Nodes, edges, conditional edges, and routing
Practice this questionWANT TO UNDERSTAND THE CONCEPT FIRST?Learn Nodes, edges, conditional edges, and routing
Overview
- A node is a function performing one graph step.
- An edge describes the next step, while a conditional edge selects from allowed destinations based on state.
- Routing can use model output, deterministic checks, or both.
Why this matters
Explicit transitions make failure paths and allowed actions reviewable.
An everyday example
A hospital sends a case to a specific department depending on validated symptoms and rules.
A technical example
intent === "claim_status" selects claim lookup; unsupported intent selects clarification.
How it works
- Run node
- Validate/update state
- Router selects named destination
- Execute next node
- Terminate at a defined endpoint.
Architecture and flow
Node → bounded route → allowed next node.
The insurance assistant example
A model can select “create draft”; only a deterministic approval check can select “submit approved draft.”
When to use it
Branching tasks and explicit retry/escalation paths.
When to avoid it
Do not let model text become a dynamically imported node name or arbitrary endpoint URL.
Interview answer
“Nodes perform work and edges control execution. I validate model-derived routing and use business rules to control consequential transitions.”
Benefits, trade-offs, and production considerations
- Each node should have a clear input, output, deadline, and failure contract.
- Keep business services independently testable and avoid a giant node containing the whole agent.
Adapted from 13_AI.MD · “Nodes, edges, conditional edges, and routing”. Code examples are study fragments. Difficulty and core labels are editorial estimates; version-specific behavior should be checked against your project.