Building Coding Agents with Devstral: From Agent Design to Tooling Training Course
Devstral is an open-source framework purpose-built for creating and operating coding agents capable of interacting with codebases, developer tools, and APIs to boost engineering productivity.
This instructor-led live training (available online or onsite) targets intermediate to advanced ML engineers, developer-tooling teams, and SREs aiming to design, implement, and optimize coding agents using Devstral.
Upon completing this training, participants will be able to:
- Configure and set up Devstral for coding agent development.
- Design agentic workflows for exploring and modifying codebases.
- Integrate coding agents with developer tools and APIs.
- Apply best practices for secure and efficient agent deployment.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical sessions.
- Hands-on implementation within a live lab environment.
Customization Options
- To arrange a tailored version of this course, please contact us.
Course Outline
Introduction to Devstral and Coding Agents
- Overview of Devstral architecture
- Agentic AI concepts in software engineering
- Use cases for coding agents
Setting Up the Development Environment
- Installing and configuring Devstral
- Integration with Python and Git workflows
- IDE support with Visual Studio Code
Designing Coding Agents
- Defining agent roles and capabilities
- Workflow design for code navigation and refactoring
- Error handling and rollback strategies
Tool and API Integration
- Connecting agents to developer tools
- API integration for external services
- Automation patterns with coding agents
Agentic Workflows in Practice
- Code exploration and documentation generation
- Automated refactoring and testing assistance
- Collaborative coding with agents
Security and Best Practices
- Safe execution environments
- 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 with feedback loops
Summary and Next Steps
Requirements
- Proficient understanding of Python
- Practical experience with software development workflows
- Familiarity with APIs and code integration
Target Audience
- ML engineers
- Developer-tooling teams
- SREs focused on developer experience
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Testimonials (2)
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
Michal Maj - XL Catlin Services SE (AXA XL)
Course - GitHub Copilot for Developers
Trainer able to adjust the course level during training to fit our understanding level on the topic, so that we could gain more useful knowledge that could further help us harness the tools in our daily works.
Tatt Juen - ViTrox Technologies Sdn Bhd
Course - Intermediate GitHub Copilot
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