<?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>Architecture on Vinh Thang's AI Tech Notes</title><link>https://vinhthang.dev/categories/architecture/</link><description>Recent content in Architecture on Vinh Thang's AI Tech Notes</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 03 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://vinhthang.dev/categories/architecture/index.xml" rel="self" type="application/rss+xml"/><item><title>Under the Hood: How the Antigravity Attention Guard Plugin Enforces Deterministic Agent Governance</title><link>https://vinhthang.dev/posts/antigravity-attention-plugin/</link><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><guid>https://vinhthang.dev/posts/antigravity-attention-plugin/</guid><description>&lt;p&gt;In our previous discussions on autonomous engineering, we explored the phenomenon of &lt;strong&gt;Attention Dilution&lt;/strong&gt;—the silent degradation of instruction-following fidelity as context windows swell past tens of thousands of tokens. While modern frontier models boast context windows of 1M+ tokens, attention mechanisms remain vulnerable to informational entropy. As terminal logs, stack traces, and code diffs accumulate, system prompt constraints drift out of the model&amp;rsquo;s active attention focus.&lt;/p&gt;
&lt;p&gt;When left unchecked, agents exhibit architectural amnesia: they bypass project-level Architecture Decision Records (ADRs), run uncompressed shell commands that flood context, guess port allocations, or skip verification steps.&lt;/p&gt;</description></item><item><title>Attention Dilution: Why 1M-Token Context Windows Kill Strict Agent Behavior (And How We Fixed It)</title><link>https://vinhthang.dev/posts/attention-dilution-context-windows-agents/</link><pubDate>Tue, 01 Sep 2026 00:00:00 +0000</pubDate><guid>https://vinhthang.dev/posts/attention-dilution-context-windows-agents/</guid><description>&lt;p&gt;There is a pervasive myth in modern AI engineering: &lt;em&gt;“Just give the model a 1,000,000-token context window, paste all your enterprise governance rules in the system prompt, and let it build your system.”&lt;/em&gt;&lt;/p&gt;
&lt;p&gt;If you have built real-world autonomous coding agents operating inside complex cloud infrastructures, multi-module monorepos, or production Kubernetes clusters, you already know the harsh truth: massive context windows don&amp;rsquo;t make agents smarter; they make them amnesiac.&lt;/p&gt;
&lt;p&gt;As an agentic conversation unfolds—accumulating terminal outputs, stack traces, file diffs, and conversational turns—a subtle failure mode emerges: &lt;strong&gt;Attention Dilution&lt;/strong&gt;.&lt;/p&gt;</description></item><item><title>Open-Sourcing the Cure for Attention Dilution: The Antigravity Attention Guard Plugin</title><link>https://vinhthang.dev/posts/attention-guard-open-source-plugin/</link><pubDate>Tue, 01 Sep 2026 00:00:00 +0000</pubDate><guid>https://vinhthang.dev/posts/attention-guard-open-source-plugin/</guid><description>&lt;p&gt;In my &lt;a href="https://vinhthang.dev/posts/attention-dilution-context-windows-agents/"&gt;previous post&lt;/a&gt;, I detailed the mathematical realities of &amp;ldquo;Attention Dilution&amp;rdquo; in LLMs with massive context windows, and how we engineered deterministic lifecycle hooks to prevent autonomous agents from suffering architectural amnesia.&lt;/p&gt;
&lt;p&gt;Today, I am thrilled to announce that we have packaged that exact solution into a fully open-source, cross-platform &lt;strong&gt;Antigravity Plugin&lt;/strong&gt;.&lt;/p&gt;
&lt;p&gt;You can now instantly secure your own agents by cloning the &lt;a href="https://github.com/vinhthang/antigravity-attention-guard-plugin"&gt;Antigravity Attention Guard Plugin&lt;/a&gt; directly into your configuration.&lt;/p&gt;</description></item></channel></rss>