<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Mental-Models on Armstrong Yan</title><link>https://yanqian.github.io/tags/mental-models/</link><description>Recent content in Mental-Models on Armstrong Yan</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 23 May 2026 20:33:47 +0800</lastBuildDate><atom:link href="https://yanqian.github.io/tags/mental-models/index.xml" rel="self" type="application/rss+xml"/><item><title>AI-Native Software Engineering, Part 1: Mental Models in Agentic Coding</title><link>https://yanqian.github.io/posts/publish/agentic-coding-mental-models-and-the-new-depth-of-software-engineering/</link><pubDate>Sat, 23 May 2026 20:33:47 +0800</pubDate><guid>https://yanqian.github.io/posts/publish/agentic-coding-mental-models-and-the-new-depth-of-software-engineering/</guid><description>&lt;p>AI can generate code. Harnesses can validate behavior. But who builds understanding?&lt;/p>
&lt;p>This is Part 1 of the AI-Native Software Engineering series.&lt;/p>
&lt;p>The series asks a larger question:&lt;/p>
&lt;div class="highlight">&lt;pre tabindex="0" class="chroma">&lt;code class="language-text" data-lang="text">&lt;span class="line">&lt;span class="cl">When AI lowers the cost of implementation,
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="cl">what remains scarce in software engineering?
&lt;/span>&lt;/span>&lt;/code>&lt;/pre>&lt;/div>&lt;p>This article starts with the first scarce resource:&lt;/p>
&lt;div class="highlight">&lt;pre tabindex="0" class="chroma">&lt;code class="language-text" data-lang="text">&lt;span class="line">&lt;span class="cl">Understanding.
&lt;/span>&lt;/span>&lt;/code>&lt;/pre>&lt;/div>&lt;p>Over the past few months, I&amp;rsquo;ve been experimenting heavily with AI-assisted software development.&lt;/p>
&lt;p>Not autocomplete.&lt;/p>
&lt;p>Not AI as a coding copilot.&lt;/p></description></item></channel></rss>