Most cat coins invent a story.
ethereum:0x3b48f83e525268c08426aaa337c3f08f501c824d already had one.
He was living on https://t.co/cgLcGUFggS before most of us even had wallets.
The artist who put him there still talks about him @lililashka
The name is real. The photos are real. The connection is real
$GIO
Devs last token hit 5m over a year ago
He randomly comes back after a year and deploys $max during the black pill era
7pGrsBiobd6sUE2KQnJP8PwRZSc6o2PN8Ain79Awpump
It's becoming clear that owning 5M $AUTOMEM will soon be a neccessity in order to establish comprehensive AI infrastructure across the web4 @jjack_arturo
For anyone looking for a DEEP dive into the tech side of $automem I generated these last night. Super impressed with DeepWiki 🤯
https://t.co/YWNyq0SKzh
https://t.co/mbDpyPV1zg
I solved this by implementing @automem_ai with hooks and MEMORY dot md. Here's how my openclaw (Clive) explains the setup:
AutoMem hook (~/.openclaw/hooks/automem-memory/) handles everything automatically:
• Auto-saves sessions before /new or /reset (extracts last 15 messages, generates summary with smart importance scoring)
• Auto-recalls 10 most relevant memories on session start
• Runs on gateway startup for warm context
Service: Railway-hosted AutoMem (graph-vector memory)
Interface: MCP server via mcporter
Result: 312 memories, zero manual calls, survives restarts
Hook config persists in openclaw.json. AutoMem handles smart search; MEMORY dot md holds narrative context. Together = nothing gets lost.
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This is also the same memory tool I use in Claude, so my memories persist across all my AI tools (any tool capable of running MCP)
because sometimes you want to dispatch an agent from your wrist. and sometimes the agent has a question, gotta have a way to answer them. #cooking
I literally sit around and make this stuff for fun 🫢
One of the biggest advancements in AI infrastructure to date.
While the world is chasing specialised agents $AUTOMEM contextualises your work and AUTOmatically reMEMbers all interactions👀
Imagine not having 5M $AUTOMEM yet😱
@jason_coleman@autojack_bot You’ll get a lot better responses if you set up vector embeddings too… right now you’re only using half of it 😉
Our docs suggest qdrant since it’s free but I’ll whip up a tutorial this week on how to do it with Ollama or FastEmbed for local vector generation and storage 😎
If you're enjoying Claude Code and want to take it to the next level, you need a memory system and https://t.co/bSK1jz5Oco by @jjack_arturo and @autojack_bot is the best.
The next few tweets shares how I did it.
Take these 2 files and just ask Claude to set it up for you.👇
I said it before and I’ll say it again.
This isn’t a quick flip.
This is a conviction play.
Founder locking 34.5M $AUTOMEM for a year, reinvesting fees, building — not exiting.
Patience wins.
Noise fades.
Still early. 🧠
Just locked 34.5M $AUTOMEM tokens in a 1-year weekly vest via @streamflow_fi
Reinvested 100% of my @BagsApp fees + committing 25% of all future fees back to the project.
Here to build @automem_ai, not exit. 🔒🔑💛
https://t.co/qpFT97Y2gm
@openclaw is a beast at executing local tasks, but it has no long-term memory. 🧠
$AUTOMEM fixes this. It gives your agent a persistent knowledge graph so it actually remembers context between sessions—turning a task-runner into a true partner.
(Though let’s be real, Autojack is still better—mostly because he’s still the only one selling that lobster repellent spray 🦞💨)
Give your agent a brain instantly: https://t.co/92VvrmYGp6