A Prompt Engineering-based Process to Build Proto-personas during Lean Inception
Resumo
Product discovery approaches such as Lean Inception (LI) typically span five days (40 working hours). During LI, the participants create and refine proto-personas during four working hours to understand user needs. Proto-personas are preliminary, assumption-based representations of ideal users that guide initial design discussions. The accuracy of proto-personas generated in this context has been counterintuitive due to limited time for idea exploration and refinement, for example. There are approaches to building personas (e.g. data-driven, LLMs). However, there is a gap in exploring the use of prompt engineering and proto-persona strategies to support the Product Discovery approaches. Our research investigates the application of a prompt engineering-based approach to building protopersonas during LI. We report an exploratory case study where six participants used our approach to generate proto-personas in a given scenario. The impact of our approach positively influenced the outcome. Most proto-personas developed by our process better represented the target audience than those from LI, despite some inconsistencies. Our process was well accepted by participants and suggestions were made to improve the process. Our approach used an average of 11 minutes of working hours (SD 2.24 minutes), traditionally this time in LI is four hours.
Palavras-chave:
prompt engineering, proto-persona, lean persona, product discovery, lean inception
Referências
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Angela Fan, Beliz Gokkaya, Mark Harman, Mitya Lyubarskiy, Shubho Sengupta, Shin Yoo, and JieMZhang. 2023. Large language models for software engineering: Survey and open problems. arXiv preprint arXiv:2310.03533 (2023).
Jeff Gothelf. 2013. Lean UX: Applying lean principles to improve user experience. " O’Reilly Media, Inc.".
Soon-Gyo Jung, Jisun An, Haewoon Kwak, Moeed Ahmad, Lene Nielsen, and Bernard J Jansen. 2017. Persona generation from aggregated social media data. In Proceedings of the 2017 CHI conference extended abstracts on human factors in computing systems. 1748–1755.
Devi Karolita, Jennifer McIntosh, Tanjila Kanij, John Grundy, and Humphrey O Obie. 2023. Use of personas in Requirements Engineering: A systematic mapping study. Information and Software Technology (2023), 107264.
Baoli Li and Liping Han. 2013. Distance weighted cosine similarity measure for text classification. In Intelligent Data Engineering and Automated Learning–IDEAL 2013: 14th International Conference, IDEAL 2013, Hefei, China, October 20-23, 2013. Proceedings 14. Springer, 611–618.
Jianing Liu, Jia Shi, Jun Xie, Xinyun Zhang, Zichuan Zhang, John Grundy, and Tanjila Kanij. 2022. A curated personas and design guidelines tool for better supporting diverse end-users. In 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, 1606–1613.
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2023. Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing. Comput. Surveys 55, 9 (2023), 1–35.
Patricia Losana, John W Castro, Xavier Ferre, Elena Villalba-Mora, and Silvia T Acuña. 2021. A systematic mapping study on integration proposals of the personas technique in agile methodologies. Sensors 21, 18 (2021), 6298.
Nuno Marques, Rodrigo Rocha Silva, and Jorge Bernardino. 2024. Using ChatGPT in Software Requirements Engineering: A Comprehensive Review. Future Internet 16, 6 (2024), 180.
Anh Nguyen-Duc, Beatriz Cabrero-Daniel, Adam Przybylek, Chetan Arora, Dron Khanna, Tomas Herda, Usman Rafiq, Jorge Melegati, Eduardo Guerra, Kai-Kristian Kemell, et al. 2023. Generative Artificial Intelligence for Software Engineering–A Research Agenda. arXiv preprint arXiv:2310.18648 (2023).
Eduardo Gouveia Pinheiro, Larissa Albano Lopes, Tayana Uchôa Conte, and Luciana Aparecida Martinez Zaina. 2018. The contribution of non-technical stakeholders on the specification of UX requirements: an experimental study using the proto-persona technique. In Proceedings of the XXXII Brazilian Symposium on Software Engineering. 92–101.
Austen Rainer and Claes Wohlin. 2022. Recruiting credible participants for field studies in software engineering research. Information and Software Technology 151 (2022), 107002.
Per Runeson and Martin Höst. 2009. Guidelines for conducting and reporting case study research in software engineering. Empirical software engineering 14 (2009), 131–164.
June Sallou, Thomas Durieux, and Annibale Panichella. 2024. Breaking the silence: the threats of using llms in software engineering. In Proceedings of the 2024 ACM/IEEE 44th International Conference on Software Engineering: New Ideas and Emerging Results. 102–106.
Joni Salminen, Kathleen Wenyun Guan, Soon-Gyo Jung, and Bernard Jansen. 2022. Use cases for design personas: A systematic review and new frontiers. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. 1–21.
Stefan Trieflinger, Dominic Lang, Selina Spies, and Jürgen Münch. 2023. The discovery effort worthiness index: How much product discovery should you do and how can this be integrated into delivery? Information and software technology 157 (2023), 107167.
Jules White, Quchen Fu, Sam Hays, Michael Sandborn, Carlos Olea, Henry Gilbert, Ashraf Elnashar, Jesse Spencer-Smith, and Douglas C Schmidt. 2023. A prompt pattern catalog to enhance prompt engineering with chatgpt. arXiv preprint arXiv:2302.11382 (2023).
Xishuo Zhang, Lin Liu, YiWang, Xiao Liu, HailongWang, Chetan Arora, Haichao Liu, Weijia Wang, and Thuong Hoang. 2024. Auto-Generated Personas: Enhancing User-centered Design Practices among University Students. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. 1–7.
Xishuo Zhang, Lin Liu, Yi Wang, Xiao Liu, Hailong Wang, Anqi Ren, and Chetan Arora. 2023. PersonaGen: A Tool for Generating Personas from User Feedback. In 2023 IEEE 31st International Requirements Engineering Conference (RE). IEEE, 353–354.
Stephen Atlas. 2023. ChatGPT for higher education and professional development: A guide to conversational AI. (2023).
Lenz Belzner, Thomas Gabor, and Martin Wirsing. 2023. Large language model assisted software engineering: prospects, challenges, and a case study. In International Conference on Bridging the Gap between AI and Reality. Springer, 355–374.
Paulo Caroli. 2015. Direto ao ponto: criando produtos de forma enxuta. Editora Casa do Código.
Paulo Caroli. 2017. Lean inception. São Paulo, BR: Caroli. org (2017).
Kathy Charmaz. 2006. Constructing grounded theory: A practical guide through qualitative analysis. sage.
Angela Fan, Beliz Gokkaya, Mark Harman, Mitya Lyubarskiy, Shubho Sengupta, Shin Yoo, and JieMZhang. 2023. Large language models for software engineering: Survey and open problems. arXiv preprint arXiv:2310.03533 (2023).
Jeff Gothelf. 2013. Lean UX: Applying lean principles to improve user experience. " O’Reilly Media, Inc.".
Soon-Gyo Jung, Jisun An, Haewoon Kwak, Moeed Ahmad, Lene Nielsen, and Bernard J Jansen. 2017. Persona generation from aggregated social media data. In Proceedings of the 2017 CHI conference extended abstracts on human factors in computing systems. 1748–1755.
Devi Karolita, Jennifer McIntosh, Tanjila Kanij, John Grundy, and Humphrey O Obie. 2023. Use of personas in Requirements Engineering: A systematic mapping study. Information and Software Technology (2023), 107264.
Baoli Li and Liping Han. 2013. Distance weighted cosine similarity measure for text classification. In Intelligent Data Engineering and Automated Learning–IDEAL 2013: 14th International Conference, IDEAL 2013, Hefei, China, October 20-23, 2013. Proceedings 14. Springer, 611–618.
Jianing Liu, Jia Shi, Jun Xie, Xinyun Zhang, Zichuan Zhang, John Grundy, and Tanjila Kanij. 2022. A curated personas and design guidelines tool for better supporting diverse end-users. In 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, 1606–1613.
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2023. Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing. Comput. Surveys 55, 9 (2023), 1–35.
Patricia Losana, John W Castro, Xavier Ferre, Elena Villalba-Mora, and Silvia T Acuña. 2021. A systematic mapping study on integration proposals of the personas technique in agile methodologies. Sensors 21, 18 (2021), 6298.
Nuno Marques, Rodrigo Rocha Silva, and Jorge Bernardino. 2024. Using ChatGPT in Software Requirements Engineering: A Comprehensive Review. Future Internet 16, 6 (2024), 180.
Anh Nguyen-Duc, Beatriz Cabrero-Daniel, Adam Przybylek, Chetan Arora, Dron Khanna, Tomas Herda, Usman Rafiq, Jorge Melegati, Eduardo Guerra, Kai-Kristian Kemell, et al. 2023. Generative Artificial Intelligence for Software Engineering–A Research Agenda. arXiv preprint arXiv:2310.18648 (2023).
Eduardo Gouveia Pinheiro, Larissa Albano Lopes, Tayana Uchôa Conte, and Luciana Aparecida Martinez Zaina. 2018. The contribution of non-technical stakeholders on the specification of UX requirements: an experimental study using the proto-persona technique. In Proceedings of the XXXII Brazilian Symposium on Software Engineering. 92–101.
Austen Rainer and Claes Wohlin. 2022. Recruiting credible participants for field studies in software engineering research. Information and Software Technology 151 (2022), 107002.
Per Runeson and Martin Höst. 2009. Guidelines for conducting and reporting case study research in software engineering. Empirical software engineering 14 (2009), 131–164.
June Sallou, Thomas Durieux, and Annibale Panichella. 2024. Breaking the silence: the threats of using llms in software engineering. In Proceedings of the 2024 ACM/IEEE 44th International Conference on Software Engineering: New Ideas and Emerging Results. 102–106.
Joni Salminen, Kathleen Wenyun Guan, Soon-Gyo Jung, and Bernard Jansen. 2022. Use cases for design personas: A systematic review and new frontiers. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. 1–21.
Stefan Trieflinger, Dominic Lang, Selina Spies, and Jürgen Münch. 2023. The discovery effort worthiness index: How much product discovery should you do and how can this be integrated into delivery? Information and software technology 157 (2023), 107167.
Jules White, Quchen Fu, Sam Hays, Michael Sandborn, Carlos Olea, Henry Gilbert, Ashraf Elnashar, Jesse Spencer-Smith, and Douglas C Schmidt. 2023. A prompt pattern catalog to enhance prompt engineering with chatgpt. arXiv preprint arXiv:2302.11382 (2023).
Xishuo Zhang, Lin Liu, YiWang, Xiao Liu, HailongWang, Chetan Arora, Haichao Liu, Weijia Wang, and Thuong Hoang. 2024. Auto-Generated Personas: Enhancing User-centered Design Practices among University Students. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. 1–7.
Xishuo Zhang, Lin Liu, Yi Wang, Xiao Liu, Hailong Wang, Anqi Ren, and Chetan Arora. 2023. PersonaGen: A Tool for Generating Personas from User Feedback. In 2023 IEEE 31st International Requirements Engineering Conference (RE). IEEE, 353–354.
Publicado
30/09/2024
Como Citar
LEÃO, Raul; AYACH, Fernando; LAMEIRÃO, Vitor; FONTÃO, Awdren.
A Prompt Engineering-based Process to Build Proto-personas during Lean Inception. In: SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SOFTWARE (SBES), 38. , 2024, Curitiba/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 585-591.
DOI: https://doi.org/10.5753/sbes.2024.3562.
