  Since its release in November 2022, ChatGPT has shaken up Stack Overflow, the
premier platform for developers' queries on programming and software
development. Demonstrating an ability to generate instant, human-like responses
to technical questions, ChatGPT has ignited debates within the developer
community about the evolving role of human-driven platforms in the age of
generative AI. Two months after ChatGPT's release, Meta released its answer
with its own Large Language Model (LLM) called LLaMA: the race was on. We
conducted an empirical study analyzing questions from Stack Overflow and using
these LLMs to address them. This way, we aim to (ii) measure user engagement
evolution with Stack Overflow over time; (ii) quantify the reliability of LLMs'
answers and their potential to replace Stack Overflow in the long term; (iii)
identify and understand why LLMs fails; and (iv) compare LLMs together. Our
empirical results are unequivocal: ChatGPT and LLaMA challenge human expertise,
yet do not outperform it for some domains, while a significant decline in user
posting activity has been observed. Furthermore, we also discuss the impact of
our findings regarding the usage and development of new LLMs.
