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Duration 14 hours
Course Outline
Introduction
- Review of the agentic coding loop, context management, and tool usage
- Identifying common challenges at the team level
Project Memory & Configuration
- Understanding the CLAUDE.md hierarchy and defining its core contents
- Managing settings files, permission modes, and allowlists
- Practical exercise: Configuring a sample repository
Subagents
- Determining when to delegate tasks to subagents
- Defining specific roles, prompts, and tool access permissions
- Practical exercise: Building a code reviewer and a test-writing subagent
Hooks
- Exploring hook events and their primary use cases
- Preventing unsafe actions and enforcing engineering standards
- Practical exercise: Automating formatting and testing on every code change
Skills, Commands & Plugins
- Developing reusable Skills and custom slash commands
- Bundling and distributing plugins across teams
- Practical exercise: Packaging a standardized team workflow
MCP Integration
- Understanding MCP fundamentals and appropriate use cases
- Connecting issue trackers, databases, and documentation systems
- Evaluating trust models and security considerations
Automation & CI
- Utilizing headless mode and scripting capabilities
- Integrating Claude Code into pull request workflows
- Managing costs, rate limits, and system monitoring
Best Practices
- Strategies for reviewing generated code effectively
- Mitigating common failure modes
- Implementing a team rollout checklist
Requirements
- Consistent daily programming experience in at least one language
- Proficiency with terminal-based workflows and Git version control
- Prior hands-on usage of Claude Code or comparable AI coding assistants
Target Audience
- Software developers and engineers who utilize Claude Code as a daily tool
- Tech leads and platform engineers responsible for defining shared engineering standards
- DevOps and QA professionals seeking to automate repetitive engineering tasks
Testimonials (1)
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
