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Duration 14 hours
Course Outline
Introduction
- Recap: The agentic coding loop, context management, and tool utilization
- Common challenges encountered at the team level
Project Memory and Configuration
- The CLAUDE.md hierarchy and its appropriate content
- Configuration files, permission modes, and allowlists
- Exercise: Configuring a sample repository
Subagents
- Identifying scenarios for delegating tasks to a subagent
- Defining roles, prompts, and tool access parameters
- Exercise: Developing subagents for code review and test writing
Hooks
- Hook events and common application scenarios
- Preventing unsafe actions and enforcing standards
- Exercise: Automating formatting and testing on every change
Skills, Commands, and Plugins
- Creating reusable Skills and slash commands
- Bundling and sharing plugins within a team
- Exercise: Packaging a team workflow
MCP Integration
- Understanding MCP and its applicable use cases
- Connecting issue trackers, databases, and documentation systems
- Considerations regarding trust and security
Automation and CI
- Headless mode and scripting capabilities
- Incorporating Claude Code into pull request workflows
- Managing costs, limits, and monitoring
Best Practices
- Reviewing generated code effectively
- Identifying common failure modes and mitigation strategies
- Checklist for team-wide rollout
Requirements
- Regular programming experience in at least one language
- Familiarity with terminal operations and Git workflows
- Prior practical experience with Claude Code or comparable coding assistants
Target Audience
- Software developers and engineers utilizing Claude Code on a regular basis
- Technical leads and platform engineers responsible for establishing shared team standards
- DevOps and QA engineers looking to automate recurring 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
