Prompt Engineering
The practice of designing prompts to get reliable, high-quality model output.
Prompt engineering is the practice of crafting input text — instructions, context, constraints, and examples — to steer a foundation model toward consistent, high-quality outputs without modifying model weights. On the AIF-C01 exam it sits at the lowest-cost end of the customization hierarchy: no training data, no compute, no redeployment, making it the first lever to try in Amazon Bedrock before RAG or fine-tuning. Do not confuse it with fine-tuning, which updates model parameters to teach new knowledge or style; prompt engineering only shapes how the model applies pre-trained knowledge at inference. Few-shot examples, chain-of-thought, and output-format directives are testable techniques.
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