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Course Outline

Hermes Agent Fundamentals

  • The role of Hermes Agent within developer workflows.
  • A comparison of local AI agent workflows versus cloud-based coding assistants.
  • Core capabilities, inherent limitations, and typical use cases.

Setting Up the Local Environment

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

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 defining execution boundaries.

Designing 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.

Integrating with Developer Tools

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

Practical Lab: Building a Secure Local Coding Assistant

  • Constructing a simple Hermes Agent workflow for code assistance.
  • Incorporating prompts, memory, and selected tools.
  • Testing the workflow against realistic development tasks.
  • Refining the workflow to enhance reliability, usability, and safety.

Troubleshooting and Next Steps

  • Addressing common setup and configuration issues.
  • Diagnosing workflow failures and ambiguous outputs.
  • Identifying opportunities for improvement and outlining adoption steps.

Requirements

  • Understanding of software development workflows and source code management practices.
  • Proficiency with command-line tools and standard development environments.
  • Fundamental programming experience.

Audience

  • Developers aiming to utilize local AI agents for coding support.
  • Technical team leads accountable for securing developer workflows.
  • DevOps and platform engineers supporting internal AI tooling infrastructure.
 14 Hours

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