Bad theory labs

We achieved a breakthrough at BTL. AI models are very linear. They think in one direction at a time, and when they're wrong they scramble and start again. For something meant to replace humans, that's way too human. We changed that. We made LLM reasoning and execution work more like a quantum computer: many paths at once, the ones that meet merge into one, the dead ends cancel out, and everything left moves forward together. On the same hard problems, a 1.7B model thinking the normal way solved 3 out of 30. Interference Search(our new architecture)solved 23. We watched the normal model find the right answer at token 1,313, check it 9 more times, wander off and run out of budget without ever answering. Ours got there in 3 steps. Parallel thinking and execution. Subagents were a terrible way to tackle this. More technical details soon.