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Duration 14 hours
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.