<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Openai-Prompt-Engineering on Ghafoor's Personal Blog</title><link>http://ghafoorsblog.com/series/openai-prompt-engineering/</link><description>Recent content in Openai-Prompt-Engineering on Ghafoor's Personal Blog</description><generator>Hugo</generator><language>en</language><managingEditor>noreply@example.com (AG Sayyed)</managingEditor><webMaster>noreply@example.com (AG Sayyed)</webMaster><copyright>Copyright © 2024-2026 AG Sayyed. All Rights Reserved.</copyright><lastBuildDate>Sat, 15 Nov 2025 17:39:51 +0000</lastBuildDate><atom:link href="http://ghafoorsblog.com/series/openai-prompt-engineering/index.xml" rel="self" type="application/rss+xml"/><item><title>Guidelines for Prompting</title><link>http://ghafoorsblog.com/courses/openai/openai-prompt-eng-developer/01-llms/01-module/003-guidelines/</link><pubDate>Thu, 12 Dec 2024 09:34:43 +0000</pubDate><author>noreply@example.com (AG Sayyed)</author><guid>http://ghafoorsblog.com/courses/openai/openai-prompt-eng-developer/01-llms/01-module/003-guidelines/</guid><description>&lt;p class="lead text-primary"&gt;
This guide outlines two key principles for writing effective prompts for large language models (LLMs). By following these guidelines, you can craft clear and structured prompts that help the model generate accurate and relevant responses.
&lt;/p&gt;
&lt;hr&gt;
&lt;h2 id="guidelines-for-prompting"&gt;Guidelines for Prompting&lt;/h2&gt;

 &lt;blockquote
 
 class="blockquote border-start ps-3 py-1 border-primary border-4"&gt;
 &lt;p&gt;&lt;strong&gt;Note&lt;/strong&gt;: These notes are based on the videos available on the &lt;a
 href="https://learn.deeplearning.ai/courses/chatgpt-prompt-eng/lesson/3/iterative"
 
 target="_blank" rel="noopener noreferrer"&gt;OpenAI platform&lt;/a&gt;.&lt;/p&gt;

 &lt;/blockquote&gt;
&lt;p&gt;This guide outlines two key principles for writing effective prompts for large language models (LLMs).&lt;/p&gt;</description></item><item><title>LLM Types</title><link>http://ghafoorsblog.com/courses/openai/openai-prompt-eng-developer/01-llms/01-module/001-llm-types/</link><pubDate>Thu, 12 Dec 2024 03:53:21 +0000</pubDate><author>noreply@example.com (AG Sayyed)</author><guid>http://ghafoorsblog.com/courses/openai/openai-prompt-eng-developer/01-llms/01-module/001-llm-types/</guid><description>&lt;p class="lead"&gt;
Large Language Models (LLMs) are categorized into three main types based on their training and functionality. Each type has unique characteristics and use cases. This document provides an overview of the three types of LLMs and their applications.
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&lt;h2 id="types-of-llms"&gt;Types of LLMs&lt;/h2&gt;
&lt;p&gt;There are three main types of LLMs:&lt;/p&gt;
&lt;ol&gt;
&lt;li&gt;&lt;strong&gt;Base LLM&lt;/strong&gt;&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Instruction-Tuned LLM&lt;/strong&gt;&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Instruction-and-Data-Tuned LLM&lt;/strong&gt;&lt;/li&gt;
&lt;/ol&gt;
&lt;h3 id="type-1-base-llm"&gt;Type 1: Base LLM&lt;/h3&gt;
&lt;p&gt;Base LLMs are the simplest form of LLMs. They predict the next word based on patterns in the training data.&lt;/p&gt;</description></item></channel></rss>