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    <title>llm on Oleksandr Kulbida</title>
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      <title>AI agents in practice: self-learning, knowledge bases, and why fewer agents is better</title>
      <link>https://okulbida.com/posts/ai-agents-knowledge-base-obsidian-local-llm/</link>
      <pubDate>Fri, 15 May 2026 00:00:00 +0200</pubDate>
      
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      <description>Building AI agents sounds fun until you actually build one. Then a different set of problems shows up — ones nobody wrote a blog post about yet.
This is a summary of a conversation between developers actively running agent systems in production or near-production. The topics: self-improvement conflicts with git, what to use for a knowledge base, Andrej Karpathy&amp;rsquo;s Obsidian approach, and why adding more agents rarely helps.
 The self-improvement problem One of the selling points of agents like Hermes is that they can self-reflect and improve — updating their own rules based on experience.</description>
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