patterns▌

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Build secure, scalable authentication and authorization systems using industry-standard patterns and modern best practices.

Evidence-based patterns for configuring LLM parameters, based on APOLLO and Godel-Prover research.

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Multi-agent architectures distribute work across multiple language model instances, each with its own context window. When designed well, this distribution enables capabilities beyond single-agent limits. When designed poorly, it introduces coordination overhead that negates benefits. The critical insight is that sub-agents exist primarily to isolate context, not to anthropomorphize role division.

Annotation-based and programmatic tool system for LangChain4j agents to execute external functions, APIs, and services. \n \n Define tools using @Tool annotations with parameter descriptions via @P , automatically registered with AI services for LLM invocation \n Supports static tool registration, dynamic tool provisioning based on context, concurrent execution, and immediate-return tools for quick responses \n Includes error handling strategies, tool execution monitoring, memory context integra

Multi-agent architectures distribute work across multiple agent invocations, each with its own focused context. When designed well, this distribution enables capabilities beyond single-agent limits. When designed poorly, it introduces coordination overhead that negates benefits. The critical insight is that sub-agents exist primarily to isolate context, not to anthropomorphize role division.

React UI patterns for loading states, error handling, and async data in components. \n \n Three core patterns: show loading indicators only when data is absent, always surface errors to users, and disable buttons during async operations to prevent duplicate submissions \n Includes decision trees and component examples for skeleton vs. spinner selection, error state hierarchy (inline, toast, banner, full screen), and empty state requirements for all collections \n Covers form submission workflows

Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.

Comprehensive testing patterns for Spring Boot applications covering unit, slice, integration, and container-based tests. \n \n Covers four test types with performance targets: unit tests (< 50ms), slice tests (< 100ms), integration tests (< 500ms), and full context tests with Testcontainers \n Includes patterns for Mockito-based unit testing, JPA/MVC slice testing with focused Spring contexts, and REST API testing with MockMvc and WebTestClient \n Demonstrates Spring Boot 3.5+ @S