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Course Outline
Introduction to Devstral and Coding Agents
- Overview of the Devstral architecture.
- Agentic AI concepts applied to software engineering.
- Key use cases for coding agents.
Setting Up the Development Environment
- Installing and configuring Devstral.
- Integration with Python and Git workflows.
- IDE support utilizing Visual Studio Code.
Designing Coding Agents
- Defining agent roles and core capabilities.
- Workflow design for code navigation and refactoring.
- Strategies for error handling and rollback.
Tool and API Integration
- Connecting agents to existing developer tools.
- Integrating APIs for external services.
- Automation patterns leveraging coding agents.
Agentic Workflows in Practice
- Code exploration and automated documentation generation.
- Assisted automated refactoring and testing.
- Collaborative coding practices with agents.
Security and Best Practices
- Establishing safe execution environments.
- Managing access controls and permissions.
- Monitoring and logging agent actions.
Scaling and Maintaining Coding Agents
- Deploying agents across teams and projects.
- Maintaining and updating agent workflows.
- Continuous improvement through feedback loops.
Summary and Next Steps
Requirements
- Strong proficiency in Python.
- Practical experience with software development workflows.
- Familiarity with APIs and code integration techniques.
Target Audience
- ML engineers.
- Developer-tooling teams.
- SREs focused on developer experience.
14 Hours
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