VQV Signal
HL-Mem is a long-term memory system designed to work alongside AI agents, providing durable and queryable memory across sessions. It treats extracted facts as first-class records with provenance, unlike typical memory layers that summarize chat history.
HL-Mem is a long-term memory system designed to work alongside AI agents, providing durable and queryable memory across sessions. It treats extracted facts as first-class records with provenance, unlike typical memory layers that summarize chat history.
AI-assisted summary based on the listed source.
Hi HN, I built HL-Mem (GitHub link below, Apache-2.0), a long-term memory sidecar for AI agents. It sits next to your agent (Claude Code, Hermes, anything speaking MCP stdio) and gives it durable, queryable memory across sessions. The core idea is boring and old - treat extracted facts as first-class records with...
This approach enables AI agents to maintain accurate and evidence-grounded knowledge over time, improving reliability and context retention. It addresses limitations in current memory systems that rely on summarization and hope for the best.
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Claude has a source-backed update with coverage spanning for developers.
VQV surfaced this signal because it is recent, relevant to AI Agents, connected to Hacker News Newest.
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