Tag: claude-code
All the articles with the tag "claude-code".
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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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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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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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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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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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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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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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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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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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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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Claude Seeing Ghosts Four Nights Straight: A Log of Opus 4.8 Fabricating Tool Output
A four-day log of Opus 4.8 tool-result confabulation: from the technical symptoms to the GitHub issue to JSONL forensics.
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Claude 半夜見鬼連續四天：Opus 4.8 捏造工具輸出實錄
Opus 4.8 連續四天的 tool-result confabulation 實錄：從技術現象、GitHub issue 到 JSONL 鑑識。
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Opus 4.8 Cries 'Prompt Injection,' Codex GPT-5.5 Tracks Down the Real Cause: a Worktree Race
With multiple sessions open in one repo and no worktree, Opus 4.8 raised a false prompt injection alarm, told me to check for supply-chain attacks and rotate API keys, until Codex GPT-5.5 read the session log and pinned the real cause: just a worktree race.
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Opus 4.8 搞烏龍報『提示注入攻擊』，Codex GPT-5.5 揪出 worktree race 真因
Opus 4.8 在我忘開 worktree 的情況下誤報「提示注入攻擊」，叫我去查供應鏈、rotate API key，最後 Codex GPT-5.5 查 session log 才揪出真因只是 worktree race。
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Running Taiwan Sports-Lottery Odds With Mobile Claude Code, Standing in the Lottery Shop: the Odds Are Garbage, You'll Lose
Walked past a lottery shop, felt like placing a sports bet, and on a whim wired up a betting-odds skill on mobile Claude Code right there. The verdict: the correct-score market carries a 191% overround, every expected value is negative, you lose.
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在彩券行用手機 Claude Code 算運彩賠率：台運賠率爛透了，誰下誰賠
路過彩券行起念想下運彩，順手用手機 Claude Code 接賭率分析 skill 現場開算，結論：台運波膽盤水錢高達 191%，期望值全負，誰下誰賠。
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Two Mindsets for Getting Unstuck: Logical Thinking, and the AI Pedagogy of Never Making the Same Mistake Twice
Teaching a student today, I said that breaking through when you are stuck is not hard. What matters are two mindsets: logical thinking, and an AI pedagogy like raising a child, where the goal is not for the AI to never err, but to never make the same mistake twice.
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卡關時的兩個心態：用邏輯思考，與『不貳過』的 AI 教育學
今天跟一個學員教學時談到，卡關時破除障礙並不難，重點是兩個心態：用邏輯思考，以及像帶孩子一樣的 AI 教育學，追求的不是讓 AI 無過，而是不貳過。
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Teaching a Talent Agency to Use Claude Code, and the Soft Landing of the DK Confidence Curve
A short trip back to Taiwan packed with private training sessions: walking a talent agency through contract review, receipt reconciliation, and closeout reports with Claude Code, plus a note on the DK confidence curve and its soft landing.
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帶藝人經紀公司用 Claude Code，與 DK 信心曲線的軟著陸
短暫回台跑私人場培訓，帶藝人經紀公司的企劃、製片、財務用 Claude Code 做合約審閱、單據核對、結案報告，順便聊聊 DK 信心曲線的快速上坡與軟著陸。
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The 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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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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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 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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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。