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Course Outline

Foundations of Hermes Agent

  • Overview of Hermes Agent and its role within developer workflows
  • Comparing local AI agent workflows with cloud-based coding assistants
  • Key capabilities, limitations, and common 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 basic parameters
  • Executing an initial workflow to validate the environment setup

Utilizing Core Components

  • Effective use of prompts, instructions, and context management
  • Understanding memory and persistent state within local workflows
  • Leveraging skills and reusable patterns for standard coding tasks
  • Safely managing tools and defining execution boundaries

Creating Practical Code Assistance Workflows

  • Defining workflow objectives, inputs, and anticipated outputs
  • Building workflows for code explanation, review, and debugging
  • Structuring prompts to ensure consistent and beneficial agent behavior
  • Managing local files and repositories with appropriate security measures

Integration with Developer Tools

  • Working with repositories, files, and command-line utilities
  • Facilitating testing and code review activities
  • Designing workflows that align with daily development routines

Safety, Privacy, and Team Governance

  • Restricting tool access and minimizing unsafe actions
  • Ensuring sensitive code and data remain within local environments
  • Analyzing logs, outputs, and workflow traces
  • Formulating team policies for secure, agent-assisted development

Practical Lab: Constructing a Secure Local Coding Assistant

  • Developing 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 Future Steps

  • Addressing common setup and configuration challenges
  • Diagnosing workflow failures and ambiguous outputs
  • Identifying areas for improvement and planning adoption next 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 overseeing secure developer workflows
  • DevOps and platform engineers supporting internal AI tooling infrastructure
 14 Hours

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Price per participant

Provisional Upcoming Courses (Require 5+ participants)

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