LLMs' reshaping of people, processes, products, and society in software development: a qualitative exploration with early adopters
Published journal article
Benyamin Tabarsi; Heidi Reichert; Sam Gilson; Ally Limke; Sandeep Kuttal; Tiffany Barnes
Empirical Software Engineering, volume 32, article 21
Citation year: 2027.
First published online: 2026-08-07.
Summary
What changed when software professionals began using LLMs in their daily work? This qualitative study analyzes interviews with 16 early adopters who used these tools in early to mid-2023. Their accounts describe changes in people, processes, products, and society, including the effort involved in evaluating and integrating generated code. Participants described productivity benefits alongside the work of checking generated output.
What this study can tell us
The interviews describe professionals’ experiences during an early period of adoption. Reported productivity gains are participants’ accounts, rather than an experimental measurement of productivity or code quality.
Author-hosted abstract
The abstract below preserves the version previously posted on this site. Its wording differs from the final publisher abstract. Consult the publisher record for the version of record.
Large language models (LLMs) are rapidly reshaping software development, but their impact across the software development lifecycle is underexplored. Existing work focuses on isolated activities such as code generation or testing, leaving open questions about how LLMs affect developers, processes, products, and the software ecosystem. We address this gap through semi-structured interviews with sixteen early-adopter software professionals who integrated LLM-based tools into their day-to-day work in early to mid-2023. We treat these interviews as early empirical evidence and compare participants’ accounts with recent work on LLMs in software engineering, noting which early patterns persist or shift. Using thematic analysis, we organize findings around four dimensions: people, process, product, and society. Developers reported substantial productivity gains from reducing routine tasks, streamlining search, and accelerating debugging, but also described a productivity-quality paradox: they often discarded generated code and shifted effort from writing to critically evaluating and integrating it. LLM use was highly phase-dependent, with strong uptake in implementation and debugging but limited influence on requirements gathering and other collaborative work. Participants developed new competencies to use LLMs effectively, including prompt engineering strategies, layered verification, and secure integration to protect proprietary data. They anticipated changes in hiring expectations, team practices, and computing education, while emphasizing that human judgment and foundational software engineering skills remain essential. Our findings, later echoed in large-scale quantitative studies, offer actionable implications for developers, organizations, educators, and tool designers seeking to integrate LLMs responsibly into software practice today.
The abstract as previously posted on this site.
Citation
@article{tabarsi2026reshaping,
title = {{LLMs' reshaping of people, processes, products, and society in software development: a qualitative exploration with early adopters}},
author = {Benyamin Tabarsi and Heidi Reichert and Sam Gilson and Ally Limke and Sandeep Kuttal and Tiffany Barnes},
year = {2027},
journal = {Empirical Software Engineering},
volume = {32},
number = {1},
eid = {21},
note = {First online 7 August 2026; volume year 2027},
doi = {10.1007/s10664-026-10917-0},
url = {https://sgilson7.github.io/papers/tabarsi2026reshaping/}
}
The publisher provides the final article as open access.