AI EngineeringInterview preparation
Intermediate·Concept·2 min read

Nodes, edges, conditional edges, and routing

Practice this question

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

  1. Run node
  2. Validate/update state
  3. Router selects named destination
  4. Execute next node
  5. 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.