IVQ 151-200

Security, Compliance & Governance

1. How do you handle authentication/authorization in LangGraph workflows?

2. Can you restrict access to specific nodes or state variables in LangGraph?

3. How do you ensure compliance (e.g., GDPR, HIPAA) in LangGraph-based apps?

4. How do you sanitize or redact sensitive data flowing through LangGraph?

5. Can LangGraph workflows be signed or verified for integrity?

6. How do you audit data access within a LangGraph pipeline?

7. Can LangGraph support RBAC (role-based access control) for workflow triggering?

8. How do you integrate vault-based secret management with LangGraph nodes?

9. What logging best practices ensure LangGraph is compliant for regulated industries?

10. How can you encrypt state and outputs at rest or in transit within LangGraph?

Performance & Optimization

1. How do you profile LangGraph workflows for bottlenecks?

2. What is the overhead of LangGraph versus raw Python LLM pipelines?

3. How do you limit API/token usage per LangGraph run?

4. How can caching be implemented in LangGraph workflows?

5. How do you manage compute-intensive operations in LangGraph?

6. How does LangGraph handle backpressure or rate-limiting?

7. Can LangGraph workflows be checkpointed or resumed efficiently?

8. What strategies help reduce latency in multi-hop LangGraph executions?

9. How do you batch node executions in LangGraph for throughput?

10. What is the best way to parallelize retrieval + reasoning steps in LangGraph?

Generative AI & LLM-Specific Workflows

1. How do you design a RAG pipeline using LangGraph?

2. How do you orchestrate summarization + Q&A steps in LangGraph?

3. Can LangGraph switch LLM providers mid-workflow (e.g., OpenAI → Claude)?

4. How do you add guardrails (e.g., content filtering) to LLM output in LangGraph?

5. How do you add prompt templates and modify them dynamically in LangGraph?

6. How do you integrate multi-modal input (text, image) in LangGraph?

7. How do you structure complex tool-using agents with LangGraph?

8. How do you log token-level LLM responses for LangGraph debugging?

9. How do you combine LangGraph with embedding search (e.g., via Qdrant)?

10. How do you A/B test LLM behavior across LangGraph paths?

Multi-Agent & Conversational Reasoning

1. How do you define agents as modular LangGraph nodes?

2. Can multiple agents collaborate and exchange memory via LangGraph?

3. How do you model planning → execution → evaluation cycles in LangGraph?

4. How do you control turn-based conversation in a LangGraph chat loop?

5. How can LangGraph model decentralized agent behavior?

6. How do you assign agent roles and capabilities inside LangGraph?

7. How do you share global context across agents in LangGraph?

8. How do you resolve agent conflicts or contradictory outputs in LangGraph?

9. Can LangGraph act as the controller for agent swarm protocols?

10. How do you simulate user-agent conversation for testing LangGraph loops?

Deployment, Edge, and Future Strategy

1. Can LangGraph be deployed to edge devices or browser environments?

2. What are the limitations of running LangGraph offline?

3. How do you deploy LangGraph workflows via serverless functions?

4. How does LangGraph integrate with LLMs hosted on private infrastructure?

5. Can LangGraph control robotic systems or physical agents?

6. How might LangGraph evolve to support vision + audio agents?

7. What changes are needed for LangGraph to support event-based workflows?

8. Can LangGraph orchestrate AI microservices across distributed systems?

9. What is the roadmap for LangGraph community plugins or ecosystem tools?

10. How do you future-proof LangGraph workflows for evolving model APIs?