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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.
 14 Hours

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