Building Coding Agents with Devstral: From Agent Design to Tooling Training Course
Devstral is an open-source framework engineered for the creation and operation of coding agents capable of interacting with code repositories, developer utilities, and APIs to boost engineering productivity.
This instructor-led, live training session (available online or onsite) targets intermediate to advanced ML engineers, developer-tooling teams, and Site Reliability Engineers (SREs) seeking to design, implement, and optimize coding agents using Devstral.
Upon completion of this training, participants will be equipped to:
- Establish and configure the Devstral environment for coding agent development.
- Architect agentic workflows tailored for codebase exploration and modification.
- Integrate coding agents seamlessly with developer tools and APIs.
- Adopt best practices for secure and efficient agent deployment.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical application.
- Hands-on implementation within a live-lab environment.
Customization Options
- To request tailored training for this course, please contact us to make arrangements.
Course Outline
Introduction to Devstral and Coding Agents
- Overview of Devstral architecture
- Agentic AI concepts within software engineering
- Practical use cases for coding agents
Setting Up the Development Environment
- Installing and configuring Devstral
- Integration with Python and Git workflows
- IDE support via 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 leveraging 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
- Comprehensive understanding of 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
Open Training Courses require 5+ participants.
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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
Michal Maj - XL Catlin Services SE (AXA XL)
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