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destroying heuristic determination in 4 dimensions to flood the engines with diversity and a lot of swear words

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upvoted a changelog about 2 hours ago
Hugging Face Papers for AI Agents
repliedto CRAFTFramework's post about 8 hours ago
Quick observation from working with Claude Cowork on multi-session projects. **The constraint:** Cowork runs in a sandboxed VM that resets between sessions. No state persistence, no conversation carryover, no cross-session memory. Each session starts with zero context about prior work. ``` https://craftframework.ai/the-hidden-cost-of-session-amnesia-why-context-matters-more-than-you-think/ ``` Within a single session, context compaction occurs as conversations approach the token limit — the system summarizes earlier exchanges, trading detail for capacity. Decisions made early in a session degrade to single-sentence summaries as the conversation grows. **The cost:** For task-based work (summarize this, debug that), this is irrelevant. For cumulative work — projects that build over days or weeks — it creates significant overhead. Users spend meaningful time each session re-establishing context that the AI previously held. **Common workarounds observed:** - Manual context injection (copy-paste at session start) - Single mega-sessions (avoids reset, but context degrades) - External state documents (maintained alongside the AI) Each trades one form of overhead for another. **The architectural question:** Claude's chat interface (claude.ai) now has persistent memory — free for all users since March 2026. But the desktop environment still operates on a session-reset model. The gap between chat-based memory and desktop-based amnesia is growing. This seems like a general problem for desktop AI tools, not just Cowork. How are others approaching session continuity in local AI environments?
updated a collection about 15 hours ago
🍺 The Bartenders 🍺
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