IVQ 101-150

Architecture & Design Patterns

1. How do you modularize LangGraph workflows into reusable components?

2. What’s the best way to separate business logic from workflow orchestration in LangGraph?

3. Can you dynamically reconfigure a LangGraph after deployment?

4. What architectural styles (e.g., DAG, FSM, Petri nets) inspire LangGraph?

5. How do you version control LangGraph workflows?

6. What design pattern does LangGraph most closely follow?

7. Can LangGraph workflows be persisted and resumed from a failure point?

8. How do you organize large-scale LangGraph projects with dozens of nodes?

9. How do you use decorators or wrappers for common behavior across nodes?

10. How do you integrate CI/CD practices into LangGraph development?

Observability & Monitoring

1. How do you log state changes across a LangGraph run?

2. How do you record inputs/outputs of each node in LangGraph?

3. Can LangGraph integrate with Prometheus, Grafana, or other observability tools?

4. How do you monitor failed executions or exceptions in LangGraph?

5. How can you emit structured logs from inside LangGraph nodes?

6. How do you create metrics or custom alerts based on LangGraph performance?

7. How do you track memory or token usage per node in LangGraph?

8. Can you enable distributed tracing (like OpenTelemetry) in LangGraph?

9. How do you perform root-cause analysis for failed workflows?

10. What tools exist to create dashboards for LangGraph workflows?

Tooling & Automation

1. Can you generate LangGraph code using a GUI or visual builder?

2. Is there a CLI for LangGraph to build, run, and test workflows?

3. How do you integrate LangGraph with GitHub Actions or other CI tools?

4. Can LangGraph automatically validate workflow logic before compile?

5. How can LangGraph help create agents that self-heal or retry intelligently?

6. Can you import/export LangGraph workflows as JSON/YAML?

7. How can LangGraph workflows be parameterized at runtime?

8. What scaffolding tools exist for LangGraph project creation?

9. Can LangGraph be deployed as a server for multi-user orchestration?

10. How do you automate deployment of LangGraph workflows in cloud environments?

Human-in-the-Loop & Decision Flow

1. How do you insert a human decision node inside a LangGraph?

2. How can you pause/resume LangGraph workflows based on human input?

3. How can LangGraph integrate Slack/email for manual decision gates?

4. What’s the best way to override or modify state manually in LangGraph?

5. Can LangGraph enforce audit trails on decision paths?

6. How do you simulate a user feedback loop in LangGraph?

7. Can LangGraph workflows include confidence scores and allow user override?

8. How do you involve SMEs (subject-matter experts) in validating LangGraph flows?

9. How do you build approval chains with LangGraph?

10. Can you enable annotation or labeling within LangGraph workflows?

Comparisons & Competitive Landscape

1. How does LangGraph compare to LangChain Expression Language?

2. What are the differences between LangGraph and Prefect?

3. How does LangGraph compare with n8n for workflow building?

4. How does LangGraph relate to Microsoft’s Semantic Kernel Planner?

5. What advantages does LangGraph have over Airflow for LLM workflows?

6. How does LangGraph's design simplify multi-agent reasoning?

7. What are LangGraph’s trade-offs versus using Hugging Face Transformers with custom orchestration?

8. Is LangGraph better suited for async or sync pipelines?

9. How does LangGraph compare with Autogen’s conversational agent graphs?

10. When should you choose LangGraph over a plain Python LLM pipeline?