a practical look at building production systems with the anthropic claude sdk — tool use, streaming, mcp servers, and the projects i've shipped with it.

how i built an mcp server to expose 40+ gitlab operations as structured tools for ai clients — the protocol, the architecture, and what surprised me.

a deep dive into designing production multi-agent architectures — task routing, memory management, tool orchestration, and the pitfalls i hit along the way.

what actually changes when you move a rag system from a notebook to prod — chunking strategies, embedding choices, reranking, and async retrieval at scale.

a practical guide to fine-tuning open-source llms using peft and qlora — from dataset curation and formatting to training and quantised inference.

implementing ddpm in pytorch from first principles — the math behind forward and reverse diffusion, noise schedules, and training a small image model.