<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Prompting on Coursiv Blog</title><link>https://coursiv.io/blog/tags/prompting</link><description>Recent content in Prompting on Coursiv Blog</description><generator>Hugo -- 0.147.0</generator><language>en-US</language><lastBuildDate>Fri, 24 Jul 2026 12:00:00 +0500</lastBuildDate><atom:link href="https://coursiv.io/blog/tags/prompting/index.xml" rel="self" type="application/rss+xml"/><item><title>AI Tools Every Beginner Should Try First</title><link>https://coursiv.io/blog/ai-tools-every-beginner-should-try-first</link><pubDate>Fri, 24 Jul 2026 12:00:00 +0500</pubDate><guid>https://coursiv.io/blog/ai-tools-every-beginner-should-try-first</guid><description>A beginner&amp;#39;s guide to the first AI tools worth trying, with a decision framework, a comparison table, and the common mistakes to avoid.</description></item><item><title>Are AI Skills Worth Learning? Insights and Recommendations</title><link>https://coursiv.io/blog/are-ai-skills-worth-learning</link><pubDate>Fri, 24 Jul 2026 12:00:00 +0500</pubDate><guid>https://coursiv.io/blog/are-ai-skills-worth-learning</guid><description>An honest look at whether AI skills are worth learning, where demand actually is, which skills matter most, and how to get started without a technical background.</description></item><item><title>What Is Generative AI in Simple Terms?</title><link>https://coursiv.io/blog/what-is-generative-ai-in-simple-terms</link><pubDate>Fri, 24 Jul 2026 12:00:00 +0500</pubDate><guid>https://coursiv.io/blog/what-is-generative-ai-in-simple-terms</guid><description>A plain-English explanation of generative AI – how it works, where it&amp;#39;s used, its benefits and limits, how it differs from traditional AI, and how to start.</description></item><item><title>Chain-of-Thought Prompting</title><link>https://coursiv.io/blog/glossary/chain-of-thought-prompting</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://coursiv.io/blog/glossary/chain-of-thought-prompting</guid><description>Asking the model to work through its reasoning step by step before answering.</description></item><item><title>Context Engineering</title><link>https://coursiv.io/blog/glossary/context-engineering</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://coursiv.io/blog/glossary/context-engineering</guid><description>Deciding what information goes into the context window, in what order, and what gets left out.</description></item><item><title>Few-Shot Prompting</title><link>https://coursiv.io/blog/glossary/few-shot-prompting</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://coursiv.io/blog/glossary/few-shot-prompting</guid><description>Including several examples in the prompt so the model infers the pattern you want.</description></item><item><title>Meta-Prompting</title><link>https://coursiv.io/blog/glossary/meta-prompting</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://coursiv.io/blog/glossary/meta-prompting</guid><description>Using a model to write, critique, or improve prompts for another model.</description></item><item><title>Negative Prompt</title><link>https://coursiv.io/blog/glossary/negative-prompt</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://coursiv.io/blog/glossary/negative-prompt</guid><description>In image generation, a list of things you want kept out of the result.</description></item><item><title>One-Shot Prompting</title><link>https://coursiv.io/blog/glossary/one-shot-prompting</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://coursiv.io/blog/glossary/one-shot-prompting</guid><description>Giving exactly one worked example alongside the instruction.</description></item><item><title>Prompt</title><link>https://coursiv.io/blog/glossary/prompt</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://coursiv.io/blog/glossary/prompt</guid><description>The input you give a model — instructions, context, examples, and question, all as text.</description></item><item><title>Prompt Engineering</title><link>https://coursiv.io/blog/glossary/prompt-engineering</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://coursiv.io/blog/glossary/prompt-engineering</guid><description>Designing and iterating on prompts to get reliable output — closer to spec-writing than to magic words.</description></item><item><title>Prompt Template</title><link>https://coursiv.io/blog/glossary/prompt-template</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://coursiv.io/blog/glossary/prompt-template</guid><description>A reusable prompt with variable slots, so a working prompt becomes a repeatable asset.</description></item><item><title>Role Prompting</title><link>https://coursiv.io/blog/glossary/role-prompting</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://coursiv.io/blog/glossary/role-prompting</guid><description>Assigning the model a role to shape its vocabulary, depth, and framing.</description></item><item><title>Structured Output</title><link>https://coursiv.io/blog/glossary/structured-output</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://coursiv.io/blog/glossary/structured-output</guid><description>Forcing the model to return data in a fixed schema so downstream code can parse it.</description></item><item><title>System Prompt</title><link>https://coursiv.io/blog/glossary/system-prompt</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://coursiv.io/blog/glossary/system-prompt</guid><description>Standing instructions that set a model&amp;#39;s role, rules, and tone for an entire conversation.</description></item><item><title>Zero-Shot Prompting</title><link>https://coursiv.io/blog/glossary/zero-shot-prompting</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://coursiv.io/blog/glossary/zero-shot-prompting</guid><description>Asking the model to do a task with no examples — just the instruction.</description></item></channel></rss>