Few-shot is an AI prompting technique giving the model a few examples before asking it to do the task. Tech jargon. Not concerning. Common in AI engineering. If your kid uses it constantly, ask them where they first heard it, not to police their speech but to understand which online community they are in. Most slang of this kind moves through TikTok and group chats, so seeing it in your child's vocabulary just means they are plugged into normal teen internet culture.
few-shot
Giving an LLM a handful of input/output examples in the prompt before asking it to handle a new case.
fjuː ʃɒtCoined ~20232020sGen AlphatrendingCurrent388 viewsLast reviewed Jun 29, 2026＋ Add a definition
Etymology timeline
Born ~2023 · 1 year of recorded useSeen in the wild
BlueskyMay 2026
“How Few-Shot Examples Add Up: A Causal Decomposition of Function Vectors in In-Context Learning” by Entang Wang, Yiwei Wang, Aleksandra Bakalova, Michael Hahn.
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Wikipedia: Prompt engineering
Effective prompt engineering involves understanding how a model interprets language, and may include techniques such as few-shot prompting, chain-of-thought prompting, and role assignment.
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Wikipedia: GPT-3
It has a context window size of 2,048 tokens, and has demonstrated strong "zero-shot" and "few-shot" learning abilities on many tasks.
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Definitions
Global
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#1·Apr 24, 2026Global
Giving an LLM a handful of input/output examples in the prompt before asking it to handle a new case. A cheap alternative to fine-tuning. "Few-shot examples in the prompt boosted accuracy by 15%." For complex tasks, three good examples often outperform a 200-word system prompt.
"Few-shot examples in the prompt boosted accuracy by 15%."
Origin: AI / developer industry term, 2023–2025.
For parents
Few-shot is an AI prompting technique giving the model a few examples before asking it to do the task. Tech jargon. Not concerning. Common in AI engineering. If your kid uses it constantly, ask them where they first heard it, not to police their speech but to understand which online community they are in. Most slang of this kind moves through TikTok and group chats, so seeing it in your child's vocabulary just means they are plugged into normal teen internet culture.
For ESL learners
Few-shot is a machine-learning term meaning prompting a model with a small number of examples to demonstrate a task. Use in AI engineering and research writing. Formal equivalent: "few-shot prompting," "few-shot learning." Common non-native mistake: hyphenation. "Few-shot" (hyphenated) is the standard form as both adjective and noun in AI literature. Read or listen to the word in context several times before trying it yourself; the right register is harder to learn than the dictionary meaning.
Cluster: ai_specific
Heard in the wild
““How Few-Shot Examples Add Up: A Causal Decomposition of Function Vectors in In-Context Learning” by Entang Wang, Yiwei Wang, Aleksandra Bakalova, Michael Hahn.”
— Bluesky· May 2026“Effective prompt engineering involves understanding how a model interprets language, and may include techniques such as few-shot prompting, chain-of-thought prompting, and role assignment.”
“It has a context window size of 2,048 tokens, and has demonstrated strong "zero-shot" and "few-shot" learning abilities on many tasks.”
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Global
#2·May 2, 2026Global
A machine learning paradigm where a model is trained on a very small amount of data, typically less than that required for traditional machine learning approaches.
Source: Wiktionary (CC BY-SA 4.0)
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For specific readers
Why is this section here?
Slang is read by different audiences for very different reasons. The For parents view re-explains the term in plain, non-judgemental language so a caregiver can understand what their child means without needing the surrounding subculture. The For English learners view focuses on register (when it's safe to use), formal alternatives, and common mistakes — what a textbook won't teach you.
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Semantically related
- zero-shot78%
An LLM correctly performing a task with zero training examples — just natural-language instructions. "Few-shot" is the same with a handful of examples.
- prompt engineering78%
The craft of writing inputs to LLMs to reliably produce the output you want. Includes role-setting, few-shot examples, chain-of-thought, and careful phrasing.
- chain of thought66%
Prompting or training technique where an LLM produces intermediate reasoning steps before the final answer, dramatically improving accuracy on multi-step problems.
- tool use66%
The ability of an LLM to call external functions (search, code execution, databases) mid-conversation. The building block of agentic systems.