CodeJedi

CodeJedi is a high-performance AI platform engineered for technical skill acquisition and automated developer assessments. By 2026, CodeJedi has transitioned from a simple coding tutor to a sophisticated RAG-enhanced (Retrieval-Augmented Generation) environment that integrates directly with proprietary internal codebases and global competitive programming standards. Its architecture utilizes a mixture-of-experts (MoE) model to provide context-aware debugging and real-time architectural advice. The platform serves two primary cohorts: individual developers aiming for elite technical roles and enterprise engineering managers seeking objective, automated evaluations of candidate performance. Unlike generic LLMs, CodeJedi employs a specialized 'Code-Logic' layer that verifies the execution and complexity of generated snippets against a virtualized sandbox. This ensures that the AI's suggestions are not only syntactically correct but also optimized for memory and time complexity (Big O). Its 2026 market positioning places it as the bridge between theoretical CS education and production-ready engineering standards, offering a gamified yet rigorous path to mastery through its 'Path-to-Architect' curriculum.