Evaluating Very Long-Term Conversational Memory of LLM Agents — HN submission

Sun, 01 Mar 2026 04:55:07 GMT

Show HN: Engram – Memory for AI coding agents (2.5K installs, 80% on LOCOMO)

Engram gives AI coding agents persistent memory across sessions. 2,500 npm installs in the first five days. The problem: every Claude Code or Cursor session starts from zero. You re-explain your architecture, conventions, past decisions. CLAUDE.md helps but it's manual and doesn't scale. Engram runs as a native MCP server. One command to install, SQLite backend, no infrastructure. Three tiers of memory: Explicit: things you tell it to remember Implicit: behavioral patterns extracted from how you work (low confidence, reinforced over time) Synthesized: meta-observations generated during…

1 point; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.

Evaluating Very Long-Term Conversational Memory of LLM Agents — HN submission

Sun, 24 Aug 2025 20:42:16 GMT

Evaluating Long-Term Conversational Memory of LLM Agents

1 point; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.

Evaluating Very Long-Term Conversational Memory of LLM Agents · HackerPapers discussions

Evaluating Very Long-Term Conversational Memory of LLM Agents — HN submission

Evaluating Very Long-Term Conversational Memory of LLM Agents — HN submission