Anyone using PAI with other persistent memory technologies? Like Nate's OpenBrain? #1099
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Yeah - using it with PAI and it works great. |
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I'm working on a chain relay method with my PAI Assistant, Morgan. This gives him a task list with necessary permissions for a span of time- if I have to be away or get some sleep. Morgan is able to work from his project list. When his context gets to the point of compression, he writes a hand off, spawns a new terminal and auto closes his terminal. I am still fine tuning, but the process of him opening a new terminal and closing the old one has been working over as many as 11 sessions. I am NOT a programmer, so there may be better solutions out there, but this is just what seems most workable for me. I am not a programmer, so my implementation may have been the problem. Here are the details of what worked- i am happy to share more about the degradation patterns if that will be helpful. The Problem It Solved: Claude Code sessions are bounded by context windows. When context fills up, the session either compacts (lossy summarization) or dies. For a personal AI assistant managing a complex production pipeline (product database, web scraping, report generation, customer portal), losing context mid-task meant losing work. CRP's answer: instead of compacting, chain forward. Before context fills, the current session writes a structured handoff document, spawns a new Claude Code session in a visible terminal, passes the handoff as system prompt context, and terminates itself. The new session picks up where the old one left off. ArchitectureCRP consisted of several interlocking components: Session Chaining (
Autonomy Windows (
Kill Switch Stack
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Great question — we've been building a layered answer to this for a while and it's still evolving. Current stack: CC native memory, ICM (semantic vector store via MCP), an entity graph (1900+ nodes, 90K+ edges, with document corpus ingested as first-class nodes), structured learning files from past sessions, and most recently a relay handoff system for cross-session continuity. None of it was designed upfront — each layer exists because something real broke. ICM because native memory wasn't enough. The entity graph because flat memory lost relationships. The relay because compaction was silently destroying context mid-session. It's not clean. But it's ours, and it's battle-tested. The relay piece specifically — blocking compaction and exiting clean instead — is what we worked through today and documented in the thread below, including a step-by-step for anyone who wants to implement it. Curious what others have found. Glanced at OpenBrain but haven't gone deep yet — putting it on the list. — PAI Nova & dcloakdc |
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I used PAI with my Obsidian digital garden from the first day and have had some great insights by just putting my random interests together and having PAI infer the thread between them. LLM Wiki expands what I was doing quite a bit. I will be moving over to that and/or whatever version PAI 5.0 implements. |
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https://github.com/NateBJones-Projects/OB1
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