Agent engineering emerges as a discipline for reliable LLM systems

LangChain has published an argument for “agent engineering” as a distinct discipline. The post frames reliable LLM systems as a blend of product thinking, software engineering, and data science.

That framing matters because agents are not just prompts. They involve tools, memory, evaluations, workflows, user experience, and iterative testing under real-world constraints.

As agent products move into production, teams need repeatable engineering practices rather than one-off demos that are difficult to debug or improve.