OpenAI’s unrolling the Codex Agent Loop details the internal mechanics of the Codex CLI, focusing on the “agent loop,” which orchestrates the flow between user input, model inference, and tool execution to perform software tasks.
It explains how prompts are built, how the model’s responses can trigger tool calls, and how these interactions repeat until a final result is produced. The post also discusses challenges like context window growth and performance optimization through prompt caching and automatic compaction.
This deep technical overview is the first in a series aimed at revealing design insights behind Codex’s efficient and safe code generation.
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