From what I gather, you can build an agent for a task as long as:
- you trust the decision making of an LLM for the required type of decision to be made; so decisions framed as some kind of evaluation of text feels right.
- and if the penalty for being wrong is acceptable.
Just to go back to the resume screening application, you'd build an agent if:
- you asked the LLM to make an evaluation based on the text content of the resume, any conversation with the applicant, and the declared job requirement.
- you had a high enough volume of resumes where false negatives won't be too painful.
It seems like framing problems as search problems helps model these systems effectively. They're not yet capable of design, i.e, be responsible for coming up with the job requirement itself.
From what I gather, you can build an agent for a task as long as:
- you trust the decision making of an LLM for the required type of decision to be made; so decisions framed as some kind of evaluation of text feels right.
- and if the penalty for being wrong is acceptable.
Just to go back to the resume screening application, you'd build an agent if:
- you asked the LLM to make an evaluation based on the text content of the resume, any conversation with the applicant, and the declared job requirement.
- you had a high enough volume of resumes where false negatives won't be too painful.
It seems like framing problems as search problems helps model these systems effectively. They're not yet capable of design, i.e, be responsible for coming up with the job requirement itself.