A single researcher solved 6 open Erdős problems in 5 days using GPT-5.6 Sol.
He attempted 13 problems in total， so the success rate sits near 46%.
He wrote the prompt almost as a contract， not a question.
It restated the problem， then spelled out what a finished proof must actually establish. listed the weaker results that would not count， so near-misses could not sneak through.
Known traps and edge cases went in before the model ever started thinking. Then he told it how to search， which is where most people stop.
Chase many approaches at once， keep incompatible ones alive， and never commit early.
Hunt for counterexamples to your own lemmas， and kill a route that only leads to another open problem.
Separate adversarial agents then tried to break every draft that survived.
None of this works without the right target， so he picked problems mathematicians already argue about， avoiding anything welded to a famous conjecture.
Codex held the whole search in memory for hours while that loop ran itself.