Comment by wtetzner
15 days ago
I think the problem is that we're using LLMs to do too much of the work. We should aim to design agents that use the LLM as the thinnest possible layer to translate the natural language intent into a deterministic process, minimizing round trips to the LLM as much as possible.
This becomes clear to anyone that wants to do marginally complex work. Developing pipelines that combine pre-processing flows, semantic targeting, and minimal contextual calls to an LLM API gets you powerful automated steps. Combined with separate validation steps, LLMs go from toys to useful.
A process isn't automated until neither human nor genie is in the loop.