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Run 10+ engineering tasks in parallel without breaking your codebase. This complete OpenAI Codex tutorial shows you how to leverage parallel development, Git worktrees, skills, and automations to ship features faster as a solopreneur or small team.I'll walk you through everything from installation to advanced workflows—including how I run multiple feature implementations simultaneously, automate weekly reports, and use cloud computing for heavy refactoring tasks. This is the all-in-one AI coding workspace that replaces juggling between five different tools. 00:00 Introduction to Parallel Engineering with OpenAI Codex 00:27 Why OpenAI Codex is Revolutionary 01:27 Overview of Today's Agenda 02:29 Setting Up OpenAI Codex 03:19 Choosing and Using Models 04:06 Understanding Sandbox Mode 06:04 Running Tasks Locally and in the Cloud 08:55 Using Git Work Trees for Parallel Development 09:53 Worktree and multithread example 13:02 Demo of worktree 1 output 14:14 Demo of worktree 2 output 16:17 Personalization 16:49 Exploring Codex Skills 22:00 Creating and Running Automations 25:02 Final Thoughts and Recommendations 26:25 Conclusion and Community Invitation 🔗 RESOURCES MENTIONED IN VIDEO OpenAI Codex: https://openai.com/codex My Health Data Analyzer App: Available on Mac App Store Linear: Project management with AI integration Automation Prompts: Available in description 📝 AUTOMATION PROMPTS Upskill Automation Prompt: You are an AI skill maintainer. Your job is to review all skills in this project, identify failures or inefficiencies, and automatically improve them. Check execution logs, update skill files, and optimize for better performance. Update Agents.md Automation Prompt: You are an AI agent maintainer. Your job is to review my recent interactions and detect misunderstandings or friction points. Update agents.md to improve future conversations based on observed patterns. 🤝 JOIN THE COMMUNITY Free AI Community (2,500+ members): https://nas.io/rumjahn 📱 ONE-ON-ONE HELP Need help with your AI automation project? Book a consultation: https://nas.io/rumjahn/sessions/1-on-... 💡 KEY TAKEAWAYS ✅ Built-in dictation saves $10-20/month on transcription tools ✅ Git worktrees prevent code conflicts when running parallel tasks ✅ Skills = reusable prompts that save hours of repetitive work ✅ Automations = cron jobs for your AI workflows ✅ Cloud execution = run heavy tasks without draining local resources TOOL COMPARISON: OpenAI Codex: Best for OpenAI Max plan users, includes worktrees OpenCode: Multi-LLM support (no Claude), missing worktrees Claude Code: Highest quality coding, no parallel support (yet) #OpenAICodex #AIcoding #ParallelDevelopment #Solopreneur #AutomationWorkflow