Augmenting Student Startups’ Customer Validation Efforts Through Adaptive Coaching Using Large Language Models

Authors

• Lois Abigail To, Ateneo de Manila University
• Zachary Matthew C. Alabastro, Ateneo de Manila University
• Joseph Benjamin R. Ilagan, Ateneo de Manila University
• Jose Ramon S. Ilagan, Ateneo de Manila University

Document Type

Conference Proceeding

Publication Date

6-22-2025

Abstract

Startup founders experience numerous barriers to venture creation. Customer development (CD), under the Lean Startup (LS) methodology, is a customer-centric process of refining business models to reduce startup failure. This paper explores the design of an LLMbased, adaptive coaching model that utilizes artificial intelligence’s (AI) natural language processing (NLP) and continuous learning capabilities to formulate contextual responses that are suitable for the user’s business context. Subsequently, the model generates synthetic customer insights to simulate customer interactions and strengthen CD competencies, creating more efficient systems for startup validation. Results suggest that the LLM-based adaptive coaching model is effective for startup validation and entrepreneurial education.

Recommended Citation

To, L. A., & Alabastro, Z. M., Ilagan, J. B., & Ilagan, J. R. (2025). Augmenting Student Startups’ Customer Validation Efforts Through Adaptive Coaching Using Large Language Models. Lecture Notes in Computer Science, Volume 15804 LNCS, Pages 209-220.