Part 4/4:

Throughout the conversation, Suly shares his insights on the rapidly changing landscape of LLMs, highlighting the ongoing advancements and the need for continuous adaptation. He notes the emergence of new capabilities, such as improved tool use and structured output generation, as well as the potential limitations of current models, which may require creative workarounds and model orchestration to overcome.

Suly's deep understanding of LLM nuances and his practical, hands-on approach to leveraging these powerful AI tools provide valuable guidance for developers, researchers, and anyone interested in pushing the boundaries of what's possible with large language models.