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    <title>Ai Agents on Strathweb. A free flowing tech monologue.</title>
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    <description>Recent content in Ai Agents on Strathweb. A free flowing tech monologue.</description>
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      <title>LLM and SLM collaboration using the Minions pattern (with Phi-4-mini and Azure OpenAI)</title>
      <link>https://www.strathweb.com/2025/10/llm-and-slm-collaboration-using-the-minions-pattern/</link>
      <pubDate>Fri, 24 Oct 2025 07:06:14 +0000</pubDate>
      
      <guid>https://www.strathweb.com/2025/10/llm-and-slm-collaboration-using-the-minions-pattern/</guid>
      <description>&lt;p&gt;In this post, we&amp;rsquo;ll explore a novel approach to optimizing AI workflows by strategically combining large language models (LLMs) with small language models (SLMs) using the &amp;ldquo;Minions pattern.&amp;rdquo; This technique, described in the research paper &lt;a href=&#34;https://arxiv.org/abs/2502.15964&#34;&gt;&amp;ldquo;Minions: Cost-efficient Collaboration Between On-device and Cloud Language Models&amp;rdquo;&lt;/a&gt; by Narayan et al., addresses one of the most pressing challenges in AI application development - the cost of processing large amounts of data with expensive, cloud-based language models. If you&amp;rsquo;ve ever built an AI system that needs to analyze extensive documents or datasets, you&amp;rsquo;ve probably felt the frustration of watching your API costs skyrocket as you process more and more content.&lt;/p&gt;</description>
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      <title>RAG Agent with HyPE Pattern using Semantic Kernel</title>
      <link>https://www.strathweb.com/2025/07/rag-agent-with-hype-pattern-using-semantic-kernel/</link>
      <pubDate>Mon, 14 Jul 2025 07:06:14 +0000</pubDate>
      
      <guid>https://www.strathweb.com/2025/07/rag-agent-with-hype-pattern-using-semantic-kernel/</guid>
      <description>&lt;p&gt;In this post we will explore a novel approach to Retrieval-Augmented Generation (RAG) called &lt;a href=&#34;https://ssrn.com/abstract=5139335&#34;&gt;HyPE (Hypothetical Prompt Embeddings)&lt;/a&gt;, which I came across in a preprint paper recently. This technique tries to address one of the fundamental challenges in RAG systems: the semantic mismatch between user queries and document content. If you&amp;rsquo;ve ever built a RAG system, you&amp;rsquo;ve probably felt the frustration when your carefully crafted vector search returns seemingly irrelevant results. At least for me, it was always tremendously annoying when a simple question like &amp;ldquo;What is quantum entanglement?&amp;rdquo; wouldn&amp;rsquo;t reliably match a document section that clearly explains quantum entanglement.&lt;/p&gt;</description>
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      <title>AI Agents with OpenAPI Tools - Part 2: Azure AI Foundry</title>
      <link>https://www.strathweb.com/2025/06/ai-agents-with-openapi-tools-part-2-azure-ai-foundry/</link>
      <pubDate>Fri, 27 Jun 2025 07:06:14 +0000</pubDate>
      
      <guid>https://www.strathweb.com/2025/06/ai-agents-with-openapi-tools-part-2-azure-ai-foundry/</guid>
      <description>&lt;p&gt;In the &lt;a href=&#34;https://www.strathweb.com/2025/06/ai-agents-with-openapi-tools-part-1-semantic-kernel&#34;&gt;previous part&lt;/a&gt; of this series, we explored how to attach OpenAPI-based tools to a Semantic Kernel AI agent. In this part, we will look at another SDK for building AI Agents, Azure AI Foundry SDK, to create an agent that can also interact with OpenAPI-based tools.&lt;/p&gt;</description>
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    <item>
      <title>AI Agents with OpenAPI Tools - Part 1: Semantic Kernel</title>
      <link>https://www.strathweb.com/2025/06/ai-agents-with-openapi-tools-part-1-semantic-kernel/</link>
      <pubDate>Mon, 23 Jun 2025 07:06:14 +0000</pubDate>
      
      <guid>https://www.strathweb.com/2025/06/ai-agents-with-openapi-tools-part-1-semantic-kernel/</guid>
      <description>&lt;p&gt;Today we will kick off a short series on building AI agents which have access to OpenAPI tools. In this first part, we will focus on the Semantic Kernel, and in the second part, we will look at Azure AI Foundry.&lt;/p&gt;</description>
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