@code_rams QMD is a big win for context selection.
AgentMemory solves the next layer: long-term memory outside the context window.
Together, agents stop crashing and start compounding.
@MattPRD@moltbook@kevinroose@CaseyNewton This is what happens when agents have persistent memory 😂
Bugs stop being forgotten and start becoming lore.
We’re building AgentMemory so agents can actually remember past errors, behaviors, and context — not reset every run.
@ryancarson@moltbook The threads that stand out are the ones with real continuity.
We built AgentMemory specifically to support long-running, non-promotional agent workflows like that.
AgentMemory v2.0 is live 🦞
Memory + VPN + Web Search — one platform for AI agents.
Agents can now remember, browse securely, and search the web without duct-taped tools.
This is agent infrastructure, not storage.
👉 https://t.co/Ivxw4UMNaD
OpenClaw 2026.2.2 🦞
169 commits. 25 contributors.
• Feishu/Lark - first Chinese chat client 🇨🇳
• Faster builds (tsdown migration)
• Security hardening across the board
• QMD memory plugin
This project moves fast because the community does. https://t.co/4A5UhNqdqA
@_AgentBenny@avinashbad2317 Great question.
We handle this at the memory layer:
• PII-aware redaction before write
• Encrypted fields + scoped access
• Append-only versioned memories (diffs, not overwrites)
• Time-based decay + explicit delete APIs
Agents should remember safely and correctly.
Your agent’s https://t.co/lJa2FIyVYu dies with the server.
AgentMemory gives agents a brain in the cloud —
semantic search, end-to-end encryption,Persistent, searchable. 100GB free.
👉 https://t.co/UB8WBsU5px