Graph Engineering: from 1 prompt to 100 agents in one system删掉不存在的箭头：从 1 条 prompt 到 100 个 agent 的图工程八步
This article argues that the workflow itself is the engineering target: alongside prompt, context, harness, and loop engineering, there is a fifth layer the author calls graph engineering. The core observation is that default linear agent flows confuse sequence with dependency: most arrows do not read an upstream result, so cutting them is what enables real parallelism. A hundred agents, in this view, are not a hundred roles but one role instantiated a hundred times with its own slice of the problem. The eight-step method covers node contracts, four topologies (chain, fan, router, controlled cycle), when joins are worth waiting for, separating probabilistic classification from deterministic routing, placing independent verifier nodes, and keeping durable state. It explicitly warns that parallel breadth is expensive, citing Anthropic's multi-agent research system consuming roughly 15x the tokens of a normal chat. Useful for engineers moving from a single prompt to a multi-agent production system, though there is no runnable code.