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    <title>Ahmed Khemissa Blog</title>
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    <description>Technical articles on AI/ML, LLMs, and software engineering.</description>
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      <title>Optimizing React Performance with Next.js and Rust</title>
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      <description>Learn how to improve React application performance using Next.js and Rust. This guide covers optimization techniques and best practices for building high-performance React applications.</description>
      <pubDate>Fri, 10 Jul 2026 00:00:00 GMT</pubDate>
      <category>React</category>
      <category>Next.js</category>
      <category>Rust</category>
      <category>Performance Optimization</category>
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      <title>Building Scalable MLOps Pipelines with FastAPI and Docker</title>
      <link>https://ahmedkhemissa.tech/blog/building-scalable-mlops-pipelines-with-fastapi-and-docker</link>
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      <description>Learn how to deploy machine learning models using FastAPI and Docker, focusing on scalability and maintainability. This post covers the design of MLOps pipelines and best practices for model deployment.</description>
      <pubDate>Thu, 09 Jul 2026 00:00:00 GMT</pubDate>
      <category>MLOps</category>
      <category>FastAPI</category>
      <category>Docker</category>
      <category>Model Deployment</category>
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    <item>
      <title>Fine-Tuning LLMs on a Budget: A Practical Guide</title>
      <link>https://ahmedkhemissa.tech/blog/fine-tuning-llms-on-a-budget</link>
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      <description>How to fine-tune large language models without a GPU cluster, using LoRA, quantization, and a single consumer GPU. A hands-on walkthrough with code.</description>
      <pubDate>Wed, 08 Jul 2026 00:00:00 GMT</pubDate>
      <category>LLM</category>
      <category>Python</category>
      <category>Machine Learning</category>
      <category>PyTorch</category>
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      <title>Prompt Engineering Patterns That Actually Work</title>
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      <description>Beyond 'be concise', the prompt patterns I reach for in production LLM apps: few-shot scaffolding, structured output, and self-checking chains.</description>
      <pubDate>Tue, 07 Jul 2026 00:00:00 GMT</pubDate>
      <category>LLM</category>
      <category>Prompt Engineering</category>
      <category>AI</category>
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