According to @godofprompt, a key trend in prompt engineering is Multi-Shot with Failure Cases, where AI engineers provide models with both good and bad examples, along with explicit explanations of why certain outputs fail. This technique establishes clearer output boundaries and improves model reliability for technical applications, such as explaining API rate limiting. By systematically demonstrating what not to do, businesses can reduce model hallucinations and ensure higher quality, more predictable outputs for enterprise AI deployments (source: @godofprompt, Dec 10, 2025). This approach is gaining traction among AI professionals seeking to deliver robust, production-ready generative AI solutions.