<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Templates on SoloSoft</title><link>https://www.solosoft.dev/es/tags/templates/</link><description>Recent content in Templates on SoloSoft</description><generator>Hugo</generator><language>es-es</language><lastBuildDate>Fri, 01 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://www.solosoft.dev/es/tags/templates/index.xml" rel="self" type="application/rss+xml"/><item><title>LangGPT: Structured Prompt Engineering Framework</title><link>https://www.solosoft.dev/es/post/langgpt-prompts-2026/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://www.solosoft.dev/es/post/langgpt-prompts-2026/</guid><description>&lt;p&gt;Prompt engineering has evolved from an art into a discipline, but most practitioners still write prompts as unstructured natural language, relying on intuition rather than methodology. &lt;strong&gt;LangGPT&lt;/strong&gt; (langgptai/LangGPT on GitHub) brings structure, repeatability, and engineering rigor to prompt design by providing a comprehensive framework for creating, managing, and evaluating LLM prompts.&lt;/p&gt;
&lt;p&gt;Developed by the LangGPT AI team, this open-source project has gained significant traction among AI practitioners who recognize that high-quality prompts require the same systematic approach as high-quality code. LangGPT introduces a template-based system where prompts are composed of reusable sections &amp;ndash; role definitions, task descriptions, output constraints, examples, and reasoning instructions &amp;ndash; assembled using variables and hierarchical composition.&lt;/p&gt;</description></item></channel></rss>