AI for journalists: Adding context to your prompts (Module 2.1)

Instructor: Joe Amditis, associate director, Center for Cooperative Media

In this module, Joe Amditis dives into one of the most important (and most overlooked) parts of prompt engineering: context. When working with AI tools, the quality of your output depends heavily on the quality of your input—and context is what helps the model understand what you actually want.

You’ll learn how to add effective background information, define roles and tone, set constraints, and make your AI prompts more relevant to your journalistic goals. Joe also shows how a little extra detail can prevent misunderstandings, reduce hallucinations, and improve your overall results.

This is where your prompts start getting smarter, sharper, and more aligned with your editorial standards.

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Chapters:
00:00:00 – Introduction to module two
00:00:40 – Definition of context for LLMs in journalism
00:01:33 – How much context is enough
00:03:22 – Creating reusable context across prompts
00:05:31 – Types of context useful for journalism
00:07:34 – Handling sensitive and private information
00:09:30 – Why good context dramatically improves responses
00:11:09 – Practical applications for journalism
00:12:46 – Conclusion and preview of next video

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🗣️ ABOUT THE INSTRUCTOR:
Twitter: https://x.com/jsamditis
Instagram:   / jamditis  
Medium:   / jamditis  
LinkedIn:   / jamditis  

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