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Duration 7 hours
Course Outline
Introduction to the Pi Coding Agent
- Understanding what Pi Coding Agent is and its place in daily development tasks
- Common use cases for both individual developers and teams
- Exploring strengths, limitations, and setting realistic expectations
Setup and Environment Preparation
- Preparing the terminal and development environment
- Installing Pi Coding Agent
- Establishing connections with supported AI providers
- Verifying installation success and performing the initial run
Core Workflow in the Terminal
- How Pi Coding Agent interprets, edits, and assists in managing files
- Executing development tasks directly from the terminal workflow
- Engaging in iterative work processes with rapid feedback loops
Prompting for Optimal Results
- Crafting clear instructions for coding, debugging, and explanation requests
- Decomposing complex tasks into manageable steps
- Refining outputs through subsequent prompts
Applying Pi to Everyday Development Tasks
- Generating small features, helper functions, and boilerplate code
- Safely refactoring and editing existing codebases
- Reviewing suggested modifications before acceptance
Validation and Troubleshooting
- Leveraging Pi Coding Agent to support testing and verify results
- Identifying errors and performing focused corrections
- Resolving common issues related to setup, provider connections, and output quality
Safe and Effective Team Adoption
- Establishing guardrails for code quality, review processes, and approvals
- Safeguarding sensitive information and ensuring responsible tool usage
- Developing a straightforward, repeatable workflow for team deployment
Summary and Next Steps
- Recapping key skills and practical takeaways
- Strategizing the application of Pi Coding Agent in real-world projects
- Identifying further steps for ongoing practice and adoption
Requirements
- Fundamental understanding of software development principles
- Proficiency in using the command line and standard developer tools
- Basic programming experience with any modern language
Target Audience
- Developers seeking to accelerate coding tasks via an AI assistant
- Technical leads aiming to implement practical workflows for team adoption
- DevOps engineers and advanced users operating primarily in terminal environments
