<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Durable on FindPicked</title><link>https://findpicked.com/tags/durable/</link><description>Recent content in Durable on FindPicked</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 16 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://findpicked.com/tags/durable/index.xml" rel="self" type="application/rss+xml"/><item><title>Architecting Durable AI Agents: Mastering Context &amp; State with Model Context Protocol</title><link>https://findpicked.com/blog/mcp-agent-context-architecture/</link><pubDate>Thu, 16 Jul 2026 00:00:00 +0000</pubDate><guid>https://findpicked.com/blog/mcp-agent-context-architecture/</guid><description>&lt;p&gt;The promise of AI agents—software that uses large language models (LLMs) to plan and execute multi-step tasks with tools—hinges on their ability to maintain context and state reliably across complex, multi-turn interactions. Without robust mechanisms for managing this information, agents can become brittle, forgetful, and prone to failure, especially in production environments. The Model Context Protocol (MCP) emerges as a critical open standard addressing these challenges, providing a standardized, robust framework for durable and production-ready AI agent systems.&lt;/p&gt;</description></item><item><title>Managing Context Rot: Durable AI Agent Sessions</title><link>https://findpicked.com/blog/managing-ai-agent-context-decay/</link><pubDate>Tue, 14 Jul 2026 00:00:00 +0000</pubDate><guid>https://findpicked.com/blog/managing-ai-agent-context-decay/</guid><description>&lt;p&gt;In the rapidly evolving landscape of &lt;strong&gt;AI agents&lt;/strong&gt;, maintaining consistent and reliable performance across extended, multi-step tasks presents a significant challenge. One of the most critical issues developers face is &lt;strong&gt;context rot&lt;/strong&gt;, a phenomenon that degrades an agent&amp;rsquo;s effectiveness over time as its internal understanding becomes cluttered or loses vital information. This article demystifies context rot, explores its root causes, and provides practical, durable strategies for developers to manage and mitigate it, ensuring your &lt;strong&gt;AI agents&lt;/strong&gt; remain sharp and effective throughout their operational lifecycles.&lt;/p&gt;</description></item></channel></rss>