> Hmm, maybe you are referring to something specific with "workflow". I'm envisioning a visual graph with a UI for each node and connection, or maybe a makefile on the other end of the spectrum. What are you envisioning?
In job orchestration systems, workflows are structured sequences of tasks that define how data moves and transforms over time. Workflows are typically defined as Directed Acyclic Graphs (DAGs) but they don't have to be. I don't believe I am referring to anything more specific than how orchestration systems generally use them. LLM-based agents shift the focus from rigidly defined transitions to adaptable problem-solving mechanisms. They don’t replace state machines entirely but introduce a layer where strict determinism isn’t always necessary or even desirable.
> Anyway, LLMs will remain at "cool software" like other niche-specific patterns until I see something general emerge. You'd have to pitch LLMs pretty savvily to show it as a clear value-add. Engineers are extremely expensive, so LLMs need to have a very low error rate to be integrated into the revenue-path of a product to not incur higher costs or a lower-quality service. I still see text- and code-generation for immediate consumption by a human (or possible classification to be reviewed by a human) as the only viable uses cases today. It's just way too easy to manipulate them with standard English.
I get the skepticism, especially about error rates and reliability. But the “cool software” label underestimates where this is heading. There’s already evidence of LLMs being useful beyond text/code-gen (e.g., structured reasoning in research, RAG-enhanced search, or dynamically adapting workflows based on complex input). The real shift isn’t just about automation but about adaptive automation, where LLMs reduce the need for brittle, predefined paths.
Of course, the general-use case is still evolving, and I agree that direct, high-stakes automation remains a challenge. But dismissing LLM-driven agents as just niche tools ignores their growing role in augmenting traditional software paradigms.