Working with Codex

2026-04-23 · Source: OpenAI News · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Novice, short

Summary

OpenAI's Codex is an AI workspace designed for organizing and executing tasks through natural language conversations, similar to ChatGPT but with the ability to take direct action on local files. Released on April 23, 2026, it features a sidebar for navigation, project management linked to local computer folders, and customizable settings. Users interact with Codex via a chat window, initiating "threads" that can be standalone or nested within projects. A key differentiator is Codex's capacity to inspect, create, and edit files within designated project folders. It also supports real-time course correction using the "Steer" function and allows for multiple concurrent tasks, such as cleaning a spreadsheet while drafting a project tracker.

Key takeaway

For AI Engineers or Software Engineers managing local development tasks, Codex offers a direct way to automate file operations using natural language. You should explore its project-folder linking and "Steer" functionality to streamline workflows and make real-time adjustments without interrupting ongoing tasks, potentially boosting productivity in code and data management.

Key insights

Codex extends conversational AI to direct file system actions, enabling task execution through natural language.

Principles

• Organize tasks into projects linked to local folders.
• Use natural language for instructions and real-time adjustments.

Method

Initiate a thread, provide instructions in plain language, specify files, and define "done." Use "Steer" for real-time course correction without restarting tasks.

In practice

• Create new projects for different file groups.
• Run multiple tasks simultaneously for efficiency.

Topics

• OpenAI Codex
• Workspace Setup
• Threads & Projects
• Local File Management
• Task Automation

Best for: AI Engineer, Software Engineer, AI Student

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Editorial summary, takeaway, and curation by AIssential. Original article published by OpenAI News.