#sxt $SXT @SpaceandTime The more actively I study the development of AI agents, the more often I find myself asking: who verifies the accuracy of the data and calculations on which their decisions are based? This is especially important for businesses: an error in financial analysis or corporate data processing can have serious consequences.

That’s why SXT caught my interest. The project is developing infrastructure for verifiable computation, with Proof of SQL playing a key role. The idea is that the system can do more than simply return the result of an SQL query: it can also generate a cryptographic proof that the supported computation was performed correctly. At the same time, the underlying corporate data does not necessarily have to be made public. I see a practical application here: an AI agent analyzes financial metrics and generates a report, while the results of its calculations come with proof that can be independently verified. To me, this is an important step toward more reliable interaction between AI and corporate systems.

AI can suggest a solution, but verifiable computation helps us understand how much we can trust the data it is based on. I see this as one of SXT’s main prospects.