OpenAI is pulling back the curtain on Codex CLI, their cross-platform coding agent that runs locally on your machine. Think of it as an AI pair programmer that lives in your terminal, making real software changes safely and efficiently. This deep dive focuses on the agent loop, which is basically the brain of the operation. It starts by taking your input and building a prompt, then sends that to the model for inference (where text gets tokenized, processed, and turned back into readable output). The model can either give you a final answer or request a tool call like “run ls and report output.” If it’s a tool call, the agent executes it, appends the results to the original prompt, and re-queries the model in a continuous feedback cycle. It’s like a conversation where the AI keeps asking for more info until it can finish the job. This is the first post in a series where OpenAI shares hard-won lessons from building a world-class software agent since launching in April. Why it matters: Understanding how agent loops work under the hood is crucial as AI moves from simple chatbots to autonomous coding assistants that could fundamentally change how developers build software.