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 Codex CLI 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 managing multi-turn sessions.
- Executing file read, write, and edit operations via prompts.
- Running 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.
- Implementing sandboxing and differentiating 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.
- Setting up 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.
- Strategies for model selection based on latency versus quality.
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 in software development using any programming language.
- Basic proficiency in command-line and terminal usage.
- Familiarity with Git fundamentals.
Audience
- Software developers interested in incorporating AI terminal agents into their workflows.
- DevOps engineers exploring Rust-based AI tooling.
- Team leads assessing OpenAI Codex CLI for organizational adoption.
14 Hours
