<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>Software Engineer - Tag - OfferGoose</title><link>/tags/software-engineer/</link><description>Software Engineer - Tag - OfferGoose</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</copyright><lastBuildDate>Mon, 20 Jul 2026 11:23:07 +0800</lastBuildDate><atom:link href="/tags/software-engineer/" rel="self" type="application/rss+xml"/><item><title>Technical Interview Prep With AI: A Full-Stack Training System for Algorithms, System Design, and Behavioral Rounds</title><link>/post426/</link><pubDate>Mon, 20 Jul 2026 11:23:07 +0800</pubDate><author>OfferGoose</author><guid>/post426/</guid><description><![CDATA[<p>@[TOC]</p>
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<p>Technical interviews are the strangest beast in the hiring world. You need to nail three things simultaneously: raw coding ability, structured verbal communication, and interview psychology. Plenty of engineers grind 500 LeetCode problems and then fail the first round on &ldquo;Tell me about the hardest bug you ever tracked down.&rdquo;</p>
<p>This article follows the real training log of a backend engineer — let&rsquo;s call him Chen — as he builds a complete AI mock interview training system across all three technical interview modules over two weeks.</p>]]></description></item></channel></rss>