// MODEL OPTIMIZATION AND PROMPT SYNTAX TERM
One-Shot
A type of prompt where you give the AI model just one example of the desired input and output to guide its response.
TECHNICAL DEFINITION
One-shot prompting is an in-context learning technique where a large language model (LLM) is provided with a single input-output example within the prompt to demonstrate the desired task format or behavior, enabling rapid generalization.
BACKGROUND
Prompt engineering is the process of structuring natural language inputs to produce specified outputs from a generative artificial intelligence (GenAI) model. Context engineering is the related area of software engineering that focuses on the management of non-prompt contexts supplied to the GenAI model, such as metadata, API tools, and tokens.
READ MORE ON WIKIPEDIASYNONYMS & ALIASES
- Single-example prompt
- Example-guided prompt
USAGE NOTE
One-shot prompting is useful for simple tasks or when demonstrating a specific output format.
DEVELOPERS
Organizations developing technology related to One-Shot.
Pioneers in large language models (e.g., GPT series) where one-shot learning, guided by expertly crafted prompts, is a primary method for model instruction and behavior customization without fine-tuning.
Develops advanced LLMs (e.g., Gemini) that effectively utilize one-shot examples within prompts to understand and perform tasks, a core concept in their prompt engineering research and application.
Focuses on building safe and helpful AI, where prompt design, including providing single-example instructions for one-shot learning, is central to controlling and guiding their Claude models.
Provides enterprise-grade LLMs, emphasizing the importance of effective prompt engineering, where one-shot examples enable quick adaptation of models to specific business tasks without extensive data or training.
A leading platform for open-source AI, offering models, tools, and datasets that enable developers and researchers to experiment with and implement one-shot learning through prompt design across a wide range of tasks.
Offers cloud services and tools for deploying and managing AI models, providing an environment where users apply prompt engineering techniques, including one-shot prompting, to customize pre-trained LLMs for specific applications.
Develops frameworks for building LLM-powered applications, specifically facilitating advanced prompt engineering techniques like dynamic one-shot example injection and prompt chaining to achieve complex reasoning and task execution.