ML Pipelines vs AI Pipelines: Why Decision Systems Are Different
Updated
•1 min read
Traditional ML pipelines move data.
AI pipelines move decisions.
ML Pipelines
Extract → Transform → Train → Predict
Linear.
Stateless.
Deterministic.
AI Pipelines
Observe → Decide → Act → Learn
Cyclic.
Stateful.
Adaptive.
What AI Pipelines Require
Memory
Tool orchestration
Feedback loops
Policy enforcement
They resemble control systems, not ETL jobs.
Architectural Implication
AI pipelines must be designed like distributed systems.
With:
Retry logic
State management
Observability
Final Thought
ML predicts.
AI decides.
That changes everything.
