"Agentic" doesn't really mean much and I dislike it. There's no clean line between a "normal" LLM and an "agentic" LLM. Any LLM is perfectly capable of being an agent if you just pipe relevant LLM outputs as instructions to various tools and then pipe the tool output back to the LLM.

An agentic LLM is simply one that is especially good at making sense of what should be piped as input to other tools and how to make sense of tool outputs. Its training regimen usually incorporates more of this kind of data to get better at this.