🧵Storacha and Phala: Private AI Agent Memory In short: Storacha and Phala support encrypted memory for AI agents. Stracha handles fast, verifiable storage on Filecoin. Phala runs confidential computation. Filecoin provides persistence, proof, and data integrity for the agent memory. 1/ Background @storachanetwork and Phala share a setup for private AI agent memory. The focus is on encrypted data, persistent storage, and confidential execution. This model is geared towards agents that run for long periods and require memory retention after sessions. 2/ Storage Storacha provides hot storage based on IPFS addresses and Filecoin support. Data is always under user control, and content is addressable and verifiable. Filecoin supports persistence and redundancy, ensuring agent memory remains available across different nodes and in case of failure. 3/ Computation @PhalaNetwork provides confidential computation through trusted hardware. Code and data remain hidden from node operators. Agents can use private memory and keys in execution paths not supported by public smart contracts. 4/ Roles Each layer strictly adheres to its respective responsibilities. @Filecoin uses decentralized proofs to protect data at rest. Stracha manages fast access. Phala handles off-chain private execution. This architecture lowers the trust assumptions across the entire technology stack.