The term AI agent is used loosely. It can mean almost anything. Here are some more concrete patterns of what it means today:
- LLM-in-a-loop. Use the output of an LLM as the input to a subsequent call. There might be some intermediate steps in the chain (preprocessing, templating, formatting).
- Chatbot with custom personas. These agents take on a specific persona via custom instructions. There are sites like Character.AI that let you create “characters” and talk to them — from well-known characters from video games or television shows to made-up ones.
- Code generation and execution via natural language. Given a natural language prompt, the LLM generates some code as part of its response and then executes it in a (hopefully) sandboxed environment.
- Dynamic workflow engine. The LLM uses its output to generate a dynamic workflow that is then executed. This is different than the predetermined workflow in the LLM-in-a-loop pattern.
- Tool use. Similar to the code generation and execution pattern, LLMs can call a number of predetermined tools to solve a query. These might just be functions or APIs that the LLM knows how to use. They might be learned over time and stored (e.g., Voyager).