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AI Inference EngineeringQuantization, batching and KV caching in production.System DesignScalable systems from first principles.Context EngineeringDesigning the context that LLMs actually reason over.Docker & KubernetesContainers and orchestration, explained.

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AI Inference Engineering

Model Optimization3

Serving Systems4

Hardware & Compilation3

Advanced Serving Techniques4

Serving Many Fine-Tunes at Once with Multi-LoRA
Structured Output and Guided Decoding
Model Routing and Semantic Caching
Test-Time Compute and Reasoning Models

Benchmarking & Evaluation5

Scaling & Deployment3

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AI Inference Engineering

Model Optimization3

Serving Systems4

Hardware & Compilation3

Advanced Serving Techniques4

Serving Many Fine-Tunes at Once with Multi-LoRA
Structured Output and Guided Decoding
Model Routing and Semantic Caching
Test-Time Compute and Reasoning Models

Benchmarking & Evaluation5

Scaling & Deployment3

Learn AI Inference Engineering Advanced Serving Techniques

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Model Routing and Semantic Caching

You don't need your biggest, most expensive model to answer "what's 2+2". Sending every request to the same model is leaving money on the table.

9 min readUpdated 2026-09-03ai-inferenceroutingsemantic-cachingadvanced-serving