<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Vibe Coding on My Space</title><link>https://famer.me/tags/Vibe-Coding/</link><description>Recent content in Vibe Coding on My Space</description><generator>Hugo</generator><language>en</language><lastBuildDate>Fri, 06 Feb 2026 13:44:21 +0800</lastBuildDate><atom:link href="https://famer.me/tags/Vibe-Coding/index.xml" rel="self" type="application/rss+xml"/><item><title>Ming's Spell Compendium #1 -- One Year of Vibe Coding: A Cold Hard Look</title><link>https://famer.me/2026/02/06/vibe-coding-one-year-reflection-en/</link><pubDate>Fri, 06 Feb 2026 13:44:21 +0800</pubDate><guid>https://famer.me/2026/02/06/vibe-coding-one-year-reflection-en/</guid><description>&lt;blockquote&gt;
&lt;p&gt;&lt;em&gt;This is a cultural adaptation — not a literal translation — of the &lt;a href="https://famer.me/2026/02/06/vibe-coding-one-year-reflection/"&gt;original Chinese article&lt;/a&gt;. Some Chinese cultural references have been swapped for Western equivalents that hit the same emotional note.&lt;/em&gt;&lt;/p&gt;
&lt;/blockquote&gt;
&lt;h1 id="foreword"&gt;Foreword&lt;/h1&gt;
&lt;p&gt;Over the past year I&amp;rsquo;ve burned through more than $10,000 in API tokens across Google, Anthropic, and OpenAI. So everything in this article is based on hands-on experience with the strongest models available — Opus 4.6, Codex-5.3-xhigh, Gemini 3 Pro — used without budget constraints.&lt;/p&gt;</description></item><item><title>明系魔法吟唱之1 -- Vibe Coding 一年实践后的冷思考</title><link>https://famer.me/2026/02/06/vibe-coding-one-year-reflection/</link><pubDate>Fri, 06 Feb 2026 13:44:21 +0800</pubDate><guid>https://famer.me/2026/02/06/vibe-coding-one-year-reflection/</guid><description>&lt;blockquote&gt;
&lt;p&gt;&lt;strong&gt;英文文化适配版：&lt;/strong&gt; &lt;a href="https://famer.me/2026/02/06/vibe-coding-one-year-reflection-en/"&gt;One Year of Vibe Coding: A Cold Hard Look (English cultural adaptation)&lt;/a&gt;&lt;/p&gt;
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&lt;h1 id="前言"&gt;前言&lt;/h1&gt;
&lt;p&gt;最近一年我在 Google/Anthropic/OpenAI 三家烧了超过 1 万美金的 token 账单。所以本文内容基于 opus4.6、codex-5.3-xhigh、gemini3-pro 等最强模型不限量使用所表现出来的编码能力进行评价。&lt;/p&gt;</description></item></channel></rss>