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Course Outline

Hermes Agent Foundations

  • Understanding what Hermes Agent is and its role within 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 adjusting basic settings.
  • Executing an initial workflow to validate the environment.

Utilizing Core Components

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

Architecting 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.

Integration with Developer Tools

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

Safety, Privacy, and Team Governance

  • Restricting tool access and mitigating 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: Constructing a Secure Local Coding Assistant

  • Creating a straightforward Hermes Agent workflow for code assistance.
  • Incorporating prompts, memory features, and selected tools.
  • Testing the workflow against realistic development tasks.
  • Refining the workflow to enhance 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 subsequent adoption steps.

Requirements

  • Proficiency with software development workflows and source code management practices.
  • Experience utilizing command-line tools and setting up development environments.
  • Foundational programming experience.

Intended Audience

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

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