Bridging the gap between industry and academia Sustainability in LLM-assisted software engineering

The advent of Large Language Models in software engineering brings both academic research and industry to the cutting edge of uncharted territory, breaking the typical division of roles, and inviting a new type of symbiosis between academia and industry. This paper draws insights from the SILAS workshop, collocated with ICT4S 2025, which aimed to examine sustainability in the context of software development supported by Large Language Models (LLMs). This paper identifies key gaps between academic and industrial approaches to methods and metrics, accessibility of systems, and efficiency trade-offs. Examples include differences in technology maturity levels, metrics, and assumptions about operational environments in each context. We outline key considerations for shaping research agendas that emphasize standardized, outcome-oriented studies linking reproducibility with real-world sustainability, aiming at achieving greener AI.