Large language models (LLMs) can be used to automate software engineering tasks, with the hope of boosting developers' productivity without sacrificing reliability. In this talk, I will briefly present two initiatives: the défi Inria LLM4Code and the CodeCommons project around SoftwareHeritage, exemplifying ongoing research efforts. Then, I will show how LLMs can automatically generate software variants across different technological spaces (Python, Rust, JavaScript, etc.) and implement new features from simple prompts. I will also highlight how LLMs can assist in modernizing legacy applications, such as those written in COBOL or in deprecated technologies. I will further discuss the concept of programming without directly manipulating programs, relying almost entirely on AI to manage technical details and customize code. For all their potential, I will also demonstrate that LLMs can dramatically fail at times, making mistakes that human developers need to carefully verify and correct. I will conclude with an illustration of LLM prompt sensitivity in chess, showcasing how LLMs can be used both to generate variants (e.g., prompts, hypotheses, ideas) and to accelerate scientific discovery through software-based exploration and analysis. 28 november 2024 @ Caen, invited talk at Normastic https://www.normastic.fr/event/journee-de-laxe-donnees-apprentissage-connaissances-large-language-models-llms/