Definition
Graph engineering is the practice of designing an agent system as explicit nodes, state, and transitions so deterministic control and model judgment have visible boundaries. A node may contain ordinary code, a model call, a tool, or a complete agent. An edge describes what may happen next.
The graph earns its complexity when it exposes something the system must control: parallel work, resumable state, approval boundaries, retries, independent verification, or recovery. Drawing many agents as nodes does not create independent judgment. Agents that share a model, context, or assumptions can produce organized error.
Why it is contested
The phrase became prominent in a 2026 discussion around LangGraph, but no reliable primary record in this corpus establishes a single coiner or settled scope. It can refer to control flow, runtime task graphs, knowledge representation, or feedback relationships. Those practices use graphs for different purposes and are not interchangeable. This glossary uses the unqualified term only as an umbrella and names the graph type when the distinction matters.
Distinguish it from nearby terms
Control-graph engineering defines permitted paths. Execution-graph engineering manages instantiated work. Knowledge-graph engineering represents facts and relationships. Improvement graphs connect failures to corrective changes. Loop engineering is not the opposite of graph engineering because a loop is a cyclic graph.
Check your understanding
A system replaces one clear tool loop with a diagram of twelve agents, all using the same model and evidence. The graph adds coordination, but it has not added independent verification or a stronger boundary.