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Course Outline

Hermes Agent Fundamentals

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

Establishing the Local Environment

  • Preparing the workstation and installing necessary dependencies.
  • Deploying Hermes Agent and verifying the runtime setup.
  • Configuring local model access and essential settings.
  • Executing an initial workflow to validate the environment.

Utilizing Core Components

  • Effectively employing prompts, instructions, and context.
  • Comprehending memory 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 objectives, inputs, and anticipated outputs.
  • Constructing workflows for code explanation, review, and debugging.
  • Structuring prompts to ensure consistent and beneficial agent behavior.
  • Managing local files and repositories with appropriate security safeguards.

Integration with Developer Tools

  • Interacting with repositories, files, and command-line utilities.
  • Facilitating testing and code review activities.
  • Designing workflows that align seamlessly with daily development tasks.

Safety, Privacy, and Team Governance

  • Restricting tool access to mitigate unsafe actions.
  • Ensuring sensitive code and data remain within local environments.
  • Auditing logs, outputs, and workflow traces.
  • Establishing team policies for secure agent-assisted development.

Practical Lab: Developing a Secure Local Coding Assistant

  • Building a basic Hermes Agent workflow for code assistance.
  • Incorporating prompts, memory, and selected tools.
  • Testing the workflow against realistic development tasks.
  • Optimizing the workflow for reliability, usability, and safety.

Troubleshooting and Future Steps

  • Resolving common setup and configuration challenges.
  • Diagnosing workflow failures and ambiguous outputs.
  • Identifying areas for improvement and subsequent adoption strategies.

Requirements

  • Proficiency in software development workflows and source code management.
  • Practical experience with command-line tools and development environments.
  • Foundational programming knowledge.

Target Audience

  • Developers looking to integrate local AI agents for coding support.
  • Technical team leads accountable for secure developer workflows.
  • DevOps and platform engineers managing internal AI tooling.
 14 Hours

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