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. The approach sounded compelling, and many of my colleagues have already seen benefits from it. So I decided to try it out myself. For this, I picked a practical analytical task: marketing budget optimisation with a bunch of constraints . Let’s see whether an autonomous loop can reach the same results as we did. Background Let’s start with some background to set the context. Autoresearch was developed by Andrej Karpathy .…