AI Glossary · Prompt Engineering
Self-Consistency
Sampling multiple reasoning paths and voting on the answer — a cheap accuracy lift for math, logic and extraction tasks.
Definition
What is Self-Consistency?
Self-Consistency is sampling multiple reasoning paths and voting on the answer — a cheap accuracy lift for math, logic and extraction tasks.
- Category
- Prompt Engineering
- Glossary set
- 11 related terms
- Audience
- Enterprise AI leaders
Why does Self-Consistency matter in enterprise AI?
Self-Consistency matters in enterprise AI programs because it helps business and technology leaders align vocabulary, scope, ownership, and measurable outcomes.
Related terms in Prompt Engineering
- Few-Shot Prompting
- Including a small number of input–output examples in the prompt to demonstrate the desired format and reasoning.
- Instruction Tuning
- Post-training on instruction–response pairs so the base model follows natural-language instructions reliably.
- Meta-Prompting
- Using an LLM to draft, critique or optimize prompts for another LLM — a scalable alternative to hand-crafting.
- Persona Prompting
- Assigning a role ("You are a senior claims adjuster…") to steer tone, depth and vocabulary of the output.
- Prompt Chaining
- Decomposing a task into a sequence of prompts where each step's output feeds the next; the poor-man's agent.
- Prompt Engineering
- The practice of designing inputs (instructions, examples, structure) that reliably elicit the desired model behavior.