Mr. Abhinav Balasubramanian
Prompt Engineering in Foundation Models: Designing Inputs for Intelligent Output
Abstract:
Prompt engineering is an emerging discipline focused on crafting effective input instructions to elicit desired behaviors from large-scale foundation models, such as those used in natural language processing, code generation and multimodal tasks. Unlike traditional programming, where logic is explicitly defined, prompt engineering operates in a zero-code paradigm where natural language itself becomes the interface to computation. At the core of this practice is the observation that language models are highly sensitive to input phrasing, structure and context, making prompt design a critical tool for maximizing model performance.
Foundation models, including large language models (LLMs) and vision-language models, are typically pre-trained on vast corpora and exhibit broad generalization capabilities across a wide range of downstream tasks. However, they often require carefully constructed prompts to perform specific actions reliably. This session explores the technical underpinnings of prompt design, including zero-shot, one-shot and few-shot learning configurations. These approaches differ in the number and format of examples provided within the prompt, each with unique implications for task accuracy and computational efficiency.
We will also examine commonly used design patterns such as role assignment, contextual grounding and output constraint specification - techniques that improve response quality and controllability. Additionally, the session introduces prompt tuning, a lightweight, parameter-efficient approach that adapts large models by learning continuous prompt embeddings rather than updating core model weights.
By the end of the session, attendees will have a foundational understanding of prompt engineering as both a practical skill and conceptual framework. They will learn to evaluate prompt effectiveness, debug prompt failures and integrate prompt techniques into larger AI workflows. While the field continues to evolve, prompt engineering is quickly becoming essential for engineers and researchers aiming to harness the full potential of foundation models.