AI Systems Design Guides
Production-grade deep dives into LLM infrastructure, inference optimization, and AI architecture patterns. Written for engineers building and interviewing at the frontier.
Vector Database Selection Guide: Pinecone vs Weaviate vs pgvector
A benchmark-driven comparison of the top vector databases for production RAG. Recall@k, indexing speed, query latency, and cost at 1M, 10M, and 100M vectors, so you can make the right call before you build.
Multi-Agent Orchestration Patterns
Router, pipeline, and supervisor patterns for multi-agent LLM systems. When each pattern breaks, and the trade-offs between LangGraph, custom orchestration, and raw API calls.
LLM Inference Optimization: KV-Cache, Continuous Batching & Quantization
How to reduce LLM serving cost and latency by 5–10x. Covers KV-cache mechanics, continuous batching with PagedAttention, GPTQ/AWQ quantization, and speculative decoding, with numbers.
Designing a RAG Pipeline at Scale
End-to-end design of a production Retrieval-Augmented Generation system: chunking strategies, embedding models, vector DB selection, reranking, and the failure modes that surface at 10M+ documents.