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Phase 19 · System Design for AI Applications

Topics

Latency & Cost Optimization

Part of the AI Engineer Roadmap.

Summary

Reducing response time and per-request cost in an AI system — through smaller models for simple tasks, caching, batching and smarter prompt design.

How to Learn This

  • 1Profile a real AI pipeline you've built and identify the slowest/most expensive step.
  • 2Learn model-cascading: use a cheap model first, escalate to a stronger one only when needed.
  • 3Practice estimating cost-per-request for a hypothetical AI feature at scale.

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Designing Scalable AI Systems

Next

Caching LLM Responses

More topics in System Design for AI Applications

Designing Scalable AI SystemsCaching LLM ResponsesLoad Balancing AI WorkloadsDesigning a RAG System at ScaleDesigning a Recommendation SystemDesigning a Content Moderation SystemHandling High-Throughput InferenceChoosing Between Fine-Tuning and RAG
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