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    <title>DEV Community: Abhishek Roy</title>
    <description>The latest articles on DEV Community by Abhishek Roy (@abhishek_roy_789b16fc14d8).</description>
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      <title>Building Task Optimal mixture of experts</title>
      <dc:creator>Abhishek Roy</dc:creator>
      <pubDate>Fri, 31 Jul 2026 11:54:49 +0000</pubDate>
      <link>https://dev.to/abhishek_roy_789b16fc14d8/building-task-optimal-mixture-of-experts-2man</link>
      <guid>https://dev.to/abhishek_roy_789b16fc14d8/building-task-optimal-mixture-of-experts-2man</guid>
      <description>&lt;p&gt;My name is Abhishek Roy, based in Kishanganj, Bihar. When building local AI agents, one major problem stands out: How do you route low-complexity prompts to fast, cheap models while preserving deep multi-pass reasoning for complex engineering prompts?&lt;/p&gt;

&lt;p&gt;In this article, I’m walking through the design of TO-MoE, a local terminal-based Python prototype built on LangGraph.&lt;/p&gt;

&lt;p&gt;Key Technical Sections:&lt;/p&gt;

&lt;p&gt;Why Keyword Routing Fails (RFC Trap A vs Trap B)&lt;/p&gt;

&lt;p&gt;Semantic Coordinate Routing with Cosine Similarity&lt;/p&gt;

&lt;p&gt;Implementing Action Verb Dominance (AVD) &amp;amp; 1-Token Jury&lt;/p&gt;

&lt;p&gt;State Protection: Silent Escalation &amp;amp; Quarantine Gates&lt;/p&gt;

&lt;p&gt;Memory Architecture: ChromaDB Vector Store + Context-Assist Semantic Cache&lt;/p&gt;

&lt;p&gt;Benchmark Results &amp;amp; Lessons Learned&lt;/p&gt;

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      <category>ai</category>
      <category>architecture</category>
      <category>machinelearning</category>
      <category>python</category>
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