/ml-pipeline

Design an ML system for a problem

# Design ML Pipeline

Design an end-to-end ML system architecture for a given problem.

## Arguments

`$ARGUMENTS` - The ML problem to design for (e.g., "recommendation system", "fraud detection", "search ranking", "content moderation")

## Workflow

1. **Clarify requirements** by understanding:
   - What predictions are being made?
   - What is the latency requirement? (real-time vs batch)
   - What is the scale? (QPS, data volume)
   - Who are the consumers of predictions?

2. **Load relevant skills** based on the problem:
   - Core ML architecture → `ml-system-design`
   - LLM-based syst...