# Theory Beyond Theorems and Proofs
Theoretical computer science is facing a pivotal moment as artificial intelligence begins to reshape the field in fundamental ways. In a guest post hosted by Scott Aaronson, three prominent researchers, Pravesh Kothari, Raghu Meka, and Prasad Raghavendra, share their thoughts on how the theory community needs to adapt to this rapidly changing landscape. Their reflections center on the major conferences in the field, particularly STOC, FOCS, and SODA, and whether the current standards for what counts as valuable theoretical work are keeping pace with reality.
The authors argue that theoretical computer science has long defined itself around a specific culture: rigorous proofs, formal theorems, and mathematical guarantees. While this foundation remains important, the rise of AI is creating new kinds of insights and contributions that do not always fit neatly into that traditional mold. The field may be missing out on important ideas if it continues to evaluate research solely through the lens of classical theorem proving.
The post calls on the theory community to broaden its definition of what meaningful theoretical work looks like in the age of AI. Rather than viewing this moment as a threat, the authors frame it as an opportunity to expand the scope and relevance of theoretical computer science. The conversation they are starting is an important one, and it invites researchers at every level to think carefully about how the field can evolve without losing its intellectual rigor.