Get in Touch

Course Outline

Hermes Agent Fundamentals

  • Understanding what Hermes Agent is and its role in developer workflows
  • Comparing local AI agent workflows with cloud-based coding assistants
  • Exploring core capabilities, limitations, and typical use cases

Configuring the Local Environment

  • Preparing the workstation and installing necessary dependencies
  • Installing Hermes Agent and verifying the runtime setup
  • Configuring local model access and basic parameters
  • Executing an initial workflow to validate the environment

Managing Core Components

  • Effectively utilizing prompts, instructions, and context
  • Comprehending memory and persistent state within local workflows
  • Leveraging skills and reusable patterns for common coding tasks
  • Safely managing tools and execution boundaries

Architecting Practical Code Assistance Workflows

  • Defining workflow objectives, inputs, and expected 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 safeguards

Integration with Developer Tools

  • Working with repositories, files, and command-line utilities
  • Supporting testing and code review activities
  • Designing workflows that seamlessly fit into daily development tasks

Safety, Privacy, and Team Governance

  • Limiting tool access and mitigating unsafe actions
  • Retaining sensitive code and data within local environments
  • Reviewing logs, outputs, and workflow traces
  • Establishing team policies for secure agent-assisted development

Practical Lab: Constructing a Secure Local Coding Assistant

  • Developing a basic Hermes Agent workflow for code assistance
  • Implementing prompts, memory, and selected tools
  • Testing the workflow against realistic development tasks
  • Refining the workflow for reliability, usability, and safety

Troubleshooting and Future Steps

  • Resolving common setup and configuration challenges
  • Diagnosing workflow failures and ambiguous outputs
  • Identifying opportunities for improvement and next steps for adoption

Requirements

  • Proficiency with software development workflows and source code management
  • Experience utilizing command-line tools and development environments
  • Foundational programming 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 overseeing internal AI tooling infrastructure
 14 Hours

Number of participants


Price per participant

Upcoming Courses

Related Categories