Building Your Own Product Copilot: Challenges, Opportunities, and Needs

A race is underway to embed advanced AI capabil-ities into products. These product “copilots” enable users to ask questions in natural language and receive relevant responses that are specific to the user's context. In fact, virtually every large technology company is looking to add these capabilities to their software products. However, for most software engineers, this is often their first encounter with integrating AI-powered technol-ogy. Furthermore, software engineering processes and tools have not caught up with the challenges and scale involved with building AI-powered applications. In this work, we present the findings of an interview study with 26 professional software engineers responsible for building product copilots at various companies. From our interviews, we found pain points at every step of the engineering process and the challenges that strained existing development practices. We then conducted group brainstorming sessions to collaborative on opportunities and tool designs for the broader software engineering community.

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Publication Details

Published
2025-03-04
DOI
https://doi.org/10.1109/saner64311.2025.00039
Citations
3
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
3.73
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article

Building Your Own Product Copilot: Challenges, Opportunities, and Needs

Jessica A. J. Rich, Sumit Gulwani, Chris Parnin, Gustavo Soares et al.
3 citations
Manufacturing Process and Optimization
3.73
article

Building Your Own Product Copilot: Challenges, Opportunities, and Needs

Jessica A. J. Rich, Sumit Gulwani, Chris Parnin, Gustavo Soares, Austin Z. Henley, Rahul Pandita
article en
3 citations

Abstract

A race is underway to embed advanced AI capabil-ities into products. These product “copilots” enable users to ask questions in natural language and receive relevant responses that are specific to the user's context. In fact, virtually every large technology company is looking to add these capabilities to their software products. However, for most software engineers, this is often their first encounter with integrating AI-powered technol-ogy. Furthermore, software engineering processes and tools have not caught up with the challenges and scale involved with building AI-powered applications. In this work, we present the findings of an interview study with 26 professional software engineers responsible for building product copilots at various companies. From our interviews, we found pain points at every step of the engineering process and the challenges that strained existing development practices. We then conducted group brainstorming sessions to collaborative on opportunities and tool designs for the broader software engineering community.

Microsoft (United States) (US), Carnegie Mellon University (US)
Openalex Percentile: Top 7%
Manufacturing Process and Optimization
3.73
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