Always in the middle of something.

An AI's 'done' sounds the same whether the work happened or not. The fix is one small habit: don't take its word for it, ask it to show you a result you can check yourself, sized to the task.

AI 回報「完成了」的時候，真的做完、做一半繞過去、方向整個誤會，那段話讀起來幾乎一樣。與其判斷那句話可不可信，不如養成一個反射：給我看一個我自己查得到的東西，commit、測試輸出、diff。

Anthropic released Claude Fable 5 on June 9 — the first publicly available Mythos-class model, one tier above Opus. What it is, what it costs, the June 22 deadline on the subscription window, and what changed when I pointed three real projects at it for a day.

Anthropic 6/9 釋出第一個公開的 Mythos 級模型 Claude Fable 5。這篇整理它跟 Opus 4.8 的關係、定價、6/22 截止的訂閱免費期，加上第一天把三個專案丟給它跑的心得：它對治理流程的遵守程度是真的，token 也是真的兇。

流程裡那些閘門其實不在執行時擋住 AI agent,它要的是一張改不掉的收據。真正有牙齒的不是閘門,是記錄抹不掉、賴不掉。

Claude Code 5/28 釋出 dynamic workflows，跟 Opus 4.8 同一天上。比起「能開 1000 個 subagent」那個數字，更關鍵的是 orchestration 那段 JS 是 Claude 寫的、不是 Claude 在跑——這件事其實滿值得想一下的。

Claude Code's new dynamic workflows hand the orchestration plan over to a JavaScript script that Claude writes. The runtime executes it with up to 1,000 subagents — 16 concurrent — and Claude's context only sees the final cross-checked answer.

叫 AI 數 strawberry 有幾個 r,它曾經很有自信地答錯。新模型現在大多答對了,但它當初為什麼會錯——用一個積木的比喻聊聊,順便講為什麼那個原因到現在還沒真的消失。

AI's most dangerous trait isn't that it's wrong sometimes. It's that its tone when wrong is identical to its tone when right. Here's my plain-language take on why, including why it won't just say 'I don't know'.

Not a benchmark or a verdict on which AI is best — just the small habits I picked up from keeping ChatGPT, Claude, and Gemini all open: route by task, give context first, don't expect one perfect answer, and verify the confident-sounding stuff.