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Course Outline

Hermes Agent Fundamentals

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

Local Environment Configuration

  • Preparation of workstations and verification of necessary dependencies
  • Installation of Hermes Agent and validation of the runtime setup
  • Configuration of local model access and foundational settings
  • Execution of an initial workflow to validate the environment

Utilizing Core Components

  • Effective application of prompts, instructions, and context
  • Comprehension of memory and persistent state mechanisms in local workflows
  • Leveraging skills and reusable patterns for routine coding tasks
  • Safe management of tools and execution boundaries

Designing Practical Code Assistance Workflows

  • Definition of workflow objectives, inputs, and anticipated outputs
  • Creation of workflows dedicated to code explanation, review, and debugging
  • Structuring prompts to ensure consistent and beneficial agent behavior
  • Safe handling of local files and repositories with appropriate safeguards

Developer Tool Integration

  • Interaction with repositories, files, and command-line utilities
  • Support for testing and code review activities
  • Designing workflows that seamlessly integrate into daily development routines

Safety, Privacy, and Governance

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

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

Troubleshooting and Future Steps

  • Resolution of common setup and configuration challenges
  • Diagnosis of workflow failures and ambiguous outputs
  • Identification of improvement opportunities and subsequent adoption steps

Requirements

  • Working knowledge of software development lifecycles and source code management practices
  • Practical experience utilizing command-line tools and standard development environments
  • Fundamental programming proficiency

Target Audience

  • Developers seeking to integrate local AI agents for coding support
  • Technical leads overseeing the security of developer workflows
  • DevOps and platform engineers responsible for maintaining internal AI tooling
 14 Hours

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