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    <title>ReAct on Cognaptus</title>
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    <description>Recent content in ReAct on Cognaptus</description>
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      <title>Think, Then Do: Why ReAct Turned LLMs into Real Agents</title>
      <link>https://cognaptus.com/blog/2026-03-04-think-then-do-why-react-turned-llms-into-real-agents/</link>
      <pubDate>Wed, 04 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-03-04-think-then-do-why-react-turned-llms-into-real-agents/</guid>
      <description>A mechanism-first reading of ReAct, the prompting framework that turned language models from passive answer generators into inspectable tool-using agents.</description>
    </item>
    <item>
      <title>Consistency Is Not a Coincidence: When LLM Agents Disagree With Themselves</title>
      <link>https://cognaptus.com/blog/2026-02-14-consistency-is-not-a-coincidence-when-llm-agents-disagree-with-themselves/</link>
      <pubDate>Sat, 14 Feb 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-02-14-consistency-is-not-a-coincidence-when-llm-agents-disagree-with-themselves/</guid>
      <description>A paper on behavioral consistency shows why repeated agent trajectories can become an early warning signal for enterprise AI reliability.</description>
    </item>
    <item>
      <title>Agentic Systems Need Architecture, Not Vibes</title>
      <link>https://cognaptus.com/blog/2026-02-02-agentic-systems-need-architecture-not-vibes/</link>
      <pubDate>Mon, 02 Feb 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-02-02-agentic-systems-need-architecture-not-vibes/</guid>
      <description>A mechanism-first reading of why reliable AI agents need subsystem architecture, reusable design patterns, and clearer diagnosis than another enthusiastic list of agent tricks.</description>
    </item>
    <item>
      <title>Beyond Utility: When LLM Agents Start Dreaming Their Own Tasks</title>
      <link>https://cognaptus.com/blog/2025-10-23-beyond-utility-when-llm-agents-start-dreaming-their-own-tasks/</link>
      <pubDate>Thu, 23 Oct 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-10-23-beyond-utility-when-llm-agents-start-dreaming-their-own-tasks/</guid>
      <description>A mechanism-first look at how open-ended LLM agents move from task execution to task generation—and why that is not the same as autonomy.</description>
    </item>
    <item>
      <title>Org Charts for Robots: What AgentArch Really Tells Us About Enterprise AI</title>
      <link>https://cognaptus.com/blog/2025-09-20-org-charts-for-robots-what-agentarch-really-tells-us-about-enterprise-ai/</link>
      <pubDate>Sat, 20 Sep 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-09-20-org-charts-for-robots-what-agentarch-really-tells-us-about-enterprise-ai/</guid>
      <description>ServiceNow’s AgentArch benchmark turns agent architecture from vendor folklore into an empirical design problem for enterprise automation.</description>
    </item>
    <item>
      <title>ReAct Without the Chaos: AgentScope 1.0 Turns Tools into Strategy</title>
      <link>https://cognaptus.com/blog/2025-08-25-react-without-the-chaos-agentscope-10-turns-tools-into-strategy/</link>
      <pubDate>Mon, 25 Aug 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-08-25-react-without-the-chaos-agentscope-10-turns-tools-into-strategy/</guid>
      <description>AgentScope 1.0 shows how tool-using agents become more operationally credible when ReAct is wrapped in disciplined abstractions, tracing, evaluation, and runtime isolation.</description>
    </item>
    <item>
      <title>Who Sees What, Who Pays the Cost? Teaching Agents to See Through Others’ Eyes</title>
      <link>https://cognaptus.com/blog/2025-08-23-who-sees-what-who-pays-the-cost-teaching-agents-to-see-through-others-eyes/</link>
      <pubDate>Sat, 23 Aug 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-08-23-who-sees-what-who-pays-the-cost-teaching-agents-to-see-through-others-eyes/</guid>
      <description>Structured planner-derived examples help LLM agents with simple shared-visibility filtering, but the harder business problem is belief tracking and pricing the cost of information.</description>
    </item>
    <item>
      <title>Plans Before Action: What XAgent Can Learn from Pre-Act&#39;s Cognitive Blueprint</title>
      <link>https://cognaptus.com/blog/2025-05-18-plans-before-action-what-xagent-can-learn-from-preacts-cognitive-blueprint/</link>
      <pubDate>Sun, 18 May 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-05-18-plans-before-action-what-xagent-can-learn-from-preacts-cognitive-blueprint/</guid>
      <description>Pre-Act shows that enterprise agents need explicit planning state, not just one-step tool reasoning, if they are expected to survive real workflows.</description>
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