Autoresearch²: When AI Starts Debugging Its Own Brain
Search is where many AI systems become embarrassingly human. They try one move. It fails. They try a nearby move. It fails. Then, with the serene confidence of a spreadsheet macro wearing a lab coat, they try the first move again. That is the real problem behind many “autonomous research” demonstrations. The issue is not always that the model cannot propose useful ideas. It is that the loop around the model is fixed: propose a change, run an experiment, evaluate the result, keep or discard. Once this loop gets stuck, the system often has no way to ask the more important question: is my search process itself badly designed? ...