#提示工程
Live, measured metrics for the hashtag #提示工程 from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #提示工程
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · mastodon.social (Mastodon public tags API) · fetched 2026-08-22 17:55 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mastodon.social (Mastodon public search API) · fetched 2026-08-22 17:55 UTCNo related tags with measured usage found for #提示工程.
Live pulse
measured · mastodon.social (Mastodon tag timeline) · fetched 2026-08-22 17:55 UTCEverything below is measured over the latest 32 public posts (spanning ~28284 hours).
Posting hours (UTC) — busiest: 00:00
Languages: Chinese (Taiwan) (31) · Chinese (1)
Avg boosts / post: 0
Top of the latest posts
🌘 精煉初始提示，而非不斷修正 ➤ 告別 AI 程式碼協作中的「教練式」循環，擁抱一次到位的指令精煉 ✤ https://elite-ai-assisted-coding.dev/p/refine-your-initial-prompt-instead-of-course-correcting 本文探討了與 AI 編程助手協作時應採取的最佳策略。作者指出，當初始提示未能達到預期結果時，許多人傾向於透過追加訊息來進行逐步修正，但這種方式容易造成 AI 的混淆，影響其效能。相較
🌘 AI 的現狀與省思 ➤ 從撰寫程式碼到文字實作的軟體開發新範式 ✤ https://srikanth.ch/posts/the-ai-situation/ 本文深入探討開發者與人工智慧協作的實務變革。作者指出，隨著開發重心從手寫程式碼轉向系統設計，開發者必須學會靈活調整提示策略、克服上下文窗口限制並有效壓縮資訊。透過挑選合適模型與建立測試工具的回饋循環，開發者能更精準地引導 AI。最終，實作階段並未消失，而是轉化為以文字進行架構規劃的全新開發模式。 + 說得太貼切了！現
🌘 大型語言模型獎勵專業素養 ➤ 為什麼在 AI 時代，你的專業領域知識比以往更重要 ✤ https://www.seangoedecke.com/llms-reward-expertise/ 雖然大型語言模型讓所有人都能輕易跨足陌生領域，但真正的產出品質仍取決於使用者的專業素養。作者透過分析數學家陶哲軒與 ChatGPT 的互動，指出專家能藉由精確的引導、對錯誤的敏銳察覺以及深厚的領域背景，從模型中挖掘出一般人無法獲取的深度洞見。這顯示在 AI 時代，人類的專業知識並非被
#提示工程 across platforms
every network with a public tag surfaceFollow #提示工程 straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/提示工程