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Duration 14 hours
Course Outline
Introduction
- Review: The agentic coding loop, context management, and available tools
- Common challenges encountered at the team level
Project Memory and Configuration
- Understanding the CLAUDE.md hierarchy and appropriate content
- Managing settings files, permission modes, and allowlists
- Exercise: Configuring a sample repository
Subagents
- Determining when to delegate tasks to a subagent
- Defining roles, prompts, and tool access parameters
- Exercise: Creating a reviewer subagent and a test-writing subagent
Hooks
- Hook events and common application scenarios
- Preventing unsafe actions and enforcing coding standards
- Exercise: Automating formatting and testing on every change
Skills, Commands, and Plugins
- Creating reusable Skills and slash commands
- Bundling and sharing plugins across a team
- Exercise: Packaging a specific team workflow
MCP Integration
- Overview of MCP and its appropriate use cases
- Connecting to issue trackers, databases, and documentation sources
- Considerations regarding trust and security
Automation and CI
- Utilizing headless mode and scripting capabilities
- Incorporating Claude Code into pull request workflows
- Managing costs, limits, and monitoring performance
Best Practices
- Techniques for reviewing generated code
- Identifying common failure modes and strategies to avoid them
- Checklist for team rollout
Requirements
- Daily programming experience in at least one programming language
- Familiarity with terminal usage and Git workflows
- Prior hands-on experience with Claude Code or a similar AI coding assistant
Target Audience
- Software developers and engineers who use Claude Code on a regular basis
- Tech leads and platform engineers responsible for establishing shared standards within teams
- DevOps and QA engineers looking to automate repetitive engineering tasks
Testimonials (2)
The session was highly interactive and applicable to the business.
Jorge Boscan - Chevron Global Technology Services Company
Course - Advanced GitHub Copilot & AI for Projects and Infrastructure
Machine Translated
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
