AI That Helps Us Help Each Other: A Proactive System for Scaffolding Mentor-Novice Collaboration in Entrepreneurship Coaching
Evey Jiaxin Huang, Matthew Easterday, Elizabeth Gerber

TL;DR
This paper introduces a proactive human-AI coaching system that enhances entrepreneurial mentoring by supporting metacognition and collaboration, leading to more focused and emotionally attuned meetings in complex, uncertain domains.
Contribution
It presents a novel AI system combining domain-specific cognitive modeling with LLMs to proactively scaffold entrepreneurial coaching and allows mentors to customize the system's logic.
Findings
Supported novice metacognition and strategic planning.
Improved meeting depth, focus, and emotional attunement.
Identified trust and misdiagnosis challenges in AI-human collaboration.
Abstract
Entrepreneurship requires navigating open-ended, ill-defined problems: identifying risks, challenging assumptions, and making strategic decisions under deep uncertainty. Novice founders often struggle with these metacognitive demands, while mentors face limited time and visibility to provide tailored support. We present a human-AI coaching system that combines a domain-specific cognitive model of entrepreneurial risk with a large language model (LLM) to proactively scaffold both novice and mentor thinking. The system proactively poses diagnostic questions that challenge novices' thinking and helps both novices and mentors plan for more focused and emotionally attuned meetings. Critically, mentors can inspect and modify the underlying cognitive model, shaping the logic of the system to reflect their evolving needs. Through an exploratory field deployment, we found that using the system…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
