happen.
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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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網頁版 Claude Code 環境設定的兩個世界
網頁版 Claude Code 有兩種環境——雲端 VM 跟 Remote-control。這篇整理我實測下來的設定訣竅、會踩到的小 bug，以及為什麼有些設定不能無腦丟到雲端。
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看清外面、想清裡面：兩個 Claude Skill 的分工
偶然看到一個競品賣得很好，第一反應是焦慮。但焦慮之前，我想先搞清楚它到底是什麼。最近用兩個 Claude Skill 把這件事做透——橫縱分析法看外面，第一性原理看裡面。
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幫企業導入 AI，教案設計最常犯的三個錯
從實際的企業培訓案例中，整理出三個教案設計的核心錯誤：統一任務不等於統一方法論、開放式問卷無效、以及缺少「自主應用」這一步。
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知識庫大掃除：用 AI 幫你找到埋了幾個月的爛帳
Rules 從 13,020 降到 7,590 tokens、92 個 wikilink 斷連、待辦系統五大根因——記錄一次花了四天的知識庫健檢，以及整理出來的季度 SOP。
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自動化影片製作管道：2026 年四月踩過的九個坑
用 Remotion、ffmpeg、yt-dlp、SiliconFlow ASR、YouTube API 自動化影片製作流程，四月份踩到的九個具體 bug 與解法。
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頻道訂閱兩週漲 2205%：一支影片怎麼把演算法打開的
用真實數據拆解 EP.18 爆款的完整機制：不是 SEO，是留存率觸發訂閱者激活，再透過 sidebar 擴散。以及我做了什麼讓這件事發生。
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A Legal Counsel Used Claude Code to Catch Patent Infringement — Days Down to Hours
A legal counsel at a mid-sized company took our Claude Code course, then compressed a multi-day patent infringement audit into a single day — and actually caught a real case that is now in legal proceedings. This story finally turns "Claude Code is not just for engineers" from a slogan into a fact.
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法務用 Claude Code 抓專利侵權，從幾天變成一天
一位幾十人公司的法務上完 Claude Code 課之後，把原本要好幾天的專利侵權查核壓到一天，而且真的抓到送上法律程序。這篇想記下這個案例，因為它讓「Claude Code 不是只給工程師用」這句話從口號變成事實。
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My Claude Code Automation Stack: /loop, Monitor Tool, the Skill System, Obsidian Reflection Reviews
From /loop clocking in for me at ERP, to Monitor Tool as a background event gatekeeper, to Google Map MCP saving browser clicks, to Obsidian + Mirror framework for weekly reflection. Here's my six-month Claude Code automation stack, plus a clarification of how commands and skills actually split.
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我家的 Claude Code 自動化工作流：/loop、Monitor Tool、skill 體系、Obsidian 反思週報
從 /loop 指令幫我打 ERP 卡、Monitor Tool 做背景事件守門員、Google Map MCP 省瀏覽器操作、到 Obsidian 搭 Mirror 框架做反思週報——整理這半年我家 Claude Code 的自動化架構，順便釐清 commands 跟 skills 到底怎麼分。
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Six Months with Claude Code: From First Affection to Hesitation, From Overtime to Detox, From Mandarin Circles to the Thai Community
From January to April, my state of mind with Claude Code went from "that PTT-generation affection for the CLI" to "20x hesitation" to "AI detox" to "practicing Thai at a Bangkok meetup." Here's the six-month arc, along with the nights agents worked overtime for me until 5 AM.
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Claude Code 用了半年：從好感到猶豫、從加班到 detox、從中文圈到泰國社群
從 1 月到 4 月陪著 Claude Code 一起長大半年，我的心態從「PTT 世代對 CLI 的莫名好感」變成「20x 的猶豫」變成「AI detox」變成「泰國社群練泰語」。整理一下這半年的軌跡，連同那些對自己講越來越 nerdy、agent 幫我加班到凌晨五點的日子。
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Two Months of Claude Code Harness Ops: Crashes, Zombies, Cache Misses, and Plan Mode Edges
From March to April, running Claude Code as a long-running harness surfaced a bunch of issues. Survival tactics during the outage, my hook for cleaning up zombie processes, the resume cache-miss fix in 2.1.90, the silent memory bloat in 2.1.100, and the Plan-Mode-question-density problem after 4.7.
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Claude Code Harness 兩個月運維史：當機、殭屍、快取、Plan Mode 的邊邊角角
從 3 月到 4 月，Claude Code 作為長時間運轉的 harness，踩過的幾個點：當機時的求生策略、我自己寫的 hook 清殭屍進程、2.1.90 修好的 resume cache miss、2.1.100 的記憶體暴增修復、還有 Plan Mode 問題太多的 4.7 癥結。
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AI-Era Business Routes: Auto-Generated Posts, the Skill Poisoning Theory, and Why I Started Rooting for OpenAI
A handful of AI industry observations I piled up on Threads this week — automating social posts uses AI in the wrong place, whether Skills are a mechanism for model providers to extract human knowledge, and why I went from hating on OpenAI to genuinely hoping they get better.
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AI 時代的經營路線之爭：自動化貼文、Skill 投毒論、跟我期待 OpenAI 的理由
這週跟朋友閒聊時累積的幾則 AI 產業觀察——用 AI 自動化產貼文是用錯場景、Skill 是不是模型商套人類知識的陰謀、為什麼我從唾棄 OpenAI 轉成期待他們越做越好。
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A Teacher's Responsibility: How a 15-Year Cram School Instructor Sees AI-Era Course Quality
When students have the wrong expectations, instructors are often also failing. After 15 years in cram schools and recent experience teaching Claude Code, a few thoughts on course quality basics, teacher responsibility, and the most practical one-word answer for a cram school going AI.
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教學者的責任心：15 年補教老師怎麼看 AI 時代的課程品質
當學員有錯誤期待時，授課者也常常不及格。15 年補教經驗加上最近試教 Claude Code 的觀察，聊一下教學品質的基本盤、老師的責任心、以及補習班 AI 轉型最實用的一句答案。
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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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Opus 4.7 After One Week: From the System Card to the Roasting, Where Did It Go Wrong?
Opus 4.7 launched on 4/16 and the Chinese and English communities ended up with opposite takes. The system card reads like a full win, but real usage burns quota at roughly 2x what Anthropic claimed, and Reddit spent the week roasting it. Here's what I saw, and why I rolled back to 4.6.
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Opus 4.7 上線一週：從系統卡到火烤文，到底哪邊出了問題
Opus 4.7 上線一週，系統卡數據看起來全面超越 4.6，但實測下來燒 quota 是官方宣稱的 2 倍，Reddit 一片火烤文。整理這週的災情、逆向分析、以及我自己退回 4.6 的路徑。
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90% of People Are Two Years Behind: The Real AI Adoption Gap
I demonstrated Claude Code to friends and they were all amazed. Then I gave them free Pro trial passes — three of them. Not a single one was used. That told me a lot about how AI adoption actually works.
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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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90% 的人落後兩年：AI 採用的真實落差
我把 Claude Code 示範給朋友看，他們都說驚艷。然後我把免費的 Pro 體驗 pass 發給他們——三張，一張都沒被用過。這件事讓我想清楚了很多關於 AI 採用的事。
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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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What Anthropic Did This Time: Cache Reduction and Token Anxiety Injection
Starting in early April, some Max and higher accounts had their subagent cache duration quietly reduced from 1 hour to 5 minutes — no announcement. Around the same time, users found a hardcoded "token remaining" warning being injected into Claude's context, causing it to cut work short prematurely. How to check your own setup, and what this pattern means.
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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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Anthropic 這次幹了什麼：快取縮水與 Token 焦慮注射
4 月初起，部分 Max 以上帳號的 subagent 快取維持時間被偷偷從 1 小時改成 5 分鐘，零公告。同期有用戶發現 Claude 被注入固定的「剩餘 token 警告」，導致 Claude 提前縮短工作。怎麼自查，以及這件事代表什麼。
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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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Two HTML/PDF Rendering Traps: Chrome Print Margin and qlmanage's Single-Page Problem
This week I exported a client proposal as HTML→PDF and split an internal report from PDF→images page by page. Both flows had a seemingly unsolvable trap. Each fix is one line of code, but tracking down that line cost me real time.
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兩個 HTML / PDF 渲染陷阱：Chrome print margin 和 qlmanage 的 1 張縮圖
這禮拜寫了客戶提案的 HTML→PDF 和內部報告的 PDF→圖逐頁拆分，兩個流程都有一個看似無解的陷阱。解法都是一行事情，但找到那一行花了我一小時。
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Digging into Claude Code's JSONL: Manual Context Usage, Cache Types, and Compact Detection
Claude Code's `/stats` only tells you the total token count, but the JSONL files hide a lot more—cache types, compact triggers, image-triggered cache misses. Here are the useful formulas I collected while building cc-audit.
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挖 Claude Code 的 JSONL：手動算 context 用量、分辨快取類型、偵測 compact
Claude Code 的 `/stats` 只告訴你總 token 數，但 JSONL 檔案裡其實藏著更細的資訊——快取類型、compact 觸發、貼圖 cache miss 都能手動算。這是我最近做 cc-audit skill 時整理出來的幾個實用公式。
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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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Claude Code's Cache Crisis: Why Your Quota Burns So Fast
A Reddit user reverse-engineered two official bugs, and combined with the compounding effect of 1M-token context, your quota might be silently burning at 20x the expected rate.
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Claude Code Skills Demystified: Lazy Loading and the Real Trigger Rate
Skills don't dump all their prompts into context by default. They load layer by layer on demand. But passive trigger rate is only 30-50%, so slash commands are your safest bet.
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Claude Code 的快取危機：為什麼你的額度燒得那麼快？
Reddit 大神逆向工程挖出兩個官方 Bug，再加上百萬 token 上下文的複合效應，你的額度可能在背後被吃掉 20 倍。完整事件始末與修復紀錄。
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Claude Code Skills 機制解密：按需載入與觸發率真相
Skills 不會把全部提示詞預設注入上下文。它是一層一層按需載入的。但被動觸發率只有 30-50%，打 slash 才是最保險的。
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Claude Code Source Leak: Three Secrets Unearthed by Reddit
Someone reverse-engineered Claude Code and found a hidden virtual pet system, next-gen model deception rate data, and an "Undercover Mode" that strips AI attribution from Anthropic employees' commits.
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Claude Code 源碼洩漏：Reddit 大神挖出的三個秘密
有人對 Claude Code 做了逆向工程，挖出了隱藏的電子寵物系統、下一代模型的欺騙率數據、以及讓 Anthropic 員工隱藏 AI 身份的 Undercover Mode。
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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。
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Mirror System: Weekly Reviews Without the Comfort
Normal weekly reviews let you make excuses for yourself. Mirror System doesn't offer reassurance — just feed your daily notes to Claude and watch it surface the patterns you've been avoiding.
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Mirror System：用 Claude 做不帶安慰的週回顧
普通的週回顧，你會幫自己找理由。Mirror System 不要肯定，不要安慰，只要事實——把本週 daily notes 餵給 Claude，看它反照出你不想正視的模式。
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Why Does Cowork Hit Your Limit in Hours While Claude Code Runs All Day?
Same Max plan, same Claude — but Cowork burns through tokens ten times faster. Here's why, and when to use which.
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為什麼 Cowork 幾小時就頂到限額，Claude Code 整天都沒事？
同樣是 Max 方案，Cowork 和 Claude Code CLI 的 token 消耗差距可以到十倍以上。這篇解釋為什麼，以及什麼時候用哪個。
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The 5 Levels of Claude Code: You Don't Choose to Upgrade, the Ceiling Forces You
From Raw Prompting to Orchestration — the 778-upvote Reddit framework where every level exists because the previous one broke.
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Claude Code 五個成熟度等級：你不是選擇升級的，是被天花板逼的
從 Raw Prompting 到 Orchestration，Reddit 上 778 個讚的框架——每一層存在的原因，是因為上一層壞掉了。
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Turning Books into Claude Skills: From Textbooks to Atomic Habits, the World Is Already On It
Turning books, frameworks, and methodologies into Claude Skills — making knowledge executable as interactive coaches. A roundup of popular examples and practical lessons.
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把書變成 Claude Skill：從教材到原子習慣，國外已經在瘋了
把書籍、框架、方法論轉成 Claude Skill，讓知識變成可執行的互動式教練。國外的熱門案例整理和實作心得。
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The Real Next Level in Claude Code: Context Management and Hooks
From Claude.md to Hooks — sharing the context management upgrade after heavy daily Claude Code usage. When rules pile up and compliance drops, Hooks become the perfect gatekeeper.
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Claude Code 的真正進階：上下文管理與 Hooks
從 Claude.md 到 Hooks，分享大量使用 Claude Code 後對上下文管理的理解升級。規則塞太多怎麼辦？Hooks 就是那個完美的守門員。
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Obsidian + Claude Code: My Daily Knowledge Management Workflow
Put your entire life into Obsidian, then let Claude Code tap in. How I do daily logs, manage to-dos, and why local Markdown beats Notion.
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Obsidian + Claude Code：我的日常知識管理工作流
把人生都放到 Obsidian，再讓 Claude Code 接入。日誌怎麼記、待辦怎麼管、為什麼本地 Markdown 勝過 Notion。
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One AI Tool to Rule Them All: Why I Only Recommend Claude Code
Instead of subscribing to a dozen AI tools, master one. What n8n, Lobster, and fomofly can do, Claude Code handles with a single skill.
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一個 AI 工具打天下：為什麼我只推薦 Claude Code
與其訂十幾個 AI 工具，不如把一個用到極致。n8n、Lobster、fomofly 能做的，Claude Code 加一個 skill 就搞定了。
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AI Security Boundaries: The Lobster Craze, Presidio, and My Three Rules
When everyone is going wild with AI automation, I chose to understand my own capability boundaries first. Sharing Presidio for data privacy and my security practices with Claude Code.
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AI 的安全邊界：龍蝦熱潮、Presidio、與我的三條鐵則
當所有人都在瘋 AI 自動化的時候，我選擇先搞清楚自己的能力邊界。分享 Presidio 隱私工具和用 Claude Code 工作的安全實踐。
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Claude Code Workshop Prep Notes: Teaching Non-Coders to Go Terminal-First
Designing a Claude Code workshop for non-engineers — from analyzing signup demand to crafting the curriculum, plus 15 quick-start tips for zero-coding-background learners.
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Claude Code 工作坊備課日誌：帶零基礎學員直上終端機
規劃一場給非工程師的 Claude Code 工作坊，從報名需求分析到教學設計，再到 15 條速成心法的完整備課歷程。
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claude-work-timer: Auto-Track Your Claude Code Working Hours
Billing clients by the hour with Claude Code? I built an open-source plugin to track actual working time automatically.
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claude-work-timer：讓 Claude Code 自動算工時
用 Claude Code 接案按時計費，甲方要看工時怎麼辦？寫了一個開源外掛自動算。
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Claude Code Initial Prompt Tips: Six Techniques for Effective AI Collaboration
Six practical tips for writing effective initial prompts in Claude Code, from clarifying your goals to leveraging plan mode for better AI collaboration.
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Claude Code 起始指令心法：六個讓 AI 真正聽懂你的技巧
分享六個下 Claude Code 起始指令的實戰心法，從釐清目標到善用計畫模式，讓你的 AI 協作更高效。
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What I Learned from 7,843 Claude Code Conversations
46 days, 6 projects, 7,843 conversations. This is not a manual — it's a diary of trial and error.
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Claude Code 用了 7843 條對話後的心得
46 天、6 個專案、7843 條對話，整理出來的 Claude Code 實戰心法。不是教學手冊，是踩坑日記。
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Recommended Reading: AI Articles from Early February
AI articles I read in early February 2026 — coding agents, AI's impact on work, the future of programming languages, and more.
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I scanned 500 Claude Code sessions and the AI stopped making the same mistakes
I used claude-log to scan 500+ Claude Code sessions across 6 projects, extracted every time I yelled at the AI, and turned those into CLAUDE.md rules. Here's what I found.
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推薦閱讀：二月上旬的 AI 文章精選
二月上旬讀到的 AI 好文，涵蓋 coding agent、AI 對工作的影響、程式語言的未來等主題。
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我掃了 500 個 Claude Code 對話紀錄，然後 AI 就不再犯同樣的錯了
用 claude-log 工具掃描歷史對話，從你罵 AI 的紀錄中提煉規則寫進 claude.md，讓 Claude Code 真正學會不再踩同一個坑。
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Critical Thinking in the AI Era: Playing Dumb, the Feynman Method, and What Future Talent Looks Like
AI won't replace your thinking, but it will expose the fact that you can't think. From rediscovering how to learn through AI interactions, to the growing demand for "AI collaboration skills" in exams and workplaces — observations from an educator.
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AI 時代的思考力：裝傻狂問、費曼學習法，與未來人才的樣子
AI 不會取代你的思考，但會暴露你不會思考。從跟 AI 互動中重新發現的學習態度，到未來考試與職場對「AI 協作力」的需求，一個教學者的觀察。
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How Teachers Can Embrace AI Without Getting Replaced
A 15-year teaching veteran shares how AI reignited his passion for teaching, how to build an AI clone of yourself, open-source your knowledge, and why "teachers who use AI" are the real threat.
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教學者如何擁抱 AI 而不被取代
一個教學從業 15 年的人，分享如何用 AI 重燃教學熱情、建立教學分身、開源知識庫，以及為什麼「會用 AI 的老師」才是真正的威脅。
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My AI Workflow: Convergence and Divergence
Distilling my AI collaboration philosophy into two modes -- convergence and divergence. Plus how I build a personal knowledge base, and my day-to-day practice of running multiple agents in parallel.
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我的 AI 工作流：收斂與發散
把跟 AI 協作的心法整理成「收斂」與「發散」兩個模式。加上個人知識庫的建構方法，以及多 Agent 並行的日常實踐。
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FIRE Planning with Claude Skills: Talking Retirement with AI
I fed all my assets, liabilities, income, and expenses into Claude Code, then just asked "am I going broke?" A month of conversations turned into a full FIRE planning toolkit — and why I open-sourced it.
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用 Claude Skill 做 FIRE 理財規劃：跟 AI 聊退休
把資產、負債、收支全部餵進 Claude Code，直接用對話問「我會不會破產」。一個月下來累積的 FIRE 理財規劃工具，以及為什麼我把它開源了。
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Building AI Products from Scratch: A Non-Engineer's Four-Generation Evolution
A teacher-turned-builder shares the real story of four generations of AI tool development—RAG, platform architecture, cross-border deployment, and open-source strategy, with all the pitfalls along the way.
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從零打造 AI 產品的踩坑日記：一個非工程師的四代進化
一個教學從業者，從 GPT 自訂 Agent 起步，歷經四代 AI 工具開發，分享 RAG、平台架構、跨國部署、開源策略的真實踩坑紀錄。
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The Truth and BS of Vibe Coding: Observations from a 10-Year Teaching Veteran
We shouldn't uniformly trash Vibe Coding, but we do need to recognize the traps in course quality. A teacher with 10+ years in the game shares how to tell the real deal from the fakes.
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Vibe Coding 的真與假：一個從業十年老師的觀察
不該統一貶低 Vibe Coding，但也要認清課程品質的陷阱。一個教學從業十年以上的人，分享辨識有料與沒料的方法。
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The Dunning-Kruger Curve of Claude Code: From Clueless to Perfect Sync
A heavy user with zero engineering background shares the Dunning-Kruger curve of Claude Code from day one to week three, and the workflow that finally clicked.
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Claude Code 的達克曲線：從陌生到極致同步的實戰心得
一個非工程師背景的重度使用者，分享 Claude Code 從第一天到第三週的達克曲線效應，以及最終找到的高效互動方式。
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Can't See Myself in Three Years: Anxiety and Adaptation in the Age of AI
AI is iterating so fast that I can't see where I'll be in three years. The journey from anxiety to finding my footing, and why I believe AI is a Kingmaker.
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看不見三年後的自己：AI 時代的焦慮與適應
AI 飛速迭代，讓我看不見自己三年後的職場位置。從焦慮到找到定位的心路歷程，以及「AI 是造王者」的核心觀點。
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Claude vs Gemini vs GPT: A Power User's Honest Field Notes
Six months of daily-driving all three major AI models. Claude's reliability, Gemini's self-doubt spirals, GPT's decline, and what I ended up subscribing to.
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Claude vs Gemini vs GPT：一個重度使用者的模型體感實錄
同時使用三大 AI 模型半年多的真實體感記錄。Claude 的穩定、Gemini 的自我懷疑、GPT 的退場，以及我最後的訂閱選擇。
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Hello World: Why I Started This Blog
Welcome to Dustin's AI Lab — a blog about practical AI workflows, tools, and insights for learning and productivity.
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你好世界：為什麼我開始寫這個部落格
歡迎來到 Dustin's AI Lab — 分享 AI 工作流、工具與學習心得的技術部落格。
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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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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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AI Micro-Notes 2025: Thoughts Too Short to Trash
Short AI hot takes from the second half of 2025, accumulated from Threads and IG. Model roasts, dev pitfalls, industry observations, tool impressions — each no more than three lines.
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AI 碎念日記 2025：那些太短但捨不得丟的觀點
2025 年下半年在 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。