Claude Code, developed by Anthropic, recently had its entire source code leaked on GitHub. The code includes around 1,900 files primarily written in TypeScript. A close examination reveals several noteworthy engineering decisions that distinguish Claude Code from OpenAI's Codex, particularly in how they handle user input and manage session context. When a user types a message, the system processes it through a series of steps, ultimately yielding a response based on a continuous event stream. This differs from Codex's approach, which relies on a Rust-based structure for handling interactions. Claude Code employs a four-tiered compaction strategy to manage the limitations of the LLM's context window. It proactively monitors token count and summarizes older messages when nearing the limit. If this proactive measure fails, a reactive fallback compacts the messages on-the-fly. The system also features a "snip compaction" mode for headless sessions, which truncates output while preserving full history for interactive use. Claude Code's handling of context is more defensive and complex compared to Codex's simpler, diff-based method that minimizes data sent per turn. The system prompt itself is intricately designed, combining static behavioral instructions with session-specific information. A unique boundary marker allows for efficient caching, leading to better performance by reusing around 3,000 tokens of instructions across users. Internal users receive specialized instructions that guide the model to avoid common pitfalls, such as misrepresenting test results or providing misleading information. The codebase also includes various feature flags and build-time checks to ensure that sensitive information does not leak into public builds, indicating a thorough approach to security and privacy.