•1 min read•from InfoQ
Article: Runtime-Agnostic AI Workflows: A Pattern for Production Durability and Fast Eval Iteration
AI workflows have two needs that trade off directly. Running reliably in production requires persisting and distributing every step so it survives crashes, deploys, and restarts. But that same machinery is what makes runs too heavy for the fast, throwaway loop you need to check an LLM's output quality. The properties that buy durability are the ones that kill iteration speed.
By Mateus MouryWant to read more?
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Tagged with
#AI workflows
#Production durability
#Fast iteration
#LLM
#Output quality
#Runtime-agnostic
#Persisting
#Distributing
#Crashes
#Deploys
#Restarts
#Production environment
#Iteration speed
#Throwaway loop
#Reliability
#Pattern
#AI
#Workflow management
#Scalability
#Machine Learning