Zero-Shot Prompting

Definitions

1. Zero-Shot Prompting is a prompting technique or prompt-side control used to shape large-model behavior at inference time. It is commonly used for chat systems, orchestration layers, and retrieval-augmented applications, where teams need predictable behavior under real workloads rather than toy examples. Practitioners pay attention to instruction clarity, jailbreak resistance, and token cost, because those factors usually determine whether the approach improves quality, latency, reliability, or operating cost in production.

   In plain English: Zero-Shot Prompting is an AI concept teams use to train models, guide predictions, or make model behavior more reliable and easier to control in practice.

   Example: "We added Zero-Shot Prompting to the assistant stack so prompts stayed within the context window, outputs became more consistent, and the inference path stopped failing on long enterprise documents during peak traffic."

Related Terms

• LLM Agent
• LLM Evaluation
• LLM Fine-Tuning
• LLM Inference
• LLM Routing
• LLM Safety
• Local LLM
• Long Context