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Duration 14 hours
Course Outline
Hermes Agent Fundamentals
- Understanding Hermes Agent and its role in developer workflows
- Comparing local AI agent workflows with cloud-based coding assistants
- Exploring core capabilities, limitations, and common use cases
Establishing the Local Environment
- Preparing the workstation and installing necessary dependencies
- Installing Hermes Agent and verifying the runtime configuration
- Setting up local model access and basic parameters
- Executing an initial workflow to validate the environment setup
Working with Core Components
- Effectively utilizing prompts, instructions, and context
- Understanding memory and persistent state management in local workflows
- Leveraging skills and reusable patterns for common coding tasks
- Safely managing tools and defining execution boundaries
Designing Practical Code Assistance Workflows
- Defining workflow objectives, inputs, and desired outputs
- Creating workflows for code explanation, review, and debugging
- Structuring prompts to ensure consistent and useful agent behavior
- Handling local files and repositories with appropriate safety measures
Integration with Developer Tools
- Collaborating with repositories, files, and command-line utilities
- Supporting testing and code review processes
- Designing workflows that seamlessly integrate into daily development tasks
Safety, Privacy, and Team Governance
- Restricting tool access to minimize risky actions
- Ensuring sensitive code and data remain within local environments
- Reviewing logs, outputs, and workflow traces
- Establishing team policies for secure agent-assisted development
Practical Lab: Building a Secure Local Coding Assistant
- Creating a basic Hermes Agent workflow for code assistance
- Incorporating prompts, memory, and selected tools
- Testing the workflow using realistic development tasks
- Refining the workflow for improved reliability, usability, and safety
Troubleshooting and Next Steps
- Resolving common setup and configuration challenges
- Diagnosing workflow failures and ambiguous outputs
- Identifying areas for improvement and planning adoption strategies
Requirements
- Knowledge of software development workflows and source code management practices
- Proficiency with command-line tools and development environments
- Foundational programming experience
Audience
- Developers looking to leverage local AI agents for coding support
- Technical leads responsible for maintaining secure developer workflows
- DevOps and platform engineers supporting internal AI tooling initiatives
