honcho

Cross-session memory management allows AI peers to retain user context across conversations by modeling users and managing per-peer memories, ensuring consistent dialogue continuity without losing prior session data.

You configure per-profile memory settings in honcho.json by defining observation toggles, recall modes, and dialectic controls. This file manages how memory sync operates for each distinct profile host block within the Hermes CLI integration.

Yes, you can use separate memory contexts for different AI peers by setting up multi-profile configurations. This approach manages distinct per-profile contexts within Hermes, isolating memory recall and observation behaviors for each peer.

Hermes CLI integration with Honcho requires initializing Honcho for a Hermes profile, configuring memory settings via honcho.json, and defining per-profile host blocks. Running a status check verifies the configuration is active.

Memory sync may fail between Hermes profiles if honcho.json is misconfigured or per-profile host blocks are missing. Troubleshooting involves verifying observation toggles, checking recall modes, and ensuring dialectic controls match the host configuration.

You should adjust dialectic controls and observation toggles when you need to tailor session context budgets or change how the AI peer recalls and processes user modeling data across different cross-session interactions.