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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 LLM-based, 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.

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

  • 会议论文

  • 发表日期：

    2025年

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  • Lois Abigail To,
  • Zachary Matthew Alabastro,
  • Joseph Benjamin Ilagan,
  • Jose Ramon Ilagan

摘要

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 LLM-based, 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.