Cryptographic proofs for AI outputs remain computationally expensive and difficult to scale. Community discussions on Lobste.rs highlight the gap between theoretical zero-knowledge proofs and practical deployment for LLMs. These hurdles prevent users from verifying that a model actually ran a specific prompt. Developers must wait for more efficient verification schemes to ensure trustless inference.