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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 techniques: read-only versus 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
  • Developing internal MCP tools for proprietary systems

Multi-Backend Support

  • Switching between OpenAI, Gemini, and GitHub Models APIs
  • Local inference using 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-scale projects
  • Managing caching and session state

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
  • Overview of community resources and open-source contributions
  • Transitioning to advanced multi-agent orchestration topics

Requirements

  • Experience in software development using any programming language
  • Familiarity with basic command-line and terminal usage
  • Knowledge of Git basics

Audience

  • Software developers seeking to incorporate AI terminal agents into their workflow
  • DevOps engineers exploring Rust-based AI tools
  • Team leads assessing OpenAI Codex CLI for group adoption
 14 Hours

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  • Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
  • Flexible Schedule: Dates and times adapted to your team's agenda.
  • Format: Online (live), In-company (at your offices), or Hybrid.
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Price per private group, online live training, starting from 2600 € + VAT*

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