Let the AI Do the Experimenting
Autoresearch is an emerging approach that leverages autonomous AI agents to continuously run experiments, evaluate outcomes, and optimize performance without constant human oversight. The concept, pioneered by Andrej Karpathy and extended by Shopify's pi-autoresearch, enables AI to iterate on tasks like marketing budget optimization under constraints. By automating hypothesis generation and testing, AI can identify high-performing strategies that might otherwise go unexplored.
- ▪Autoresearch was developed by Andrej Karpathy and involves AI agents running self-directed experiments in a continuous loop.
- ▪Shopify open-sourced pi-autoresearch, an extension that uses a terminal-based coding harness to test and refine ideas autonomously.
- ▪The AI evaluates each idea based on whether it improves, worsens, or has no effect on a predefined metric, keeping only beneficial changes.
- ▪The approach was tested on a marketing budget optimization task with a $30M constraint, aiming to maximize projected revenue across campaigns.
- ▪Autoresearch can be applied to any task with a clear objective and measurable outcomes, from code optimization to analytical modeling.
Opening excerpt (first ~120 words) tap to expand
Agentic AI Let the AI Do the Experimenting Using autoresearch to optimize marketing campaigns under budget constraints Mariya Mansurova Apr 28, 2026 14 min read Share Image generated by author with DALLE-3 Have you ever been in a situation where you have plenty of ideas on how to improve your product, but no time to test them all? I bet you have. What if I told you that you no longer have to do it all on your own, you can delegate it to AI. It can run dozens (or even hundreds) of experiments for you, discard ideas that don’t work, and iterate on the ones that actually move the needle. Sounds amazing. And that’s exactly the idea behind autoresearch, where an LLM operates in a loop, continuously experimenting, measuring impact, and iterating from there.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Towards Data Science.