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
- Core features: prompt handling, 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 systems
- 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
- Executing single prompts and multi-turn sessions
- File read, write, and edit operations derived from prompts
- Shell command execution and output piping
- Managing working directories and project context
Approval Modes and Safety
- Configuring automatic, ask-before-execute, and fully manual modes
- Sandboxing techniques 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 via 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
- Strategies for model selection based on latency versus quality trade-offs
Team Deployment and Governance
- Managing shared configurations and secrets
- Establishing usage policies and audit logging for enterprise settings
- Setting up standardized team prompts and guardrails
Custom Prompts and Workflows
- Creating reusable prompt templates
- Chaining tasks for complex refactoring projects
- Batch processing across multiple files and repositories
Performance Tuning
- Understanding the performance characteristics of Rust
- Optimizing token usage for large projects
- Managing caching and session state
Troubleshooting Common Issues
- Resolving connection failures to backend services
- Debugging prompt ambiguity and misinterpretations
- Addressing rate limiting and implementing retry strategies
Security Best Practices
- Protecting API keys in shared environments
- Preventing prompt injection and command hijacking
- Considering data residency and compliance requirements
Summary and Next Steps
- Recap of core capabilities and workflows
- Resources for community engagement and open-source contributions
- Transitioning to advanced multi-agent orchestration topics
Requirements
- Experience in software development with any programming language
- Basic proficiency in command-line and terminal usage
- Familiarity with fundamental Git concepts
Audience
- Software developers seeking to incorporate AI terminal agents into their workflow
- DevOps engineers exploring Rust-based AI tools
- Team leads evaluating OpenAI Codex CLI for organizational adoption
14 Hours
