Comment by AbhinavX
6 days ago
Colloquially, AI agents are just while loops with LLM calls and tool calls. More specifically, what distinguishes an agent from LLM pipelines is that its next step is determined dynamically (based on the output of the previous one) so the execution path isn’t fixed. The boundary between complex LLM chaining and agents is pretty fuzzy, but we support both.
Haha also our whole backend is in Django :)
Gotcha, you're using the "LLM calling tools in a loop" definition. I think that's a decent one, but I worry that many people out there are carrying around completely different ideas as to what the term means.
Do you have a writeup on the different interpretations of "AI Agent"?
I need to put one together. The big ones are:
- "LLM running tools in a loop" - often used by Anthropic, generally the most popular among software engineers who build things
- "An AI system that performs tasks on your behalf" - used by OpenAI, I dislike how vague this one is
- "an entity that perceives its environment through sensors and acts upon that environment through actuators to achieve specific goals" - the classic academic one, Russell and Norvig. I sometimes call this the "thermostat definition".
- "kinda like a travel agent I guess?" - quite common among less technical people I've talked to
I gathered over a hundred on Twitter last year, summarized by Gemini here: https://gist.github.com/simonw/beaa5f90133b30724c5cc1c4008d0...
I also have a tag about this on my blog: https://simonwillison.net/tags/agent-definitions/
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