[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"glossary-self-refine::en":3,"gloss-cluster-self-refine::en":23,"gloss-next-self-refine::en":9},{"slug":4,"category":5,"name":6,"definition":7,"meta_desc":8,"faq":9,"schema_markup":9,"related":10},"self-refine","prompt-eng","Self-Refine","Self-Refine is an iterative prompting loop in which a single model generates an answer, critiques its own output, and then rewrites it using that critique — repeating until it is satisfied or a step limit is hit. Introduced by Madaan et al. (2023), the key point is that no extra training, external reward model, or human feedback is required: the same LLM plays author, reviewer, and editor across three prompts. It tends to help on open-ended generation — code, drafts, dialogue responses — where a first pass is decent but has fixable flaws the model can spot when asked to look. For SaaS builders it's a cheap quality lever: after generating, add a \"list concrete problems with this output, then produce an improved version\" step. Two caveats: gains are uneven and can plateau or even regress after a couple of rounds, and each iteration costs more tokens and latency — so cap the loop (often one or two passes) and, ideally, measure whether the refined output actually beats the original on your eval set.","Self-Refine loops one model through generate, critique, rewrite until it is satisfied — no extra training, no external tools, just iteration.",null,[11,14,17,20],{"slug":12,"name":13},"chain-of-verification","Chain-of-Verification",{"slug":15,"name":16},"llm-as-judge","LLM-as-Judge",{"slug":18,"name":19},"prompt-chaining","Prompt Chaining",{"slug":21,"name":22},"self-consistency","Self-Consistency",[24,28,31,34,38,39,42,45,48,51,54,57],{"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":35,"category":5,"name":36,"updated_at":37},"chain-of-thought-prompting","Chain-of-Thought Prompting","2026-08-24T02:46:36+00:00",{"slug":12,"category":5,"name":13,"updated_at":27},{"slug":40,"category":5,"name":41,"updated_at":37},"chunking","Chunking",{"slug":43,"category":5,"name":44,"updated_at":37},"constrained-decoding","Constrained Decoding",{"slug":46,"category":5,"name":47,"updated_at":37},"context-stuffing","Context Stuffing",{"slug":49,"category":5,"name":50,"updated_at":37},"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":27},"emotion-prompting","Emotion Prompting",{"slug":58,"category":5,"name":59,"updated_at":37},"few-shot-prompting","Few-Shot Prompting"]