[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"glossary-emotion-prompting::en":3,"gloss-cluster-emotion-prompting::en":23,"gloss-next-emotion-prompting::en":9},{"slug":4,"category":5,"name":6,"definition":7,"meta_desc":8,"faq":9,"schema_markup":9,"related":10},"emotion-prompting","prompt-eng","Emotion Prompting","Emotion prompting is the practice of adding emotionally charged phrasing to a prompt — statements like \"This is very important to my career\" or \"Take pride in your work and do your best\" — to try to improve model performance. It came from the EmotionPrompt study (Li et al., 2023), which reported measurable gains on a range of benchmarks when such \"emotional stimuli\" were appended to instructions. The proposed intuition is that these cues resemble motivational or high-stakes language in the training data and nudge the model toward more careful responses. For SaaS builders, the honest framing is: it's a low-cost thing to A\u002FB test, not a guaranteed lever. Effects vary by model, task, and phrasing, some later results are mixed, and gains reported on benchmarks may not transfer to your specific feature. Treat it as one candidate tweak among many — throw it into your evaluation set alongside clearer, more reliable techniques like explicit instructions, examples, and rubrics, and keep it only if your own numbers actually move.","Emotion prompting adds emotionally charged lines like \"this is important to my career\" to a prompt — a much-repeated trick on shaky, model-dependent evidence.",null,[11,14,17,20],{"slug":12,"name":13},"chain-of-thought-prompting","Chain-of-Thought Prompting",{"slug":15,"name":16},"meta-prompt","Meta Prompt",{"slug":18,"name":19},"prompt-engineering","Prompt Engineering",{"slug":21,"name":22},"role-prompting","Role Prompting",[24,28,31,34,36,39,42,45,48,51,54,57],{"slug":25,"category":5,"name":26,"updated_at":27},"analogical-prompting","Analogical Prompting","2026-08-24T02:46:37+00:00",{"slug":29,"category":5,"name":30,"updated_at":27},"automatic-prompt-optimization","Automatic Prompt Optimization",{"slug":32,"category":5,"name":33,"updated_at":27},"chain-of-density","Chain of Density (CoD)",{"slug":12,"category":5,"name":13,"updated_at":35},"2026-08-24T02:46:36+00:00",{"slug":37,"category":5,"name":38,"updated_at":27},"chain-of-verification","Chain-of-Verification",{"slug":40,"category":5,"name":41,"updated_at":35},"chunking","Chunking",{"slug":43,"category":5,"name":44,"updated_at":35},"constrained-decoding","Constrained Decoding",{"slug":46,"category":5,"name":47,"updated_at":35},"context-stuffing","Context Stuffing",{"slug":49,"category":5,"name":50,"updated_at":35},"delimiter","Delimiter",{"slug":52,"category":5,"name":53,"updated_at":27},"directional-stimulus-prompting","Directional Stimulus Prompting",{"slug":55,"category":5,"name":56,"updated_at":35},"few-shot-prompting","Few-Shot Prompting",{"slug":58,"category":5,"name":59,"updated_at":27},"generated-knowledge-prompting","Generated Knowledge Prompting"]