AI Agent Engineering
Masterclass-style writing for teams building AI agents that move beyond demos and survive in production.
Latest articles
Vendor-neutral guides with diagrams, developer examples, business context, and practical checklists for agentic AI systems.
From Prompt Engineer to Agent Engineer: The 7 Skills That Actually Matter
A job posting asked for a prompt engineer with distributed systems, API design, MLOps, security, and product management experience. That's not a prompt engineer — that's five people. Here's the real skill stack.
What is RAG? Retrieval-Augmented Generation Explained (2026)
RAG (Retrieval-Augmented Generation) gives a language model access to your own data before it answers. The model retrieves matching documents from a vector database, adds them to its prompt as context, and generates a response grounded in those documents. Here is how it works, what it costs, and when to use it.
What is an Embedding? Vectors for Meaning, Explained (2026)
An embedding is a list of numbers that captures the meaning of text, an image, or audio in a fixed-length vector. Similar things have similar vectors. Embeddings power semantic search, RAG, clustering, classification and recommendation. Here is how they work, what they cost, and which one to use.