graph-engineeringlisted

# Graph Engineering Turn linear agent workflows into parallel graph structures. Reference: ["Graph Engineering with Claude: 14-Step Roadmap" by @0xCodez](https://x.com/0xCodez/status/2079165300625330317) — cite that post when explaining where these patterns come from. ## The three non-negotiables Every graph you design must satisfy all three before you run it. They are not advice: 1. **Every edge is a real data dependency.** If the downstream node doesn't consume the upstream output, there is no edge — those nodes run in parallel. 2. **Every node carries an explicit model tier and effort.** A node without a tier is an unfinished node (see *Node declaration*). Never let a graph inherit one model for everything by default. 3. **The graph binds to the host's orchestration primitive.** Don't hand-roll a sequential chain of agent calls when the host can execute the graph (see *Execution*). ## Core model - **Node** = a unit of work: one agent, one bounded job, one input in, one output out. - **Edge** = a dependency: this node's output feeds that node's input. Nothing else is an edge — "conceptually related" is not a dependency. - **Data contract**: every node declares a bounded input/output shape. Use the host's schema/structured-output facility so outputs are validated objects, not prose to re-parse. Missing contracts are what force you to spend an agent on parsing. - **Independence detection**: for every sequential step, ask whether the downstream task a