LLM Architecture: System Design for Production AI
Design decisions for production LLM systems — routing, cost, guardrails, and multi-model orchestration. The layer between running models and building reliable AI applications.
LLM Architecture
Cost Optimization for LLM Systems: Where the Money Actually Goes
Spend tokens where they actually matter.
LLM costs scale linearly with usage. A system processing 10,000 requests a day at $0.01 per request costs $100 daily — $365 a year. At enterprise scale, that’s over $10,000.
LLM Guardrails in Practice: What Actually Works
Control the risk, not just the model.
LLMs are unpredictable. They hallucinate, leak data, generate harmful content, or refuse legitimate requests. Guardrails constrain model behavior without sacrificing capability.
Model Routing: Stop Using One Model for Everything
The right model for the right task.
Running a 70B parameter model to summarize a 200-word email is wasteful. Running a 3B model to review production code is reckless. Most systems live somewhere in between — and that’s where model routing comes in.
Multi-Model System Design: When One Model Isn't Enough
Pick the simplest pattern that works.
Single-model systems are simple. Multi-model systems are powerful. The challenge isn’t choosing models — it’s designing the architecture that orchestrates them.
Writing effective prompts for LLMs
Requires some experimenting but
Still there are some common approaches how to write good prompts so LLM would not get confused trying to understand what you wand from it.