OpenAI just dropped Codex, a beautiful new GUI for their AI coding agent, and after a day of testing, I'm genuinely impressed. Let me show you why this might change how developers work with AI.

In this video, I take you on a complete tour of OpenAI's new Codex application for macOS. We explore the stunning interface, the impressive multi-threaded workflow, automations, skills, and MCP server integrations. Then I put it to the test by building a complete Java 25 vending machine CLI application from scratch, including adding JSpecify for null safety.

Key Takeaways
• Codex's thread-based workflow lets you multitask across multiple projects simultaneously
• GPT 5.2 Codex is now 40% faster - a huge improvement for developer workflows
• Built-in support for Git work trees enables parallel AI-driven development
• Automations can scan commits for bugs, draft weekly notes, and summarize stand-ups
• Skills and MCP servers extend Codex's capabilities to tools like Notion and Sentry

Timestamps
0:00 - Intro & First Impressions
0:45 - Codex Website Tour
2:15 - Multi-Platform Support (Mac, CLI, Web)
3:00 - GPT 5.2 is 40% Faster
3:45 - Project Setup: Vending Machine CLI
5:00 - Thread-Based Workflow Explained
6:15 - Automations & Skills Deep Dive
8:00 - MCP Servers & Git Integration
9:30 - Building the App with Codex
11:00 - Reviewing Generated Code
12:30 - Running Tests & Demo
13:30 - Adding JSpecify Null Safety
14:45 - AI-Generated Commit Messages
15:15 - Final Thoughts & Wrap Up

🔗Resources & Links mentioned in this video:
Codex: https://openai.com/codex/

Have you tried OpenAI Codex yet? Drop your thoughts in the comments below - I'd love to hear how it's fitting into your workflow!

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Dan Vega

A first-look walkthrough of OpenAI's new Codex desktop app (macOS), covering its key features: thread-based project management for parallel agent tasks, automations (e.g., scanning commits for bugs, drafting standup summaries), skills for teaching the LLM reusable behaviors, MCP server integrations, and built-in Git worktree support. The author demos building a Java 25 Maven vending machine CLI app with tests, then adds JSpecify null-safety annotations, and commits via the app's AI-generated commit message feature. GPT-4.1/5.2 Codex models are noted to be 40% faster, addressing a previous complaint about latency compared to Claude Code.

I Tried OpenAI's New Codex Agent. Here are my First Impressions (It's Really Good)