Large Language Models (LLMs) have been widely adopted and are becoming ubiquitous and integral to software development. However, we have little knowledge as to how these tools are being used by software developers in real-world scenarios, beyond anecdotal evidence and word-of-mouth reports. In this work, we present a study toward understanding how developers engage with and utilize LLMs by reporting the results of an empirical study identifying patterns in the conversation that developers have with LLMs. In particular, we performed an empirical study of developers’ conversations with LLMs in which we identified a total of 19 topics describing the purpose of the developers in their conversations with LLMs. Our findings reveal that developers use LLMs to facilitate various aspects of their software development processes (e.g., information-seeking about programming languages and frameworks and soliciting high-level design recommendations) to a similar extent to which they use them for non-development purposes such as writing assistance, general purpose queries, and conducting Turing tests to assess the intrinsic capabilities of the models. This work not only sheds light on the diverse applications of LLMs in software development but also underscores their emerging role as critical tools in enhancing developer productivity and creativity as we move closer to widespread AI-assisted software development.