  We introduce the concept of "thinking assistants", an approach that
encourages users to engage in deep reflection and critical thinking through
brainstorming and thought-provoking queries. We instantiate one such thinking
assistant, Gradschool.chat, as a virtual assistant tailored to assist
prospective graduate students. We posit that thinking assistants are
particularly relevant to situations like applying to graduate school, a phase
often characterized by the challenges of academic preparation and the
development of a unique research identity. In such situations, students often
lack direct mentorship from professors, or may feel hesitant to approach
faculty with their queries, making thinking assistants particularly useful.
  Leveraging a Large Language Model (LLM), Gradschool.chat is a demonstration
system built as a thinking assistant for working with specific professors in
the field of human-computer interaction (HCI). It was designed through training
on information specific to these professors and a validation processes in
collaboration with these academics. This technical report delineates the
system's architecture and offers a preliminary analysis of our deployment
study. Additionally, this report covers the spectrum of questions posed to our
chatbots by users. The system recorded 223 conversations, with participants
responding positively to approximately 65% of responses. Our findings indicate
that users who discuss and brainstorm their research interests with
Gradschool.chat engage more deeply, often interacting with the chatbot twice as
long compared to those who only pose questions about professors.
