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    <title>AiAgentNook — Guides to AI agents</title>
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    <description>AI agents from first principles: what they are, the types, how to evaluate them, and the build flow for shipping one.</description>
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    <lastBuildDate>Wed, 12 Aug 2026 12:00:00 +0800</lastBuildDate>

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      <title>What is an AI agent?</title>
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      <pubDate>Wed, 12 Aug 2026 09:00:00 +0800</pubDate>
      <description>A definition narrow enough to be useful: an AI agent is a model using tools in a loop it controls itself. What that means, and why autonomy is a cost, not a feature.</description>
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      <title>Types of AI agents</title>
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      <pubDate>Wed, 12 Aug 2026 09:10:00 +0800</pubDate>
      <description>The textbook taxonomy of AI agents and the workflow-versus-agent split practitioners actually use, plus the environments that shape coding, browser, and voice agents.</description>
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      <title>AI agent evaluation: how to know it actually works</title>
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      <pubDate>Wed, 12 Aug 2026 09:20:00 +0800</pubDate>
      <description>Task success rates, the public benchmarks (SWE-bench, GAIA, tau-bench, OSWorld), building your own eval suite, and what a success rate hides.</description>
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      <title>Build flow and sequence: shipping an AI agent in the right order</title>
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      <pubDate>Wed, 12 Aug 2026 09:30:00 +0800</pubDate>
      <description>The seven-step order of operations for shipping an AI agent — task, baseline, tools, loop, evals, guardrails, deploy — and why the sequence is the safety feature.</description>
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      <title>Agent memory: context windows, RAG, and long-term state</title>
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      <pubDate>Wed, 12 Aug 2026 09:40:00 +0800</pubDate>
      <description>The context window as working memory, retrieval-augmented generation for knowledge, external stores for long-term state, and when each earns its complexity.</description>
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      <title>Tool use and MCP: how agents touch the world</title>
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      <pubDate>Wed, 12 Aug 2026 09:50:00 +0800</pubDate>
      <description>Function calling, writing tool descriptions the model can actually use, and the Model Context Protocol — the open standard connecting agents to external systems.</description>
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      <title>Multi-agent systems: when one agent isn't enough</title>
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      <pubDate>Wed, 12 Aug 2026 10:00:00 +0800</pubDate>
      <description>The orchestrator–worker pattern, what parallel subagents buy you, the roughly 15× token cost, and the coordination failures nobody budgets for.</description>
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      <title>Agent failure modes: prompt injection, runaway loops, silent drift</title>
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      <pubDate>Wed, 12 Aug 2026 10:10:00 +0800</pubDate>
      <description>Documented AI agent failure modes — direct and indirect prompt injection, the lethal trifecta, runaway loops, and silent reliability drift — and the guardrail that answers each.</description>
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      <title>The cost of running agents</title>
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      <pubDate>Wed, 12 Aug 2026 10:20:00 +0800</pubDate>
      <description>Why agent token bills multiply with every loop iteration — about 4× a chat for one agent, 15× for multi-agent — the hidden costs, and the levers that control them.</description>
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      <title>Agent frameworks: build direct or adopt one?</title>
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      <pubDate>Wed, 12 Aug 2026 10:30:00 +0800</pubDate>
      <description>What LangGraph and the OpenAI Agents SDK actually add, what the abstraction layer costs you, and when a framework earns its place.</description>
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