"where agents would ever be better than workflows"
That is a very important observation and we should avoid to let agents go the way of the blockchain -- you know what I mean.
I have build a narrow AI for credit decisioning on a 100B portfolio between 2012 and 2020. This "agent" can make autonomous credit decisions, if and only if the agent is 100% certain that all inputs are accurate. The value comes from the workflow, not the model.
LLMs change this as there is now a general, I like to call them vanilla models, that does not specifically be trained to the data set. Would I use that in this workflow? Likely not.
(a) it is likely that the narrow model is cheaper to operate than a larger model without seeing a substantial benefit in productivity.
(b) in regulated industries we always need to be able to explain why the AI made a decision. If there is no clear governance framework around operating the agent, then we can't use it. Case in point > "nH predict"
I have build a narrow AI for credit decisioning on a 100B portfolio between 2012 and 2020. This "agent" can make autonomous credit decisions, if and only if the agent is 100% certain that all inputs are accurate. The value comes from the workflow, not the model.
LLMs change this as there is now a general, I like to call them vanilla models, that does not specifically be trained to the data set. Would I use that in this workflow? Likely not.
(a) it is likely that the narrow model is cheaper to operate than a larger model without seeing a substantial benefit in productivity.
(b) in regulated industries we always need to be able to explain why the AI made a decision. If there is no clear governance framework around operating the agent, then we can't use it. Case in point > "nH predict"