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Show HN: An agent that remembers across sessions (no chat history)

Hi HN — I built this in my off-hours over the last 3 months. Sharing now because I just filed the provisional patent yesterday (US 64/050,345) and the repo is freshly public. The frustration that started it: every time I use a coding agent (Cursor, OpenCode, Aider, Claude Code, etc.), it eventually loses context — forgets the SSH address, re-asks for the DB password, tries to redeploy to localhost when the server is remote. The "proper" answer is "set up 10 specialized agents with short context windows." I'm too lazy for that. The conventional architecture is the actual problem. Every turn re-sends the full conversation, the model recomputes attention from scratch, and cost compounds with conversation length. Long-running agents are economically infeasible by design. What I built: NLS captures the model's own computed K/V states (and recurrent states for hybrid models like Qwen3.5-MoE) after each turn, persists them to disk, and re-injects them into the cache on the next turn — at the right positions, with proper alignment. The model behaves as if it had the full conversation in context, but the conversation is never re-sent. Validated across three settings, in increasing order of stringency: (1) Standard conversational recall: 5/5 on a 5-fact production test. Baseline check. (2) LongMemEval (published cross-session benchmark, ~19K sessions). On the 18-question "fully answerable" subset: Condition Qwen 3.5 Qwen 3.6 Memories provided as TEXT in the prompt 8/18 9/18 Same memori