Table of Contents
The Codex Playbook
Enterprise AI Software Engineering with Codex
Igor van der Burgh 20 chapters 5 parts Practical enterprise playbookNavigate
Front Matter Part I: Foundations Part II: Context Engineering Part III: Codex-Ready Repositories Part IV: Enterprise Workflows Part V: Practical Patterns Back MatterFront Matter
Before the Playbook
- Author's Note
- Introduction: Why This Playbook Exists
Part I
Foundations
The language, mental model, and lifecycle readers need before designing repositories, workflows, or agent patterns.
- 01 The Rise of AI Software Engineering
Why AI changes the software delivery loop and why human accountability remains central.
- 02 What Codex Is and Where It Fits
How to understand Codex as an engineering collaborator and decide which work belongs in the workflow.
- 03 Codex CLI, IDE, Cloud, and ChatGPT
When to use each Codex interaction surface across local, editor, cloud, and conversational work.
- 04 The AI Development Lifecycle
A practical lifecycle for moving from intent to context, implementation, verification, review, and learning.
Part II
Context Engineering
How teams turn context into a durable engineering asset instead of relying on one-off prompts.
- 05 Why Context Matters More Than Prompts
How teams turn context into an engineering design surface rather than prompt decoration.
- 06 AGENTS.md Explained
How durable repository instructions guide Codex behavior, standards, verification, and review.
- 07 Repository Memory and Documentation
How documentation and repository memory help humans and Codex understand the system.
- 08 Context Loading and Prioritisation
How to decide what Codex should read, trust, ignore, refresh, or escalate.
Part III
Codex-Ready Repositories
Repository structure, Markdown documentation, quality gates, CI/CD, security, and governance for AI-assisted work.
- 09 Designing the Ideal Repository
How to structure repositories so Codex can discover intent, boundaries, tests, and ownership.
- 10 Markdown Files Codex Should Understand
How Markdown files become operational context for architecture, APIs, testing, security, and delivery.
- 11 Testing, Quality Gates, and CI/CD
How to make Codex-assisted changes reviewable, repeatable, and safe to accept.
- 12 Security, Secrets, and Governance
How to define security boundaries, secrets handling, and governance gates for AI-assisted work.
Part IV
Enterprise Workflows
GitHub, MCP, multi-agent development, pull request review, and enterprise operating models.
- 13 GitHub Workflow with Codex
How to move from issue to branch, task, commit, pull request, review, and merge with Codex in the loop.
- 14 MCP and Connected Tooling
How MCP and connected tools expand Codex context and action surfaces.
- 15 Multi-Agent Development
How to coordinate specialized agents without losing ownership, context, or review discipline.
- 16 Code Review and Pull Requests
How to review Codex-assisted work with evidence, boundaries, and human accountability.
- 17 Operating Codex in Enterprise Teams
How teams, platform owners, AI champions, and leaders can operate Codex responsibly.
Part V
Practical Patterns
Applied patterns, reusable templates, and checklists for enterprise teams adopting Codex.
- 18 Building an AI Dashboard
A practical dashboard workflow covering data, documentation, review, and deployment concerns.
- 19 Building a Competitive Intelligence Platform
An enterprise intelligence workflow built around sources, evidence, governance, and automation.
- 20 Codex Playbook Templates and Checklists
Reusable templates, prompts, checklists, and adoption assets for enterprise teams.
Back Matter
Reference Material
- Glossary
- Further Reading and Official Documentation Links