<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Prompt Templates on SoloSoft</title><link>https://www.solosoft.dev/tags/prompt-templates/</link><description>Recent content in Prompt Templates on SoloSoft</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Fri, 01 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://www.solosoft.dev/tags/prompt-templates/index.xml" rel="self" type="application/rss+xml"/><item><title>Prompt Poet: Character.AI's Open-Source Prompt Engineering Framework</title><link>https://www.solosoft.dev/post/prompt-poet-2026/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://www.solosoft.dev/post/prompt-poet-2026/</guid><description>&lt;p&gt;Prompt engineering has evolved from a niche skill into a critical discipline in AI application development. The difference between a good prompt and a great one can determine whether an LLM application delivers accurate, reliable results or produces inconsistent, error-prone output. &lt;strong&gt;Prompt Poet&lt;/strong&gt; by Character.AI brings engineering rigor to this process, providing a structured framework for designing, testing, and optimizing prompts at scale.&lt;/p&gt;
&lt;p&gt;Character.AI operates one of the world&amp;rsquo;s largest consumer AI platforms, serving millions of users daily across thousands of distinct AI characters. Managing prompts at this scale &amp;ndash; where each character has unique personality traits, knowledge boundaries, and interaction patterns &amp;ndash; requires tooling far beyond what simple text files or ad-hoc experimentation can provide. Prompt Poet grew out of this real-world need for systematic prompt management.&lt;/p&gt;</description></item></channel></rss>