Switching Models Shouldn't Mean Starting Over | Walrus Protocol's Kimberly Logan
10. Switching Models Shouldn't Mean Starting Over | Walrus Protocol's Kimberly Logan
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Show: Chain of Thought
Host / guest: Not listed
Focus: Agents for Everyone
Date: October 7, 2026
Duration: 38:00
Topics:
Summary: Host Conor Bronsdon interviews Walrus Foundation product lead Kimberly Logan about preserving AI agent memory when switching models or agent harnesses. The discussion distinguishes dumping old chats from preserving structured, selectively accessible, portable experience. Questions include storage provenance, verifiable retrieval, ownership of remembered preferences and the costs of context migration. It also raises the possibility that decentralized storage could enable durable memory without requiring one assistant provider, while providing no independent proof that Walrus's implementation solves every data governance problem. The episode is sponsored by Walrus and the interviewee's product assertions should be treated as claims. Its full show notes and transcript were checked in the previous day's verified media evidence; an audio listen-through is not claimed.
Why it matters: Anyone building a long-lived personal or team agent should separate task procedures, permissions and durable context from model-vendor identity. This complements today's Agent Skills recipe: version the procedure and make its source data portable and auditable.
Connection to the brief: Anyone building a long-lived personal or team agent should separate task procedures, permissions and durable context from model-vendor identity. This complements today's Agent Skills recipe: version the procedure and make its source data portable and auditable.
Coverage: Selected for this edition.
Listen / watch: Chain of Thought