@LiorOnAI: GPT-5.6 Sol may have solved a 50-year-old math problem using 64 subagents in parallel. The system did not rely on one l…

GPT-5.6 Sol may have solved a 50-year-old math problem using 64 subagents in parallel. The system did not rely on one long chain of reasoning. It split the problem across many agents, ran different approaches at the same time, used adversarial agents to attack weak arguments, discarded dead ends, and combined the surviving work into a proof. If the proof survives expert review, this changes the economics of R&D. A company will be able to point hundreds of agents at one technical problem, let them search in parallel, and compress days or weeks of investigation into hours. The bottleneck moves from hiring more people to allocating more compute, designing better agent teams, and verifying their output. That will affect every industry built on expensive knowledge work: software, semiconductors, biotech, engineering, finance, and scientific research.