Agent Apprenticeship Seed Dataset for AI Agent Training

Agent Apprenticeship provides open infrastructure for AI agents to learn from real-world tasks. The dataset, created by Forsy-AI, facilitates iterative workflow loops and the exchange of reusable experience and training signals. It was last updated on June 20, 2026.

Use Cases

• Training AI agents on complex, multi-step workflows based on the described iterative workflow loops.
• Improving agent performance through shared learning signals based on the concept of collective training signal exchange.
• Benchmarking agent learning efficiency using reusable experience generated from real-world task execution.

Strengths

• Dataset is part of a living ecosystem for agent learning, as described.
• Focuses on generating reusable learning signals from real-world tasks.
• Created by a named author, Forsy-AI.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

huggingface

Collection Method

Likely contains data generated from agent execution loops and shared improvement processes.

Freshness

Last updated 2026-06-20 23:32:36; freshness should be verified.