No it's more like if you knew how to build it before - LLM agents help you build it faster. There's really no useful analogy I can think of, but it fits my current role perfectly because my work is constantly interrupted by prod support, coordination, planning, context switching between issues etc.
I rarely have blocks of "flow time" to do focused work. With LLMs I can keep progressing in parallel and then when I get to the block of time where I can actually dive deep it's review and guidance again - focus on high impact stuff instead of the noise.
I don't think I'm any faster with this than my theoretical speed (LLMs spend a lot of time rebuilding context between steps, I have a feeling current level of agents is terrible at maintaining context for larger tasks, and also I'm guessing the model context length is white a lie - they might support working with 100k tokens but agents keep reloading stuff to context because old stuff is ignored).
In practice I can get more done because I can get into the flow and back onto the task a lot faster. Will see how this pans out long term, but in current role I don't think there are alternatives, my performance would be shit otherwise.
You could probably replace LLM with "junior engineer" here as it sounds like you're basically a manager now. The big negative that LLMs have in comparison with junior engineers is that they can't learn and internalise new information based on feedback.
"The big negative that LLMs have in comparison with junior engineers is that they can't learn and internalise new information based on feedback."
No, but they can take "notes" and can load those notes into context. That does work, but is of course not so easy as it is with humans.
It is all about cleaning up and maintaining a tidy context.