New tools for building agents
161–165 of 165 posts
Re: New tools for building agents
#162Earlier quoted context omitted.
Every manager I see now who gave up or was not a good coder is now chomping at the bit to use these tools
Not true. It’s impossible to find talent with experience in major agent frameworks like smolagents, autogen/ag2, crewAI. I wish that there were tons of managers desperate to learn how to use these tools. I’m not seeing it!
Re: New tools for building agents
#163Earlier quoted context omitted.
I think Anthropic's definition makes the most sense. - Workflows are systems where LLMs and tools are orchestrated through predefined code paths. (imo this is what most people are referring to as "agents") - Agents, on the other hand, are systems where LLMs dynamically direct their own processes and tool usage, maintaining control over how they accomplish tasks. https://www.anthropic.com/engineering/building-effectiv…
The problem with this definition is that modern workflow systems are not through predefined code paths, they do dynamically direct their own processes and tool usage.
If they are driven by LLMs interpretation then there is no explicit code written and it's figured out at runtime
Re: New tools for building agents
#164I don't know how much this API churn is going to help developers who are trying to integrate OAI into real, actual, non-wrapper products. Every vendor-managed state machine that handles conversation, messages, prompt hand-off, etc., has ultimately proven inadequate, presumptive or distracting for my use cases. At the end of the day, all I ever seem to use is the chat completion API with structured outputs turned on.…
Don't get me wrong, chat completions are nice to have for certain use cases, but that being the only option makes me practically unable to use the model.
Re: New tools for building agents
#165Earlier quoted context omitted.
Why would you assume that? Modality of engagement is drastically different between the way LLM engages with UI vs human being
Oh, I had assumed that it was trained on human interaction data and should be generally similar, and from the examples I saw - it generally was (although still not as good as us). In what sense do you expect it to be drastically different?
Do you really see no difference in the way a hollow algorithm interacts with UI vs how a person would go about interacting with UI?