Prompt engineering essentials: Getting better results from LLMs | Tutorial

Video Description

Struggling to get useful responses from AI models? This prompt engineering tutorial covers everything developers need to know for effective LLM interactions. Learn how to think about context and tokens, structure your requests, and overcome common prompt issues. Perfect for anyone looking to leverage AI more effectively in their development workflow. #PromptEngineering #AI #LLM — CHAPTERS — 00:00 Intro to prompt engineering 00:34 What are LLMs? 01:06 Context, tokens, and limitations 01:53 Understanding hallucinations and limitations 02:25 What is a prompt? 03:14 What is prompt engineering? 03:41 Key components of effective prompting 04:15 Refining a prompt example 05:26 Handling prompt confusion and multi-step tasks 06:17 Token limits and iterative prompting 07:14 Being explicit and avoiding assumptions 07:52 Final recap and takeaways Want to learn more? Visit: https://github.blog/ai-and-ml/github-copilot/github-for-beginners-how-to-get-llms-to-do-what-you-want Stay up-to-date on all things GitHub by connecting with us: YouTube: https://gh.io/subgithub Blog: https://github.blog X: https://twitter.com/github LinkedIn: https://linkedin.com/company/github Insider newsletter: https://resources.github.com/newsletter/ Instagram: https://www.instagram.com/github TikTok: https://www.tiktok.com/@github About GitHub It’s where over 100 million developers create, share, and ship the best code possible. It’s a place for anyone, from anywhere, to build anything—it’s where the world builds software. https://github.com