Comment by empath75

I have heard this sort of thing a lot from people working with agents, and I just think it's fundamentally misguided as a way to think of them, and if you work with them this way, you are probably setting money on fire for no reason because the tasks you are able to perform this way _don't need agents to begin with_.

You might use an LLM api call here as a translation or summary step in a deterministic workflow, but they are not acting as agents, because they lack _agency_.

The value of using an agent harness is precisely that they are _not deterministic_. You provide agents a goal, tools and constraints and they do the task they were asked to perform as best as they can figure out how to do it. You may provide them deterministic workflows as tools they can call, but those workflows, outside of the agent harness itself, should not constrain what the agent does. You are paying a lot of money for agent reasoning, not to act as an expensive data transformation pipeline.

It may be the case that a lot of agentic workflows are more properly done with fully deterministic workflows, but the goal there should be to _remove the agents entirely_ and spend those tokens on non deterministic tasks that require agentic decision making.

I do think there are fundamental limits to what agents are capable of doing unsupervised and there does need to be a lot more human guidance, observability and control over what they are doing, but that's sort of the opposite of embedding them in deterministic workflows, that is more of team integration/communication problem to solve.