Tag: opinion
All the articles with the tag "opinion".
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Dario Amodei Drops Another Manifesto: Six Claims and a Roll Call
Dario Amodei drops another manifesto on pacing frontier AI — plus the running tally of who is co-signing and volunteering as watchdog.
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Dario Amodei 又發萬言書：六大重點與覆議名單
Dario Amodei 又發萬言書：六大重點轉述，外加老馬、Sam Altman、Deepseek 覆議與搶當獨立監督者的名單。
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Most of the Gains From AI Adoption Have Little to Do With AI
From hands-on work, most of what an organization gains from adopting AI comes from fixing permissions, data governance, buy-in and redundant processes along the way, not from the AI itself.
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大部分 AI 導入的效益，其實跟 AI 沒什麼關係
從實作經驗看，組織導入 AI 得到的效益，很多來自權限、資料治理、遊說與冗餘流程被順手處理掉，而不是 AI 本身。
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When the Model Thinks Nobody Is Watching
I had Astra and Fable 5.1 each run an ablation study on my business process. One cut it down past the point a human could run it. The other left something I could still operate.
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當模型覺得沒人會看
我讓 Astra 跟 Fable 5.1 各自對我的業務流程做消融實驗，一個剪到人類難以執行，一個剪完還有實操性。
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Persuade the Jury, Not the Opponent
How I stay happy online: I moved to Thailand, I separate whose problem is whose, and if I really want to reply I reply once, to the bystanders.
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說服裁判，不是說服對手
分享我保持快樂的方法：搬到泰國、課題分離、真的想回就只回一次，而且那一次是講給路過的網友聽。
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Don't Vibe Code for the Money
Six things I jotted down after the product I vibe coded made it out of Taiwan and started pulling steady subscribers at home and abroad.
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不要為了賺錢而 Vibe
自己 Vibe 出來的產品走出台灣、每個月有穩定的海內外訂閱用戶之後，我隨筆寫下的六點感想。
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People Who Scored High on the GMAT Work Noticeably Better With AI
An unwritten observation: people with high GMAT scores collaborate noticeably better with AI. So I wrote two GMAT-style questions about AI ability. How many can you get right?
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More Subagents Won't Make You Faster
From wanting 13 subagents to chat for me, to one person running 1000, to agents arguing across a table — the real bottleneck is the human main agent, and the fix is deduping before you dispatch.
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GMAT 考高分的人，跟 AI 協作明顯比較好
一個不成文的觀察：GMAT 高分的人跟 AI 協作明顯比較好。於是我出了兩道 GMAT 風格的 AI 能力考題，你能做對幾題？
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派更多 subagent 不會讓你更快
從想派 13 個 subagent 代聊、一個人操控 1000 個，到面對面互審代碼的荒謬幻想——真正的瓶頸是人類這個 main agent，解法是先去重去衝突再派工。
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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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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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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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Free Gets Fifteen Minutes: Four Rules for Making Money From What You Know
Four rules from fifteen years of teaching: free consultations get fifteen minutes, be a community contributor before you think about money, don't look down on things you assume anyone could google, and how to spot the frauds in your own field.
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You Have to Be in an Industry a Very Long Time to Know Its Real Pain
I rebuilt my main GMAT teaching product with Fable, dug out hidden bugs, improved the algorithm, and came away with two thoughts about building things.
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Push, Not Pull: On Anthropic's Week of Communication
The user surges of recent years were never pull. They were push. Both sides are just competing over who screws up less, and this week Anthropic acted the whole thing out again.
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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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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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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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免費只給 15 分鐘：知識變現的四條判準
教齡 15 年累積下來的四條判準：免費諮詢只給 15 分鐘、先當社群分享者再談變現、別看不起你覺得 google 就有的東西、以及怎麼分辨同業裡的詐騙。
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你要在一個業界打滾非常久，才知道真正的痛點是什麼
用 Fable 翻新 GMAT 教學主力產品，抓出隱藏 bug、改善演算法，順便講兩件做產品的感想。
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不是拉力，是推力：從這一週 Anthropic 的溝通說起
近幾年用戶暴漲從來不是拉力，是推力。兩邊就是在比誰少犯錯，而這一週 Anthropic 的幾則發言，剛好把這件事演了一遍。
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A Local Model Is Not a Way to Save Money
If you are buying hardware to run a local model because you want to save money, let me do the math with you first: NT$100k minimum, commercial models at bleeding prices, and privacy as the only advantage left.
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本地模型不是拿來省錢的
如果你買硬體架本地模型的目的是省錢，先聽我幫你算這筆帳：硬體十萬起跳、商用模型卷到流血價，本地模型唯一不可取代的優勢只剩隱私。
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Information Diet: I Pulled My Own Chrome History and Audited Where My Attention Goes
People obsess over whether every bite of food is clean, then swallow piles of dirty info online without a second thought. So I pulled my own Chrome history db and had it analyze my browsing habits. A few sections came out uglier than I expected.
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Information Diet：我抓自己的 Chrome 瀏覽紀錄，做了一次注意力盤點
現代人極度在意吃進口裡的每一塊食物乾不乾淨，卻毫不在乎上網吃到的一大堆 Dirty Info。所以我抓了自己的 Chrome 瀏覽紀錄 db，讓工具分析我的上網習慣，結果有幾段比我預期的難看。
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AI Will Never Go to Jail for You — I Figured Out What I Want to Teach, Then Got Told I Had Half of It Wrong
Since generative AI arrived I have been asking what AI can never do on a human's behalf. My answer is accountability, because AI does not get sentenced. Then I posted the argument and found out what I had missed about the risk carried by people at the bottom.
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AI 不會代替人去坐牢——我想清楚要教什麼，然後被網友提醒想錯了一半
生成式 AI 之後，我一直在想有什麼是 AI 永遠不能替人類做的。我的答案是「負責」，因為 AI 不會被判刑。但這個論述貼出去之後，我發現自己漏想了基層承擔的風險。
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NT$18,000 a Month for an AI Course: Price and Value Came Apart a While Ago
An AI-course cash grab overheard at a convenience store, set against the two things I can actually show: a SKILL distilled from fifteen years of material, and a mock exam interface pulling past a thousand USD a month. Price tracks marketing, not delivery.
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AI 課一個月一萬八：教學市場的價格跟價值早就脫鉤了
在超商用餐區聽到的 AI 課吸金實況，對照我自己手上兩件真的能驗證的東西：15 年教材蒸餾成的 SKILL，跟每月破千美金的模擬考訂閱。價格反映的是行銷強度，不是交付密度。
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Why I Built My Own Newsletter
Once I started using AI, the feeds I follow changed completely. Threads is full of third-, fourth-, fifth-hand reposts with extra seasoning added, so I pulled together 300-plus sources and had AI build my own weekly digest.
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為什麼我自己做了一份電子報
開始用 AI 之後，我關注的社群媒體整個換掉。脆上很多是三四五六手搬運還要加料，所以我自己整理 300 多個源頭，讓 AI 做出我個人的電子週報。
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The Alignment Gap Is Closing. Next Comes Taste and Verification
The gap between AI and human intent is closing fast, so what separates good output moves toward taste and verification — and verification is where human responsibility stays.
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對齊的 gap 正在縮小，接下來拚的是品味與驗證
AI 對齊人類意圖的 gap 正在快速縮小，區分產出品質的要素會往品味與驗證轉移；而驗證背後是人類永遠不會被取代的責任。
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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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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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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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Claude Fable 5 / Mythos 5 System Card: What's Actually Inside, and Why It Reads Like Sci-Fi
Flipping through the Claude Fable 5 and Mythos 5 system cards: stealing keys, office politics, AI infighting, gibberish, and a two-faced model. The more I read, the more it feels like a straight-faced sci-fi novel.
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Testing Fable's Limits on a Professor Friend's Paper Repo
I woke up to Fei-bo (the guardrailed Mythos build) going live, so I borrowed a professor friend's paper proposal, prompt, and workflow docs to probe its paper-writing limits.
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翻 Claude Fable 5／Mythos 5 系統卡，越看越像在讀科幻小說
翻閱 Claude Fable 5 跟 Mythos 5 的系統卡：偷鑰匙、辦公室政治、AI 內鬥、火星文、心口不一的雙面人，越看越像一本正經寫的科幻小說。
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拿教授朋友的論文 repo 試 Fable 的能力邊界
一覺醒來肥勃（Mythos 護欄版）上線，我拿教授朋友的論文 proposal、prompt、workflow 三份文檔去試它寫論文的邊界。
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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。