GenRec replaces a stack of hand-engineered ranking models with a single fine-tuned LLM that scores items from natural-language context. Here is the architecture, the training loop, and what production teams should know before shipping it.
Claude loop engineering is the practice of building bounded, observable, tool-using agentic workflows on top of Anthropic’s Claude. This post covers loop anatomy, stop conditions, tool design, and the production patterns that keep agents from drifting, looping forever, or burning budget.
Prompt engineering is shrinking inside the model. Context engineering — choosing what goes into the window — is now the lever for quality, cost, and reliability.
A working engineer’s journal of fine-tuning a small open-source LLM with LoRA on a custom dataset — the full pipeline, the surprises, and the measurable results.
Most RAG failures start long before the LLM is ever called. This post walks through the five hardest ingestion problems and the patterns teams use to fix them in production.