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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
 14 Hours

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