AI engineering glossary · Prompt context engineering
What is context stuffing?
Context stuffing: Placing as much source material as possible into the prompt in one go, relying on the model's large input capacity rather than selecting passages. It is easy but raises cost and can bury the relevant part among noise.
Context stuffing: an example
Pasting an entire 150-page policy PDF into the prompt to answer a single question about leave rules.
Related terms
More Prompt context engineering terms
- Context truncation
- Contrastive chain-of-thought
- Conversation buffer memory
- Conversation history
- Delimiters
- Developer message
- Directional stimulus prompting
- DSPy
Where you learn it
Context stuffing is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.