6. 我重寫了我的卡拉OK應用,讓每個人的手機都能變成遙控器 I Rebuilt My Karaoke App So Everyone''s Phone Could Be a Remote (dev.to)
7. 人工智能的失敗並非因為模型本身有問題,而是因為它缺乏深層的基礎。 AI doesn''t fail because the model is bad. It fails because there''s nothing underneath it (dev.to)
9. OrinIDE v1.0.7 — 人工智能終於能全面理解您的整個項目了 OrinIDE v1.0.7 — The AI Finally Understands Your Whole Project (dev.to)
11. 從“三天截止期限”的災難到真正的產品:重振我的首個全棧項目 From a 3-Day Deadline Disaster to a Real Product: Reviving My First Full-Stack Project (dev.to)
12. 克勞德與Gemini在4個安全領域中的對決:勢均力敵——而63%的AI代碼在加固過程中被跳過 Claude vs Gemini Across 4 Security Domains: A Dead Heat — and the Hardening 63% of AI Code Skips (dev.to)
13. 僅靠懶加載還不夠:我是如何將加載時間從15秒縮短到1.1秒的 Lazy Loading Wasn''t Enough: How I Cut Load Time from 15s to 1.1s (dev.to)
14. 我對移動運營商的APK進行了逆向工程——隨後Hermes Agent撰寫了執行報告 I reverse-engineered my mobile operator''s APK — then Hermes Agent wrote the executive report (dev.to)
15. 我將Hermes Agent轉變為一個可驗證的代理操作系統 I Turned Hermes Agent into a Verifiable Agent Operating System (dev.to)
16. 我在 Python 代理中添加了一個 71 行代碼的黑盒子,然後使用 DuckDB 查詢了那次價值 200 美元的崩盤事件 I Added a 71-Line Black Box to My Python Agent, Then Queried the 200 Crash With DuckDB (dev.to)
19. 重振 Ultra Creative Suite:首款專為視障用戶設計的全無障礙視頻編輯器 Reviving Ultra Creative Suite: The First Fully Accessible Video Editor for Blind Users (dev.to)
21. 每一場偉大的杯賽都始於一個正確的問題——我藉助 Hermes Agent 構建了支撐這個答案的社區 Every Great Cup Starts with the Right Question — I Built the Community Behind the Answer with Hermes Agent (dev.to)
22. 我用 Python 開發了一款人工智能驅動的電腦顯示器。28 位陌生人共同構成了它的“大腦”。PC Workman 1.7.6 I Built an AI-Powered PC Monitor in Python. 28 Strangers Shaped Its Brain. PC Workman 1.7.6 (dev.to)
23. 兩年前我沒能完成的項目——ChatGPT筆記本 The Project I Couldn’t Finish 2 Years Ago - Notebook for ChatGPT (dev.to)
24. 我在 PM Agent 中添加了人工否決功能——看看首先出了什麼問題 I Added a Human Veto to My PM Agent — Here''s What Broke First (dev.to)
25. 500 MB 的緩衝區如何導致我們的歸檔任務失敗——以及為何流式傳輸解決了這個問題 How a 500 MB Buffer Killed Our Archival Job — And Why Streaming Fixed It (dev.to)
29. Kubernetes 過度使用:為何我為小型環境打造了一款“K8s 殺手” The Kubernetes Overkill: Why I Built a "K8s Killer" for Small Environments (dev.to)
30. 一款自託管的 Google reCAPTCHA 替代方案(我們提供該服務) A self-hosted Google reCAPTCHA alternative (we ship it) (dev.to)
31. 我開發了“Sổ Lãi”——一款專為越南網店設計的實用利潤追蹤工具 I Built Sổ Lãi, a Practical Profit Tracker for Vietnamese Online Shops (dev.to)
32. 我的 AI 總是在胡編亂造職業發展路徑。我放棄了這個項目。GitHub Copilot 幫我修復了真正存在的問題。 My AI Kept Hallucinating Career Paths. I Abandoned the Project. GitHub Copilot Helped Me Fix What Was Actually Broken. (dev.to)
33. 開發者機會雷達 #1:10萬美元的人工智能資助金、兩項研究員獎學金以及人工智能代理資源 Dev Opportunity Radar #1: A 100K AI Grant, Two Fellowships, and an AI Agent Resource (dev.to)
34. DevRelCon NYC 2026:開發者關係、DevX 與開發者營銷的交匯之地 DevRelCon NYC 2026: Where Developer Relations, DevX, & Developer Marketing Come Together (dev.to)
35. Copilot 幫助我將我的個人項目發佈到了 App Store Copilot helped me deploy my passion project to the App Store (dev.to)
36. Git 與 GitHub:如何使用簡單的 Git 命令管理 GitHub 倉庫 Git for GitHub: How to use simple Git commands to manage a GitHub repository (dev.to)
39. 我為自己的工學學士畢業設計開發了一個 MCP 代理框架。發佈首周,該框架在 npm 上的下載量就突破了 750 次。以下便是它的逆襲故事。 I Built an MCP Agent Framework for My B.Tech Major Project. It Got 750 npm Downloads in Week One. Here''s the Comeback Story. (dev.to)
41. 利用 Hermes Agent 構建以離線模式為主的叢林大火響應平臺 Building an Offline-First Bushfire Response Platform With Hermes Agent (dev.to)
43. AI 代理在處理我們 80% 的代碼方面表現出色。剩下的 20% 正是我們仍需資深開發人員的原因。 AI Agents Are Great at 80% of Our Code. The Other 20% Is Why We Still Need Seniors. (dev.to)
50. Hermes Mentor —— 助你擺脫教程地獄的本地 AI 助手 Hermes Mentor — A Local AI Agent That Gets You Out of Tutorial Hell (dev.to)
51. Next.js 16 在 4 個地方導致我的應用崩潰,但都沒有拋出錯誤 Next.js 16 Broke My App in 4 Places and None of Them Threw an Error (dev.to)
56. GitHub Copilot 幫助我們在電子商務業務中將時間縮短了 50% 至 75% Github Copilot helped us cut down 50-75% time in our e-commerce business (dev.to)
62. 如果連微軟和優步都負擔不起人工智能編程,我們其他人還有什麼機會? If Microsoft and Uber can''t afford AI coding, what chance do the rest of us have? (dev.to)
63. 現在我明白為什麼翻譯們會因人工智能而感到恐慌了——程序員也該恐慌嗎? Now I See Why Translators Are Panicking Over AI—Should Coders Panic Too? (dev.to)
66. 為什麼人工智能生成的代碼總是“夠用”——卻永遠稱不上“出色” Why AI-Generated Code Is Always Good Enough — And Never Great (dev.to)
67. 一款基於 Google Gemma 4 的 100% 私有本地 AI 簡歷優化工具:我是如何打造 ResuMate 的! A 100% Private, Local AI Resume Optimizer with Google Gemma 4: How I Built ResuMate! (dev.to)
68. Google I/O 2026:AI 僅用 12 小時就開發出一個操作系統。而我卻把時間都花在整理截圖上了。 Google I/O 2026: AI Built an OS in 12 Hours. I Spent Mine Sorting Screenshots. (dev.to)
69. 別讓人工智能破壞你們的集體思維:面向工程團隊的實用指南 Don’t let AI break your collective thinking: a practical guide for engineering teams (dev.to)
70. 我放棄了雲端大型語言模型,轉而使用 Gemma 4 4B:一位 DevOps 工程師的 48 小時現實檢驗 I Ditched Cloud LLMs for Gemma 4 4B: A DevOps Engineer''s 48-Hour Reality Check (dev.to)
71. PromptGuard:我開發了一款本地 AI 隱私防火牆,能在提示詞離開您的設備之前對其進行數據脫敏處理 PromptGuard: I Built a Local AI Privacy Firewall That Sanitizes Your Prompts Before They Leave Your Machine (dev.to)
72. Vestige:一款不會對你吹牛的Gemma 4腦電波追蹤儀 Vestige: A Gemma 4 Brain Tracker That Won''t Blow Smoke Up Your Ass (dev.to)
73. 先做再用:我是如何從零開始編寫435節人工智能工程課程的 Build It, Then Use It: How I wrote 435 AI engineering lessons from scratch (dev.to)
74. 你的公司不會用優秀的AI來取代你。他們只會用糟糕的AI來取代你。 Your company won''t replace you with good AI. They''ll replace you with bad AI. (dev.to)
75. NeuralHats:我利用Gemma 4將愛德華·德·博諾的“六頂思考帽”模型應用於本地化大型語言模型 NeuralHats: I Put Edward de Bono’s Six Thinking Hats on Local LLMs Using Gemma 4 (dev.to)
78. 大家都在熱議 Gemini 3.5 Flash。但 2026 年 Google I/O 大會上的真正亮點其實是一個技能文件。 Everyone''s Talking About Gemini 3.5 Flash. The Real Story at Google I/O 2026 Was a Skill File. (dev.to)
80. Google Antigravity 1.0 至 2.0/IDE 快速遷移指南 Google Antigravity 1.0 to 2.0/IDE Quick Migration Guide (dev.to)
81. 從“洞穴”裡的手機到全球開源:谷歌的Gemma模型為何是預算有限開發者的救命稻草 From a Phone in a "Cave" to Global Open Source: Why Google’s Gemma Models are a Lifeline for Budget Developers (dev.to)
83. 我在筆記本電腦的顯卡上對 Gemma 4 E4B 的 128K 上下文進行了壓力測試——召回效果很好,預填充效果則不盡如人意 I stress-tested Gemma 4 E4B''s 128K context on a laptop GPU — recall is great, prefill is not (dev.to)
85. 2026年穀歌I/O大會上最被低估的公告,竟被埋沒在一段90秒的演示中 The Most Underrated Announcement from Google I/O 2026 Was Buried in a 90-Second Demo (dev.to)
86. 我基於 Gemma 4 E4B 的 128K 上下文構建了一個本地文檔問答工具——耗時五天,未使用 RAG,也未連接雲端 I built a local document Q&A tool around Gemma 4 E4B''s 128K context — five days, no RAG, no cloud (dev.to)
87. 我僅用3個月就搭建了一個生產級電商平臺——GitHub Copilot 就是我的聯合創始人 I Built a Production-Grade E-Commerce Platform in 3 Months — GitHub Copilot Was My Co-Founder (dev.to)
89. 7 個 Next.js 16 版本的緩存漏洞:編譯通過卻在生產環境中悄然失效 7 Next.js 16 Caching Bugs That Compile Fine and Break Silently in Production (dev.to)
91. 我提高了Gemma 4的代幣上限。Dense模型不再拒絕了。 I Raised Gemma 4''s Token Cap. The Dense Model Stopped Refusing. (dev.to)
92. 您應該在開發中使用 Gemma 4 嗎?通過多維分析,判斷 Gemma 4 是否適合您! Should you use Gemma 4 for your Development? A Multiversal Analysis to Determine if Gemma 4 is Right for You! (dev.to)
95. 我們如何利用 Gemini Embeddings 在 DEV 上構建一個更智能、由社區驅動的信息流 How we''re using Gemini Embeddings to build a smarter, community-driven feed on DEV (dev.to)
96. 無障礙功能——這看起來正是開發者倡導者大顯身手的時候! Accessibility - This looks like a job for a developer advocate! (dev.to)
100. 回收變簡單:一款由Gemma 4驅動的波蘭回收助手 Recycling made easy: a Polish recycling assistant powered by Gemma 4 (dev.to)
102. 利用人工智能構建數據庫性能測試工具:真實詳解 Building a Database Performance Testing Tool With AI: The Honest Breakdown (dev.to)
103. 參加 GitHub “Finish-Up-A-Thon” 挑戰賽:總獎金高達 3,000 美元! Join the GitHub Finish-Up-A-Thon Challenge: 3,000 Prize Pool! (dev.to)
106. 中級開發者的悖論:為何初級開發者從容不迫,而中級開發者卻會在凌晨三點重構你的代碼 The Mid-Dev Paradox: Why Juniors Are Chill and Mid-Levels Will Reorganize Your Code at 3 AM (dev.to)
109. MCP 現已登陸您的手機:Google AI Edge Gallery 的實際功能是什麼 MCP Just Landed on Your Phone: What Google AI Edge Gallery Actually Does (dev.to)
110. 一個糟糕的提示詞如何在18分鐘內耗盡了我40美元的Claude預算 How one bad prompt burned 40 of my Claude budget in 18 minutes (dev.to)
111. 我決定構建一個 Kubernetes 替代方案。是的,我知道我瘋了 I decided to build a Kubernetes alternative. Yes, I know I''m crazy (dev.to)
114. Google AI Edge Gallery 現已支持在設備上運行 MCP。隱私架構 Google AI Edge Gallery Now Runs MCP On-Device. The Privacy Architecture (dev.to)
115. 發現了一個隱藏在我關注者中的、有組織的 GitHub 關注機器人網絡? Found a Coordinated GitHub Follow Botnet Hiding in My Followers? (dev.to)
116. 為印度普及前沿人工智能:Gemma 4 在資源匱乏環境中的邊緣計算能力 Democratizing Frontier AI for Bharat: Gemma 4’s Edge Capabilities in Low-Resource Environments (dev.to)
119. Cloudflare 已棄用我的生產環境模型。推薦的升級方案需花費 4 美元/百萬令牌。而 Gemma 4 MoE 則無需此費用。 Cloudflare Deprecated My Production Model. The Recommended Upgrade Costs 4/M Tokens. Gemma 4 MoE Doesn''t. (dev.to)
123. 我開發了一個免費的調試器,因為在開發過程中,Next.js 16 的 ''use cache'' 功能完全無法察覺 I built a free debugger because Next.js 16 ''use cache'' was completely invisible during development (dev.to)
124. 如果在人工智能時代,房間裡的每部手機都能變成遊戲手柄,會怎樣? What If Every Phone in the Room Was a Game Controller — in the Age of AI? (dev.to)
126. 誠實是最好的策略。關於在DEV環境中使用AI的秘密之戰 Honesty is the best Policy. The Secret Wars on the use of AI on DEV (dev.to)
129. 我還是不想給克勞德 SSH 訪問權限,所以我為我的家庭實驗室搭建了一個代理服務器 I still don''t want to give Claude SSH access, so I built a doctor for my homelab (dev.to)
130. 使用 Antigravity 和 Strava API 構建騎行分析 Web 應用 Building a Ride Analysis Web App with Antigravity and the Strava API (dev.to)
132. 自託管版 Gemma 4 用於生產自動化,揭示了兩個 Ollama 漏洞 Self-Hosting Gemma 4 for Production Automation Revealed Two Ollama Bugs (dev.to)
135. 您的代碼庫存在技術債務。但您的團隊是否也存在理解債務? Your Codebase Has Technical Debt. But Does Your Team Have Comprehension Debt? (dev.to)
136. 如今人人都在談論更強大的AI模型。而我開發了一款基於Gemma 4的“農場醫生”系統,即使在斷網時也能正常運行。 Everyone''s Talking About Bigger AI Models. I Built a Gemma 4 Farm Doctor That Works When the Internet Doesn''t. (dev.to)
137. 我直接在瀏覽器中運行了 AI 模型,並測量了其對核心網絡指標的影響 I Ran AI Models Directly in the Browser and Measured What It Did to Core Web Vitals (dev.to)
139. 我把過去六個月的回顧資料給了克勞德。它發現了我之前遺漏的三點。 I gave Claude six months of our retros. It found three things I''d missed. (dev.to)
140. DeepSeek 正運行在你最常用的 AI 工具中——而沒人告訴你 DeepSeek Is Running Inside Your Favorite AI Tool – And Nobody Told You (dev.to)
141. 我為 Gemma4 挑戰賽開發了一個實時美國手語(ASL)翻譯器,無需雲端支持 I built a real-time ASL interpreter for the Gemma4 challenge, no cloud needed (dev.to)
142. 我開發了一款桌面應用,徹底告別了“打開7個終端窗口然後祈禱”的日常 I Built a Desktop App That Ends My “Open 7 Terminals and Pray” Routine (dev.to)
144. #100DaysOfCode 第100天——我的成果、收穫與下一步計劃 Day 100 of #100DaysOfCode — What I Built, What I Learned, and What''s Next (dev.to)
145. 我受夠了 Docker 佔用我的樹莓派內存——於是我開發了自己的容器編排工具 I Got Tired of Docker Eating My Raspberry Pi''s RAM — So I Built My Own Container Orchestrator (dev.to)
146. Gemma 4 対 克勞德 対 Llama:哪款模型最受開發者青睞 Gemma 4 vs Claude vs Llama: Which Model Wins for Devs (dev.to)
147. “最後的開發者博物館”:從 Stack Overflow 到人工智能 The Last Developer Museum: From Stack Overflow to AI (dev.to)
149. 我在 Gemma 4 中添加了三條規則。MoE 進行了搜索。Dense 模型拒絕了。 I Added Three Rules to Gemma 4. The MoE Searched. The Dense Model Refused. (dev.to)
152. 別再憑感覺來評估你的代理技能了。消除上下文安全風險。 Stop trusting your agent skills with vibes. Eliminate the context security risk. (dev.to)
155. OpenSEO 在 GitHub 上獲得了 1.7k 個星標。我只花了 0 美元就實現了同樣的功能。 OpenSEO Has 1.7k GitHub Stars. I Built the Same Thing for 0. (dev.to)
156. 通過聊天功能,創建並安排您專屬的Hacker News郵件摘要吧! Chat to build and schedule your own personal Hacker News email digest! (dev.to)
159. 構建“Sweets Vault”——一款集成物理硬件的多模態Gemini代理 Building "Sweets Vault" - a multimodal Gemini Agent with physical hardware integration (dev.to)
160. 更大的AI模型並不一定更好。以下是實際選擇的方法。 Bigger AI models aren''t always better. Here''s how to actually choose. (dev.to)
163. #100DaysOfCode 第99天 — DevCollab:部署 Next.js 並上線 Day 99 of #100DaysOfCode — DevCollab: Deploying Next.js and Going Live (dev.to)
164. 您的軟件包比《雷神之錘》大4000倍。通過9個步驟的審核即可解決此問題。 Your bundle is 4000x bigger than Quake. The 9-step audit that fixes it. (dev.to)
167. 我讓 Cursor 重命名了一個函數。它發送了 8,400 個代幣。我確認了一下。 I asked Cursor to rename a function. It sent 8,400 tokens. I checked. (dev.to)
168. 人工智能可以編寫代碼,但它仍然會忽略那些關鍵的決策。 AI Can Write the Code. It Still Forgets the Decisions That Matter. (dev.to)
169. 人工智能並沒有讓軟件工程變得更簡單,反而讓其中的難點變得更加棘手。 AI Didn''t Make Software Engineering Easier. It Made the Hard Parts Harder. (dev.to)
170. 全新的 AWS 代理工具包包含 20 多種代理技能,但如果沒有這個文件,您的代理可能永遠無法加載它們 The new Agent Toolkit for AWS includes 20 agent skills, but your agent might never load them without this one file (dev.to)
171. 我如何藉助人工智能助手在4天內完成整個產品的文檔編寫 How I Documented an Entire Product in 4 Days with an AI Agent (dev.to)
172. 使用 Veo 3.1 和 NanoBanana 2 製作完美正方形 AI 視頻 Hacking perfectly square AI videos with Veo 3.1 and NanoBanana 2 (dev.to)
173. PHP 與 Node.js 對比,Next.js 與 Angular 對比:該學什麼 PHP vs Node.js & Next.js vs Angular: What to Learn (dev.to)
174. 老舊電腦 vs 新型AI:2015年的臺式機真的能運行Gemma 4嗎?(2B vs 4B 性能測試) Old PC vs New AI: Can a 2015 Desktop Actually Run Gemma 4? (2B vs 4B Benchmark) (dev.to)
177. 我的 GitHub 墳場裡有 27 個已廢棄的項目。以下是關於原因的殘酷真相。 My GitHub Graveyard has 27 dead projects. Here is the brutal truth about why. (dev.to)
178. 本地優先的人工智能實踐範例:Gemma 4 E2B 與“思考模式”如何賦能 DiagramFlowAI Local-First AI Done Right: How Gemma 4 E2B and ''Thinking Mode'' Powered DiagramFlowAI (dev.to)
180. 職業倦怠的真實感受(而非Instagram上所描述的那樣) What Burnout Actually Feels Like (Not What Instagram Tells You) (dev.to)
181. 從第600萬名到第2.6萬名:1.5年、1040道LeetCode題目,以及一個改變一切的驚喜包裹 From Rank 6,000,000 to 26,000: 1.5 Years, 1040 LeetCode Problems, and a Surprise Package That Changed Everything (dev.to)
182. React 過於複雜:為何 Python HTMX 將在 2026 年佔據主導地位 React is Overkill: Why Python HTMX is Dominating in 2026 (dev.to)
186. Open Vibe——藉助人工智能發佈您的SaaS產品,暢通無阻。 Open Vibe -- Ship your SaaS with AI. Without getting stuck. (dev.to)
188. 我不再抗拒 React 服務器組件了——這才是最終讓我接受它的原因 I Stopped Fighting React Server Components — Here''s What Finally Made It (dev.to)
190. “見效快”背後的隱性代價:為何速效方案會損害長期速度 The Hidden Cost of "It Works": Why Quick Fixes Kill Long-Term Speed (dev.to)
191. 《提示工程師生存指南:AI無法取代的技能》 The Prompt Engineer''s Survival Guide: Skills That AI Can''t Replace (dev.to)
192. 我正準備重寫我的聊天路由器。結果發現,問題出在提示信息裡的兩行代碼上。 I Was About to Rewrite My Chat Router. The Bug Was Two Lines in a Prompt. (dev.to)
193. 您的 AWS 賬單在誤導您——它顯示的是服務,而非功能 Your AWS bill is lying to you — it shows services, not features (dev.to)
195. 使用 Docker Model Runner 免費在本地運行 Claude Code Run Claude Code Locally for Free with Docker Model Runner (dev.to)
196. 我測試了PaioClaw——當我將其推向極限時發生了什麼 I Tested PaioClaw — Here''s What Happened When I Pushed It to Its Limits (dev.to)
199. 我如何不再為後院的亂象感到絕望,並開啟了一個AI副業項目 How I Stopped Despairing Over the Backyard Mess and Started an AI Side Project (dev.to)
200. 我在11.8萬顆真實恆星中定位了Gemma 4——它能做什麼 I Grounded Gemma 4 in 118,000 Real Stars — Here''s What It Can Do (dev.to)
202. 如何保障生產環境中AI代理的安全:MCP的正確之處(及其不足) How to Secure AI Agents in Production: What MCP Gets Right (and What It Doesn’t) (dev.to)
205. 我用GTX 1650測試了所有Gemma 4型號。以下是實際測試結果。 I Tested Every Gemma 4 Model on a GTX 1650. Here''s What Actually Happened. (dev.to)
208. 使用 Gemma 26B MoE、.NET 8、Python 和 React 構建人工智能驅動的 ERP 系統 Building an AI-Powered ERP System with Gemma 26B MoE, .NET 8, Python & React (dev.to)
210. 當你第一次看到人工智能代理進行購物時,你會產生一種難以言喻的感覺。 The first time you watch an AI agent buy something, you will feel something you cannot name. (dev.to)
211. 在生產環境中使用 InversifyJS 三年後,我已經受夠了,於是我開發了一個更好的依賴注入容器 I was sick of InversifyJS after 3 years in production, so I built a better DI container (dev.to)
214. 作為一名MCA三年級學生,我是如何入選2026年穀歌夏季編程大賽(GSoC)的 How I Got Into Google Summer of Code (GSoC) 2026 as a Tier-3 MCA Student (dev.to)
217. 別再手動繪製骨架了。讓您的 UI 像魔法一樣自動生成骨架。 Stop hand-drawing skeletons. Let your UI trace itself magically. (dev.to)
218. @supports 謊言:當 CSS 說“是”,瀏覽器卻說“哈哈,才怪” @supports Lies: When CSS Says ''Yes'' but Browsers Say ''LOL No'' (dev.to)
220. 如何找到規劃器從未選中的 Postgres 索引(我在 51 箇中發現了 20 個) How to Find the Postgres Indexes Your Planner Never Picks (I Found 20 of 51) (dev.to)
221. Python 的 GIL 究竟是如何工作的(以及何時會給你帶來麻煩) How Python''s GIL actually works (and when it bites you) (dev.to)
222. 我開發了一個 Ruby gem,這樣我就不用再眯著眼睛看哈希轉儲了 I built a Ruby gem so I don''t have to squint at hash dumps anymore (dev.to)
223. 每個開發者的 Git 日誌都是一處犯罪現場——七步調查法 Every Developer''s Git Log is a Crime Scene - A 7-Stage Investigation (dev.to)
224. 永不停歇的本地模型:Gemma 4 與 MTP 作為馬拉松引擎 The Local Model That Doesn''t Sleep: Gemma 4 MTP as a Marathon Engine (dev.to)
226. 使用 Terraform 和 Cloud Run 部署多代理系統 Deploying a Multi-Agent System with Terraform and Cloud Run (dev.to)
228. [GCP 實踐][BwAI] 人工智能驅動的開發:使用 Gemini CLI 快速部署 LINE 機器人云備份工具 [GCP Practice][BwAI] AI-Powered Development: Quickly Deploy a LINE Bot Cloud Backup Tool with Gemini CLI (dev.to)
230. 為什麼我不讓 AI 處理我的滾動動畫:Astro、React 和 TypeScript 架構 Why I Didn’t Let AI Handle My Scroll Animation: Astro, React, and TypeScript Architecture (dev.to)
231. 黑客馬拉松如何教會新手開發者那些一年教程也無法傳授的知識 How a Hackathon Will Teach a New Developer What a Year of Tutorials Can''t (dev.to)
237. 我用 TypeScript 編寫了一個僅 200 行代碼的 AI 路由器。我的月賬單減少了 41%。 I built a 200 line AI router in TypeScript. My monthly bill dropped 41%. (dev.to)
239. 我用75美元的樹莓派取代了500美元的顯卡:Gemma 4如何讓計算機視覺成本降低10倍 I Replaced My 500 GPU with a 75 Raspberry Pi: How Gemma 4 Makes Computer Vision 10x Cheaper (dev.to)
243. 祝賀 Google Cloud NEXT ''26 寫作挑戰賽的獲獎者! Congrats to the Google Cloud NEXT ''26 Writing Challenge Winners! (dev.to)
245. Amazon Bedrock AgentCore Harness 負責運行您的代理。ShapeV2 則控制其被允許執行的操作 Amazon Bedrock AgentCore Harness runs your agent. ShapeV2 controls what it''s allowed to do (dev.to)
251. 加入“Gemma 4 挑戰賽”:總獎金 3,000 美元,將有十位獲獎者! Join the Gemma 4 Challenge: 3,000 prize pool for TEN winners! (dev.to)
254. 請停止這樣使用 useEffect:5 種正在悄無聲息地破壞你的 React 應用的模式 Stop Using useEffect Like This: 5 Patterns That Are Silently Breaking Your React App (dev.to)
255. 我們將全力支持您(AI Avatar v7:姿勢捕捉及其他功能(VS Code 和 Chrome 擴展程序)) We''ll Support You with All Our Might (AI Avatar v7: Pose Capture and More (VS Code and Chrome Extension)) (dev.to)
259. 人工智能到底是什麼?(我休息了一段時間,結果不得不重新學習一切) What Even Is AI? (I Took a Break & Had to Relearn Everything) (dev.to)
261. 基於 Gemini API 文件搜索工具的多模態 RAG:開發者指南 Multimodal RAG with the Gemini API File Search Tool: A Developer Guide (dev.to)
262. 面向人工智能編程時代的VR編程——同時監控5個AI代理 VR Coding for the AI Coding Era - Monitoring 5 AI Agents at Once (dev.to)
263. 使用 Angular 和 Signals 構建流式 Gemini 聊天應用——然後將其部署到 Cloud Run Build a Streaming Gemini Chat in Angular with Signals — Then Ship It on Cloud Run (dev.to)
264. 開發阿茲拉:別讓她發現你:我的遊戲開發歷程中的啟示 Working on Azirah: Don’t Let Her See You: Lessons from My Game Development Journey (dev.to)
266. 我分別在文檔、PDF 和代碼上測試了分塊處理。結果每次都不一樣。 I Tested Chunking on Docs, PDFs, and Code. The Winner Changed Every Time. (dev.to)
267. 2026年真實存在的6款代理網關平臺(及其優勢) 6 Agent Gateway Platforms That Actually Exist in 2026 (And What They''re Good For) (dev.to)
268. 大規模管理 150 多種 AI 代理技能——哪些出了問題,我又構建了什麼 Managing 150 AI Agent Skills at Scale — What Broke, What I Built (dev.to)
269. 我們發佈的代碼比以往任何時候都多,但我們對其中內容的理解卻越來越少。 We''re Shipping More Code Than Ever. We Understand Less of It. (dev.to)
270. 如何在 Cloud Run 上構建自定義 AI 質量檢查(從零開始到投入生產) How to Build a Custom AI Quality Gate on Cloud Run (From Zero to Production) (dev.to)
271. [Google Cloud Next ''26 回顧 #3] Anthropic 對“後軟件時代”的展望 [Google Cloud Next ''26 Recap #3] Anthropic''s Vision for "After Software" (dev.to)
272. 一位領英招聘人員向我發送了偽裝成“面試前代碼審查”的惡意軟件 A LinkedIn Recruiter Sent Me Malware Disguised as a "Pre-Interview Code Review" (dev.to)
273. 將 pytest 風格的測試環境引入 Ruby,實現更智能的瀏覽器測試 Introducing pytest-style fixtures into Ruby for smarter browser testing (dev.to)
275. 我花了3天時間開發了一個移動應用。最難的部分是保持其網絡連接。 I Built a Mobile App in 3 Days. The Hard Part Was Keeping It Connected. (dev.to)
276. AI 代理與代碼漏洞:Anthropic Mythos 究竟是大事一樁,還是危言聳聽? AI Agents vs Code Vulnerabilities: Was Anthropic Mythos a Big Deal or Fear-mongering? (dev.to)
280. 我開發了一款無需註冊即可使用的免費發票生成器、簡歷生成器和求職信生成器 I Built a Free Invoice Generator, Resume Builder, and Cover Letter Generator That Don''t Require Signup (dev.to)
283. 我如何用 Python 構建了一個離線 AI 助手——不依賴 OpenAI、LangChain 及任何其他依賴項 How I Built an Offline AI Assistant in Python - No OpenAI, No LangChain, No Dependencies (dev.to)
284. AI 刪除了我的測試,還說“所有測試均通過”——將“typia”從 TypeScript 移植到 Go 時的一段恐怖經歷 AI Deleted My Tests and Said ''All Tests Pass'' — A Horror Story from Porting ''typia'' from TypeScript to Go (dev.to)
286. 我開發了一款能夠檢測多個搜索引擎中SEO中毒現象的工具 I Built a Tool That Detects SEO Poisoning Across Multiple Search Engines (dev.to)
289. 我那位法學碩士助手的最新流行語是,在回覆開頭總愛說“坦率地說”。聽著真讓人不舒服。 My LLM assistant''s new buzzword is starting responses with "be completely candid". Very grating. (dev.to)
290. 我用JAX重構了Karpathy的NanoChat。以下是XLA做對的地方,以及它徹底搞錯的地方。 I Rebuilt Karpathy''s NanoChat in JAX. Here''s What XLA Gets Right and What It Gets Dead Wrong. (dev.to)
291. GitHub 搞砸了 Git:那個悄無聲息刪除了你代碼的合併隊列漏洞 GitHub Broke Git: The Merge Queue Bug That Silently Deleted Your Code (dev.to)
292. 我是如何構建 TypeScript 中最快的顏色處理庫的,以及我學到的優化技巧 How I built the fastest color manipulation library in TypeScript and the optimization techniques I learned (dev.to)
295. 函數調用框架 2:CoT 合規率從 9.91% 提升至 100% Function Calling Harness 2: CoT Compliance from 9.91% to 100% (dev.to)
297. 《AI Harness:為何你的AI編程助手只能像你放置它的代碼倉庫那樣聰明》 The AI Harness: why your AI coding agent is only as smart as the repo you put it in (dev.to)