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Course Outline

Foundations of Hermes Agent

  • Overview of Hermes Agent and its role within developer workflows.
  • Comparison of local AI agent workflows against cloud-based coding assistants.
  • Examination of core capabilities, inherent limitations, and standard use cases.

Establishing the Local Environment

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

Utilizing Core Components

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

Architecting Practical Code Assistance Workflows

  • Defining workflow objectives, input parameters, and expected outcomes.
  • Creating workflows for code explanation, review, and debugging processes.
  • Structuring prompts to ensure consistent and useful agent behavior.
  • Handling local files and repositories with appropriate security safeguards.

Integration with Developer Tools

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

Safety, Privacy, and Organizational Governance

  • Restricting tool access and minimizing the risk of unsafe actions.
  • Ensuring sensitive code and data remain within local environments.
  • Reviewing logs, outputs, and workflow traceability.
  • Establishing team policies for secure, agent-assisted development.

Practical Laboratory: Constructing a Secure Local Coding Assistant

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

Troubleshooting and Future Directions

  • Addressing common setup and configuration challenges.
  • Diagnosing workflow failures and interpreting unclear outputs.
  • Identifying opportunities for improvement and outlining adoption strategies.

Requirements

  • Proficiency in software development workflows and source code management practices.
  • Hands-on experience with command-line tools and professional development environments.
  • Fundamental programming skills.

Target Audience

  • Developers seeking to integrate local AI agents into their coding support processes.
  • Technical leads overseeing the security and efficiency of developer workflows.
  • DevOps and platform engineers responsible for managing internal AI tooling infrastructure.
 14 Hours

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