Agent Apprenticeship
Open-source agent development and engineering for agent apprenticeship, agent economy, agent experience.
What does this agent do, and when should you use it?
The repository describes Agent Apprenticeship as: The living ecosystem where AI agents complete tasks through workflow loops, improve through iterative execution, are evaluated by mentor agents or humans in the loop, and turn completed work into reusable work experience and data to improve future agents. This profile is a source-based catalog entry; an independent FARS review is still pending.
The living ecosystem where AI agents complete tasks through workflow loops, improve through iterative execution, are evaluated by mentor agents or humans in the loop, and turn completed work into reusable work experience and data to improve future agents.
- Evaluate it for an agent application or engineering workflow.
- Prototype integrations around its documented tools or APIs.
- Inspect the source before adapting it to an existing stack.
What are this agent's strengths and limitations?
- Public source and README are available for inspection.
- Focused on agent apprenticeship, agent economy, agent experience.
- Setup, model-provider support, and maturity must be confirmed against the current release.
- No independent FARS score has been assigned yet.
How do you install or deploy this agent?
Follow the current installation instructions in the [repository README](https://github.com/ray-r-ren/agent-apprenticeship#readme). Requirements and provider setup vary by release.
How do you use this agent?
Start with the examples and quickstart in the [repository documentation](https://github.com/ray-r-ren/agent-apprenticeship#readme), then test the workflow with limited permissions and non-sensitive data.