How AI code review tools work, key features, pitfalls, and a step-by-step plan to pilot them in your engineering workflow.
A practical blueprint for preventing prompt injection in LLM apps: threat models, mitigations, code patterns, testing, and operations.
Design robust REST API health check endpoints: liveness vs readiness, payload schema, dependencies, security, caching, and production-ready examples.
A practical guide to integrating an AI writing assistant via API—architecture, prompt design, code samples, safety, evaluation, and performance optimization.
Build a production-grade semantic search with embedding models: data prep, indexing, similarity, hybrid retrieval, re-ranking, evaluation, and scaling.
Clear rules for naming API resources, fields, and events across REST, GraphQL, and gRPC—with examples, pitfalls, and a practical checklist.
