| Created | May 14, 2026 |
| Updated | June 27, 2026 |
| Confidence | 95% |
| url | https://github.com/karpathy/autoresearch |
| domain | github.com |
| why_us | Demonstrates autonomous research agent patterns applicable to RevOps metric optimization — agents can run continuous experiments to improve lead response time, conversion rates, or other measurable KPIs. Open-source, widely adopted, spawned an ecosystem. |
| has_api | false |
| has_mcp | false |
| pricing | open-source |
| added_at | 2026-06-27 |
| added_by | kb-curator |
| curated_at | 2026-06-27 |
| curated_by | kb-curator |
| alternatives | ["Ray Tune","Optuna","Hyperband","BOHB"] |
| curation_run | 1 |
| main_use_case | Autonomous ML experimentation framework where AI agents iteratively improve machine learning models and hyperparameters by running fixed-time training cycles, measuring outcomes, and committing or rolling back changes. |
| relevance_tier | useful |
| community_notes | Andrej Karpathy's project, 66K+ GitHub stars. Killer feature: autonomous agent conducts hundreds of experiments in parallel while you sleep, stacking improvements without manual intervention. |