Context Engineering: The Discipline Behind Reliable LLM Applications
Prompt engineering is shrinking inside the model. Context engineering — choosing what goes into the window — is now the lever for quality, cost, and reliability.
Rag
The Hardest RAG Ingestion Problems and How Engineers Actually Solve Them
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.
Graphify Replaces the RAG Vector Store: Why Graph-Based Retrieval Is the Next Leap
Graph-based retrieval is displacing the pure vector store in production RAG stacks. Here is how Graphify works, why it outperforms flat embeddings on multi-hop questions, and what it takes to migrate.
Architecting Retrieval-Augmented Generation Systems: A Deep Dive into Production Pipelines
How to design Retrieval-Augmented Generation pipelines that hold up in production — covering indexing, hybrid retrieval, reranking, evaluation harnesses, and the operational realities of freshness, latency, and cost.
The Complete AI Agent Architecture: From Perception to Action
A field guide to designing production AI agents — from perception and reasoning loops to memory, tool routing, and the orchestration patterns that keep them reliable at scale.