10 copy-paste AI prompts for reviewing and improving Java code quality. Covers SOLID violations, thread-safety bugs, virtual thread carrier pinning, N+1 query patterns, resource leaks, exception handling, null safety, logging quality, and full quality audits. Works in Claude, ChatGPT, Gemini, and Cursor.
10 copy-paste AI prompts for Spring Boot development. Covers scaffolding REST endpoints, configuring Spring Security JWT, debugging autoconfiguration, global exception handling, production tuning, Actuator health checks, CORS, caching, and migrating from Spring Boot 2.x to 3.x. Works in Claude, ChatGPT, Gemini, and Cursor.
A deep-reference guide to Spring Data JPA covering the full JpaRepository hierarchy, derived query methods, @Query JPQL and native queries, Specifications, pagination, interface and class/record projections, @Transactional rules, and entity auditing with @CreatedDate — with fully annotated production-grade code examples and a decision matrix for choosing the right query strategy.
A deep-reference guide to Java Records — the concise, immutable data-carrier syntax introduced in Java 16 and matured in Java 21. Covers declaration syntax, compact constructors, custom accessors, equals/hashCode/toString behaviour, records with Jackson, records with Hibernate, records in Spring Boot, and key limitations — with fully annotated code examples and a comparison to plain Java classes.
A complete reference guide to Java Generics: generic classes and methods, bounded type parameters, wildcards, the PECS rule, type erasure, generic interfaces, common pitfalls, and AI prompts to modernise raw-type code.
The runnable companion to the Spring AI 2.0 LLM gateway article: clone the module, run the tests with no API key or Docker, read the configuration, and see what the gateway answers over HTTP.
A complete Spring Boot 4.1 and Spring AI 2.0.1 RAG project, file by file: the pgvector schema, configuration, wiring, endpoints and a real end-to-end run. The tests use scripted models, and the page says so wherever an answer appears.
Build and test an LLM gateway on Spring AI 2.0: hint-based routing, failover that works with the new tool-calling advisor, one circuit breaker per provider, token and dollar caps, and a semantic cache. Every number comes from a run.
A Spring AI 2.0 RAG pipeline on Spring Boot 4.1, taken apart one stage at a time on a real PostgreSQL with pgvector: chunking, once-only PDF ingestion, the similarity threshold that is off by default, injection-proof tenant filters, reranking and answer checks. Every number comes from a committed transcript, and the page says plainly what was scripted.
Records, pattern-matching switch, virtual threads, sequenced collections, scoped values and structured concurrency from Java 21 to Java 25 LTS, each compiled and run on JDK 21, 25, 26 and 27: what is really final, when virtual threads stopped pinning, and what 26 and 27 mean for the road to Java 29.