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Duration 14 hours
Course Outline
Hermes Agent Fundamentals
- Defining what Hermes Agent is and its position within developer workflows.
- Comparing local AI agent workflows with cloud-based coding assistants.
- Exploring core capabilities, inherent limitations, and typical use cases.
Setting Up the Local Environment
- Preparing the workstation and installing required dependencies.
- Installing Hermes Agent and verifying the runtime configuration.
- Configuring local model access and adjusting basic settings.
- Executing an initial workflow to validate the environment setup.
Working with Core Components
- Effectively utilizing prompts, instructions, and context.
- Understanding memory management and persistent state 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 goals, inputs, and expected outputs.
- Building workflows for code explanation, review, and debugging.
- Structuring prompts to ensure consistent and useful agent behavior.
- Handling local files and repositories with appropriate security safeguards.
Integrating with Developer Tools
- Working with repositories, files, and command-line utilities.
- Supporting testing and code review activities.
- Designing workflows that integrate seamlessly into daily development tasks.
Safety, Privacy, and Team Governance
- Limiting tool access and mitigating unsafe actions.
- Ensuring sensitive code and data remain within local environments.
- Reviewing logs, outputs, and workflow traces for auditing.
- Establishing team policies for secure agent-assisted development.
Practical Lab: Building a Secure Local Coding Assistant
- Creating a simple Hermes Agent workflow for code assistance.
- Adding prompts, memory structures, and selected tools.
- Testing the workflow using realistic development tasks.
- Refining the workflow to enhance reliability, usability, and safety.
Troubleshooting and Next Steps
- Resolving common setup and configuration issues.
- Diagnosing workflow failures and ambiguous outputs.
- Identifying opportunities for improvement and planning adoption next steps.
Requirements
- Familiarity with software development workflows and source code management practices.
- Experience utilizing command-line tools and setting up development environments.
- Foundational programming knowledge and experience.
Audience
- Developers seeking to integrate local AI agents into their coding support processes.
- Technical team leads accountable for maintaining secure developer workflows.
- DevOps and platform engineers supporting internal AI tooling infrastructure.