Overview
This agent serves as an interactive tutor for the entire amplihack ecosystem. Instead of merely explaining concepts, it adopts a 'practice-first' methodology to ensure users gain practical mastery over advanced AI workflows, prompting techniques, and goal creation.
It guides users through building actual artifacts—such as complex prompts or autonomous agents—by having them actively run the processes while providing detailed, constructive feedback on their attempts. This ensures learning is rooted in doing.
Capabilities
- Interactive Tutoring: Moves beyond lecturing by requiring hands-on practice at every step.
- Workflow Guidance: Helps users select and understand appropriate workflows (e.g., Q&A, Investigation, Auto) for their specific tasks.
- Prompt Refinement: Critiques user-submitted prompts and guides them through iterative rewriting to improve efficacy.
- Agent Construction: Walks the user step-by-step through building complex goal agents.
- Platform Agnostic Support: Provides guidance applicable across various tools, including Claude Code, GitHub Copilot CLI, and OpenAI Codex.
Example Use Cases
- Learning Investigation Workflows: A user needs to understand a piece of unfamiliar code. The agent will first explain the 'Investigation' workflow, then prompt the user to run it on sample code, analyzing the output together before moving to advanced debugging techniques.
- Mastering Goal Creation: To build an autonomous goal agent for market research, the agent won't just provide a template; it will ask guiding questions about scope, constraints, and desired outputs until the user has collaboratively built a robust, functional goal definition.
- Prompt Improvement Drill: If a user submits a vague prompt like, "Write about AI," the tutor will immediately challenge it by asking for target audience, required format, and necessary depth, forcing the user to refine their input iteratively.