Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to OpenAI Codex CLI
- Understanding what Codex CLI is and its 2025 open-source Rust architecture
- Key features: prompts, file operations, bash execution, and multi-step tasks
- Comparison with Claude Code and other terminal agents
- Overview of approval modes and security boundaries
Installation and Setup
- Installing Codex CLI on macOS and Linux
- Configuring API keys for OpenAI and compatible providers
- Connecting to local backends via Ollama and Atomic Chat
- Setting up SSH and remote development environments
Core Workflow Commands
- Running single prompts and multi-turn sessions
- Performing file read, write, and edit operations via prompts
- Executing shell commands and handling piped outputs
- Managing working directories and project context
Approval Modes and Safety
- Configuring automatic, ask-before-execute, and fully manual modes
- Sandboxing and distinguishing between read-only and write-enabled sessions
- Safely handling destructive commands and file deletions
Git and CI Integration
- Using Codex CLI to generate commits and diffs
- Implementing pre-commit hooks with agent review
- Running Codex CLI in headless CI environments
- Integrating with GitHub Actions and GitLab CI
MCP Server Integration
- Connecting to Model Context Protocol servers
- Extending tool capabilities with custom MCP endpoints
- Building internal MCP tools for proprietary systems
Multi-Backend Support
- Switching between OpenAI, Gemini, and GitHub Models APIs
- Performing local inference with Ollama and self-hosted endpoints
- Selecting models based on latency versus quality trade-offs
Team Deployment and Governance
- Managing shared configurations and secrets
- Establishing usage policies and audit logging for enterprise environments
- Setting up standardized team prompts and guardrails
Custom Prompts and Workflows
- Writing reusable prompt templates
- Chaining tasks for complex refactoring projects
- Batch processing multiple files and repositories
Performance Tuning
- Understanding Rust performance characteristics
- Optimizing token usage for large projects
- Implementing caching and session state management
Troubleshooting Common Issues
- Resolving connection failures to backends
- Debugging prompt ambiguity and misinterpretations
- Handling rate limiting and implementing retry strategies
Security Best Practices
- Protecting API keys in shared environments
- Preventing prompt injection and command hijacking
- Addressing data residency and compliance considerations
Summary and Next Steps
- Recap of core capabilities and workflows
- Exploring community resources and open-source contributions
- Transitioning to advanced multi-agent orchestration topics
Requirements
- Experience with software development in any programming language
- Basic proficiency in command-line and terminal usage
- Familiarity with fundamental Git concepts
Audience
- Software developers interested in integrating AI terminal agents into their workflow
- DevOps engineers exploring Rust-based AI tools
- Team leads evaluating OpenAI Codex CLI for organizational adoption
14 Hours