OpenAI Codex Automation: Build AI Workflows & CLI Tools
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Stop using Codex as a one-off coding assistant. Build repeatable engineering workflows that save time, improve consistency, and keep humans in control.
Who this course is for
Developers who want to automate repetitive GitHub and repository workflows
QA engineers who need consistent test-failure investigation and verification
DevOps engineers building safer maintenance and code-health routines
Technical freelancers who want reusable delivery systems for clients
Engineering leads who want team-ready Codex skills and plugins
What you will learn
Build a pull-request review workflow with clear review criteria
Create recurring code-health and documentation checks
Define safe automation scope, approval gates, and stop conditions
Use Codex CLI for local, repeatable engineering tasks
Turn a successful prompt into a reusable Codex skill
Write workflow inputs, constraints, verification requirements, and output formats
Build a test-failure triage workflow that produces evidence-based recommendations
Package skills into a versioned Codex plugin
Understand when to use skills, plugins, and MCP-connected tooling
Create a portfolio-ready Codex automation system for clients or employers
Requirements
Basic Git and GitHub knowledge
Ability to open a terminal and navigate a project folder
Familiarity with pull requests and software testing
Access to a Codex-supported plan or environment
A small practice repository, ideally with tests
Final project
You will build and document a Codex Engineering Automation System containing four workflows: pull-request review, recurring code-health reporting, test-failure triage, and documentation updates. Your finished submission includes the workflow files, safety controls, test evidence, architecture diagram, and a case-study README.
Scrivi un commento