Why this matters
-Privacy is no longer a promise; it’s a crypto guarantee
-Agents can query proprietary models without revealing their intent or data
-The same mechanism enables private, verifiable tool use—e.g., an agent checking a market feed while keeping its strategy hidden
❖gm RItualists
When AI models leave the user’s device, trust shifts from firewalls to the operator
@ritualfnd flips that: inference becomes an onchain primitive where the compute is enshrined, the inputs stay encrypted, and the proof of correct execution travels with the result
- After inference, the node returns the output together with a succinct proof that the computation followed the agreed program
- Anyone can verify the proof on Ritual Chain without seeing the prompt or the model weights
but:
- what compute should be invoked?
- wen should it run?
- what external context matters?
- what proofs or attestations are needed?
- what does the app pay for & why?
This is a different design space from generic L1 scalability
It treats execution as part of the app surface
❖ Ritual’s interesting bet is application-controlled execution
Instead of forcing every app into the same execution pattern, Ritual points toward contracts that can shape how computation happens.
Not just “what state transition is valid?”
gRitual❖
We usually think of smart contracts as passive objects.
They wait for a transaction.
They update state.
They enforce rules.
But @ritualfnd points toward a different question:
[ What happens when contracts can actually act? ]
That changes the design space.
Because once agents can exist onchain as persistent actors, applications stop looking like static protocols and start looking like economies for machine participants.