OpenAI has published a detailed breakdown of how Codex CLI operates, a local agent that works with code on your machine. The system relies on an agent loop where a prompt is built with instructions, and the model either outputs text or requests tool execution, repeating until the task is complete.

Key points include the challenge of context size with a 32KB limit, the use of prompt caching to reduce inference costs, and a shift to a stateless model design for zero data retention. Additionally, a compaction mechanism compresses old messages to keep the context window manageable.

Codex CLI also supports local models via a flag for integration with Ollama or LM Studio. More details on CLI architecture and tool usage are expected in future articles.

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Source: @ai_machinelearning_big_data