AI Workflow Challenges

Introduction

Ten workflow design challenges: DAGs, parallelism, retries, durability, human-in-loop. Use any orchestrator (LangGraph, Inngest, Temporal).

Understanding the topic

Core concepts:

• Sequential summariser pipeline.
• Parallel fan-out / fan-in research workflow.
• Decision-tree router for ticket triage.
• Workflow with human-in-loop approval.
• Durable workflow that survives crashes.
• Sub-workflow composition.
• Workflow with conditional retries.
• Workflow with budget cap + early stop.
• Workflow versioning with feature flag rollout.
• Workflow with event-driven triggers (webhook + cron).

Syntax reference

Visual workflow / architecture:

┌──────────────┐
│   Exercise   │
└──────┬───────┘
       ▼
  Build · Test · Eval
       │
       ▼
  Compare with model answer

Real-world use

These mirror designs you'll see at Inngest, Temporal, LangGraph users in production.

Best practices

• Draw the DAG before coding.
• Force a kill switch in every workflow.

Common mistakes

• Workflows that hang silently — always add timeouts.

Hands-on exercise

Interview preparation — practice these questions:

• Q1. Why a DAG over a list?
• Q2. Two patterns for human-in-loop.
• Q3. Scenario: a workflow step deadlocks. Three debugging steps?