25 August 2025

#Spring_AI

#Spring_AI
Level Topic Subtopics
Basic Introduction to Spring AI What is Spring AI, Role of AI in Spring Apps, Overview of LLM Integration, Use Cases in Applications, Benefits of AI with Spring
Spring AI Setup Adding Spring AI dependencies, Configuration Basics, API Keys Management, Connecting with OpenAI/LLMs, Simple AI Service Example
Prompt Engineering Basics Prompt Structure, Few-shot Prompts, Zero-shot Prompts, Prompt Variables, Handling AI Responses
REST API with AI Creating AI-backed REST endpoints, Handling JSON Responses, Simple Text Completion API, Basic Error Handling, Returning AI Results
Intermediate AI Integration with Spring Boot Service Layer Integration, Async Calls with AI APIs, Handling Timeouts, Error Recovery, Logging AI Calls
Advanced Prompt Engineering Multi-turn Prompts, Chaining Prompts, Contextual Memory, Structured Outputs, Guardrails
Data Access + AI Using AI for Query Generation, AI-Assisted Search, Vector Databases with Spring Data, RAG (Retrieval-Augmented Generation), Caching AI Results
Spring AI Observability Logging AI Requests/Responses, Metrics Collection, Distributed Tracing, Monitoring Performance, Debugging AI Behavior
Security in Spring AI Securing API Keys, Rate Limiting, Handling Sensitive Data, Input Validation, AI Safety Basics
Advanced AI Orchestration Multi-Model Orchestration, Model Selection Strategies, Chained AI Workflows, Using Agents in Spring, Async Orchestration
Spring AI + LangChain4j LangChain4j Basics, Integrating with Spring, Creating Chains, Using Tools, Memory in LangChain4j
AI + Databases SQL Generation, Natural Language to SQL, Query Optimization with AI, Using AI for Schema Mapping, Intelligent Data Access
AI for Business Workflows AI in E-commerce, AI for Recommendations, AI for Fraud Detection, Document Processing, Chatbots
Testing Spring AI Applications Unit Testing AI Integrations, Mocking AI Responses, Contract Testing, Load Testing AI Services, Regression Testing with AI
Expert Scaling AI in Spring Running AI in Production, Horizontal Scaling, Caching Strategies, Performance Tuning, Load Balancing AI Services
Enterprise Security + AI Enterprise Authentication (OAuth2, JWT), Data Privacy, Responsible AI Guidelines, PII Handling, Auditing
AI Deployment Strategies On-Prem LLM Integration, Hybrid Cloud AI, Model Fine-Tuning, Model Hosting, Custom AI Endpoints
Emerging Trends in Spring AI RAG at Scale, Multi-Agent Systems, AI Governance, Observability 2.0, AutoML Integration
Best Practices & Pitfalls Avoiding Hallucinations, Cost Optimization, Versioning Prompts, Failover Strategies, Continuous Improvement

1. Spring AI Basics

  1. What is Spring AI and why is it used?
  2. How does Spring AI integrate with Large Language Models (LLMs)?
  3. Difference between Spring AI and directly calling an AI API.
  4. What are the benefits of using Spring AI in enterprise applications?
  5. Explain a basic use case of Spring AI in a REST API.
  6. How do you add Spring AI dependencies in a Spring Boot project?
  7. How do you configure API keys in Spring AI?
  8. What are the supported LLM providers in Spring AI?
  9. How do you create a simple text completion service in Spring AI?
  10. How do you handle AI responses in JSON format?
  11. What is prompt engineering in the context of Spring AI?
  12. Difference between zero-shot and few-shot prompting.
  13. How do you pass dynamic variables into a prompt?
  14. What are guardrails in AI prompt design?
  15. How does Spring AI handle error responses from LLMs?
  16. How do you log AI requests and responses in Spring AI?
  17. What is the difference between synchronous and asynchronous calls to AI APIs?
  18. How do you test a basic AI-powered Spring Boot application?
  19. How do you secure API keys in Spring applications?
  20. What are common challenges with integrating AI into Spring?
  21. Explain how Spring AI can be used in a chatbot application.
  22. What is the role of Spring Boot in Spring AI projects?
  23. How do you version and manage AI prompts in Spring AI?
  24. What is a typical architecture for AI-enabled microservices?
  25. Best practices for starting with Spring AI.

2. Intermediate Spring AI

  1. How do you design service layers that interact with AI models?
  2. What are async calls in Spring AI and why are they important?
  3. How do you handle timeouts in AI calls?
  4. How do you implement retry mechanisms for failed AI requests?
  5. Explain advanced prompt engineering techniques.
  6. How do you maintain conversation context across multiple AI calls?
  7. How do you ensure structured outputs from AI models?
  8. What is Retrieval-Augmented Generation (RAG) in Spring AI?
  9. How do you integrate vector databases with Spring AI?
  10. Explain caching strategies for AI results.
  11. How do you log and monitor AI calls in Spring?
  12. How do you implement distributed tracing for AI services?
  13. How do you measure AI performance in a Spring application?
  14. What are common security issues in Spring AI applications?
  15. How do you implement rate limiting for AI services?
  16. How do you validate user inputs for AI queries?
  17. What is AI safety in Spring AI?
  18. How do you prevent sensitive data leakage in AI responses?
  19. How do you implement feature toggles for AI functionality?
  20. Explain integration of Spring AI with external APIs.
  21. How do you handle bulk AI requests efficiently?
  22. How do you implement concurrency controls in AI services?
  23. How do you monitor cost usage for AI API calls?
  24. What is role-based access control for AI endpoints?
  25. Common mistakes developers make in intermediate Spring AI projects.

3. Advanced Spring AI

  1. How do you orchestrate multiple AI models in Spring?
  2. Explain multi-model routing in Spring AI.
  3. How do you chain multiple AI calls into workflows?
  4. What are agents in Spring AI and how are they implemented?
  5. Explain async orchestration in Spring AI pipelines.
  6. What is LangChain4j and how does it integrate with Spring AI?
  7. How do you use LangChain4j chains with Spring Boot?
  8. How do you implement memory in LangChain4j with Spring?
  9. How do you use AI for SQL query generation in Spring?
  10. How does AI assist in schema mapping in Spring Data?
  11. How do you implement AI for intelligent search?
  12. Explain AI-powered recommendations with Spring Boot.
  13. How do you use AI for fraud detection in Spring applications?
  14. How do you build an AI-powered document processing pipeline?
  15. Explain AI-powered chatbots with context memory in Spring AI.
  16. How do you integrate Spring AI with Kafka for event-driven AI?
  17. How do you implement circuit breaker patterns for AI calls?
  18. How do you optimize AI performance for low latency in Spring apps?
  19. How do you implement caching layers for repeated AI queries?
  20. Explain AI-powered anomaly detection with Spring.
  21. How do you handle streaming AI responses in Spring WebFlux?
  22. How do you build a multi-turn conversational flow in Spring AI?
  23. What are key challenges in integrating AI with enterprise databases?
  24. How do you implement distributed AI inference in Spring apps?
  25. Best practices for advanced AI integration in Spring.

4. Expert Spring AI

  1. How do you scale Spring AI applications in production?
  2. What are best practices for running AI services in Kubernetes?
  3. How do you implement horizontal scaling for AI workloads?
  4. How do you optimize AI cost in large-scale Spring deployments?
  5. How do you secure AI services with OAuth2 and JWT?
  6. What are responsible AI guidelines for enterprises?
  7. How do you implement privacy-preserving AI in Spring?
  8. How do you handle Personally Identifiable Information (PII) in AI?
  9. How do you implement auditing for AI services in enterprises?
  10. How do you integrate on-prem LLMs with Spring AI?
  11. Hybrid cloud AI: how do you combine on-prem and cloud AI?
  12. How do you fine-tune models and integrate them with Spring AI?
  13. How do you host custom AI models in Spring Boot?
  14. How do you implement enterprise-wide governance for AI?
  15. What is observability 2.0 for Spring AI services?
  16. How do you build multi-agent AI systems in Spring?
  17. What is the role of AutoML in Spring AI applications?
  18. How do you implement versioning and rollback strategies for AI prompts?
  19. What is the future of RAG (Retrieval-Augmented Generation) in Spring AI?
  20. How do you implement failover strategies for AI endpoints?
  21. What are key pitfalls in enterprise AI adoption with Spring?
  22. How do you balance performance and accuracy in AI-powered services?
  23. What are compliance requirements (e.g., GDPR, HIPAA) for AI in Spring?
  24. How do you ensure continuous improvement in AI-based applications?
  25. Emerging trends in Spring AI and enterprise adoption.
-
Labels: , ,
Subscribe to: Comments (Atom)