the examples, and the capabilities of the generative AI (gen AI) model you are using. As a general rule of thumb, you should use at least three to five examples for few-shot prompting. However, you may simplicity Prompts should be concise, clear, and easy to understand for both you and the model. As a rule of thumb, if it’s already confusing for you it will likely be also confusing for the model. Try not more robust and generalizable performance on unseen data. Prompt Engineering February 2025 60 A good rule of thumb is to start with 6 few shot examples and start testing the accuracy from there. Adapt to

conventional automation, agents are uniquely suited to workflows where traditional deterministic and rule-based approaches fall short. Consider the example of payment fraud analysis. A traditional rules making them well-suited for use cases that involve complex decisions, unstructured data, or brittle rule-based systems. To build reliable agents, start with strong foundations: pair capable models with

which acquires rewards from a helpful reward model ??ℎ??? ???, a safety reward model ???? ????, and a rule-based reward model ??????. The final reward of a response ?? is ?? = ?1 · ??ℎ??? ???(??) + ?2 ·