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Course Outline

Hermes Agent Fundamentals

  • An overview of Hermes Agent and its role within developer workflows.
  • A comparison between local AI agent workflows and cloud-based coding assistants.
  • Key capabilities, inherent limitations, and common use cases.

Configuring the Local Environment

  • Preparing the workstation and ensuring all necessary dependencies are in place.
  • Installing Hermes Agent and verifying the runtime setup.
  • Setting up local model access and basic configuration options.
  • Executing an initial workflow to validate the environment.

Interacting with Core Components

  • Effectively using 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 defining execution boundaries.

Architecting Practical Code Assistance Workflows

  • Establishing workflow objectives, inputs, and anticipated outputs.
  • Building workflows for code explanation, review, and debugging.
  • Structuring prompts to ensure consistent and useful agent behaviour.
  • Handling local files and repositories with appropriate safeguards.

Integration with Developer Tools

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

Safety, Privacy, and Team Governance

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

Practical Lab: Creating a Secure Local Coding Assistant

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

Troubleshooting and Future Directions

  • Addressing common setup and configuration challenges.
  • Diagnosing workflow failures and ambiguous outputs.
  • Identifying opportunities for improvement and planning adoption strategies.

Requirements

  • A solid understanding of software development workflows and source code management.
  • Practical experience with command-line tools and standard development environments.
  • Foundational programming knowledge.

Audience

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

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