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Course Outline

Hermes Agent Fundamentals

  • Overview of Hermes Agent and its role in developer workflows
  • Comparison of local AI agent workflows with cloud-based coding assistants
  • Key capabilities, limitations, and common use cases

Local Environment Setup

  • Preparation of the workstation and installation of required dependencies
  • Installation of Hermes Agent and verification of the runtime environment
  • Configuration of local model access and basic settings
  • Execution of an initial workflow to validate the setup

Core Component Management

  • Effective use of prompts, instructions, and contextual data
  • Understanding memory and persistent state in local workflows
  • Leveraging skills and reusable patterns for routine coding tasks
  • Safe management of tools and execution boundaries

Designing Practical Code Assistance Workflows

  • Defining workflow objectives, inputs, and expected outcomes
  • Developing workflows for code explanation, review, and debugging
  • Structuring prompts to ensure consistent and useful agent behavior
  • Handling local files and repositories with appropriate safeguards

Developer Tool Integration

  • Interaction with repositories, files, and command-line utilities
  • Supporting testing and code review activities
  • Integrating workflows into daily development tasks

Safety, Privacy, and Team Governance

  • Restricting tool access and minimizing unsafe 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

  • Construction of a basic Hermes Agent workflow for code assistance
  • Incorporation of prompts, memory, and selected tools
  • Testing the workflow with realistic development tasks
  • Refinement for reliability, usability, and safety

Troubleshooting and Next Steps

  • Resolution of common setup and configuration issues
  • Diagnosis of workflow failures and ambiguous outputs
  • Identification of improvement opportunities and adoption strategies

Requirements

  • Proficiency with software development workflows and source code management systems
  • Experience using command-line interfaces and development environments
  • Foundational programming skills

Audience

  • Developers looking to leverage local AI agents for coding support
  • Technical leads accountable for maintaining secure developer workflows
  • DevOps and platform engineers responsible for supporting internal AI tooling
 14 Hours

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