You can call one agent. You can return typed output. The next step: what happens when the input isn't one client email — it's forty, and they all need the same processing?
I'd loop over them. A list comprehension maybe — same agent call, different input each time. Does that actually work at scale?
It's exactly a list comprehension. [classify_urgency(t) for t in texts] runs the same agent call for every item in the list. Each call is independent — the model doesn't remember the previous one.
What about cost? Forty API calls sounds expensive.
Each call costs roughly the same as one chat message. Forty calls for 40 client emails is the same as a junior assistant reading each one — except it runs in parallel and costs a fraction of an hour of your time. The economic comparison isn't 40 calls vs. 0 calls; it's 40 calls vs. 40 minutes of your unbilled time.
Goal: by the end of the week you can process entire client lists through AI agents in a single function call.
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You can call one agent. You can return typed output. The next step: what happens when the input isn't one client email — it's forty, and they all need the same processing?
I'd loop over them. A list comprehension maybe — same agent call, different input each time. Does that actually work at scale?
It's exactly a list comprehension. [classify_urgency(t) for t in texts] runs the same agent call for every item in the list. Each call is independent — the model doesn't remember the previous one.
What about cost? Forty API calls sounds expensive.
Each call costs roughly the same as one chat message. Forty calls for 40 client emails is the same as a junior assistant reading each one — except it runs in parallel and costs a fraction of an hour of your time. The economic comparison isn't 40 calls vs. 0 calls; it's 40 calls vs. 40 minutes of your unbilled time.
Goal: by the end of the week you can process entire client lists through AI agents in a single function call.