One thing I’ve noticed when experimenting with agent pipelines is that the “single-purpose agent” model tends to make both cost control and reasoning easier. Each agent only gets the context it actually needs, which keeps prompts small and behavior easier to predict.
Where it gets interesting is when the pipeline starts producing artifacts instead of just text — reports, logs, generated files, etc. At that point the workflow starts looking less like a chat session and more like a series of composable steps producing intermediate outputs.
That’s where the Unix analogy feels particularly strong: small tools, small contexts, and explicit data flowing between steps.
Curious if you’ve experimented with workflows where agents produce artifacts (files, reports, etc.) rather than just returning text.