THE ROBOT IS FOLLOWING HER, NOT THE CAMERA 🤖
A long street of palm trees, parked cars and blue sky all the way down.
Mint mini dress, white sneakers, a black tote bag. Right behind her walks a white humanoid robot with a black face.
At 0:03 she turns, points at something across the road and the robot slows down too.
At 0:06 she walks on and the robot keeps the same step behind her.
At 0:09 she glances back to check it's still there.
Twelve seconds, one girl, one very loyal machine.
Would you trust it to carry the bag?
The article attached to this post is the other side of clips like this: 5 AI characters, 60 days, $91K 👇
FUCK, THIS KID MAKES $20K
USING A NEW METHOD COPYTRADING MILLIONAIRES🤯
Check: https://t.co/EHckQIYkdh
This kid discovered a new way to follow millionaire trades. Here’s the FULL tutorial on how to copytrade using FOMO:
Sean, a crypto insider, shared his strategy for tracking smart money, following millionaire wallets, and identifying potential memecoin opportunities before they attract widespread attention.
With memecoins gaining more exposure on platforms like Robinhood, traders are constantly searching for the next coin with huge upside potential.
Instead of gambling on random coins and hoping they pump, FOMO lets you monitor experienced traders and study their moves.
Here’s how to use FOMO:
→ Copy millionaire traders: Check the leaderboard, discover successful wallets, and review their previous trades.
→ Track whale wallets: Monitor smart money movements to see which memecoins major wallets are buying or selling.
→ Find potential insiders: Identify wallets making unusual moves and dig deeper into their transaction history.
→ Follow top performers: Subscribe to selected wallets and stay updated on their latest trades.
→ Build a smart wallet watchlist: Track multiple wallets in one place instead of manually checking every transaction.
The best part? You don’t need to be a professional trader to get started.
I’ve put together a list of 400 top insider, millionaire, and whale wallets trading memecoins.
I’m sharing this list so you can research these wallets and track their activity yourself.
Comment “SMART WALLETS”
and I’ll send you the list.
GROK DOESN’T CONTROL THE MACHINE BECAUSE IT IS SMART.
IT CONTROLS IT BECAUSE THE STACK GIVES IT STRINGS TO PULL.
a model can generate an answer.
an agent system can remember what happened, choose a tool, delegate work, operate a browser and prove whether the action succeeded.
that difference is infrastructure.
here are 10 real GitHub repositories for turning Grok into something closer to an operating layer:
(1/10) xAI Python SDK
connect Grok to search, code execution, tools and external systems
▸ https://t.co/ZnR9doaFbg
(2/10) xAI TypeScript SDK
build typed Grok applications, tool calls and agent workflows in TypeScript
▸ https://t.co/vYhvy8TVsh
(3/10) Grok Build
inspect xAI’s own open coding-agent harness and terminal interface
▸ https://t.co/2x1Y3bE7Nq
(4/10) xAI Plugin Marketplace
give the agent reusable capabilities instead of writing every integration from zero
▸ https://t.co/qwgVFEiF63
(5/10) LangGraph
turn isolated prompts into durable workflows with state, checkpoints and controlled branches
▸ https://t.co/FmLW7pexb8
(6/10) CrewAI
split one large objective between specialized agents with separate responsibilities
▸ https://t.co/pALg8jdMKc
(7/10) Microsoft Agent Framework
orchestrate production-grade agents, handoffs and multi-agent workflows
▸ https://t.co/302fU1jtYR
(8/10) Mem0
give the system persistent memory across users, sessions and agent runs
▸ https://t.co/xZbzhPJeTn
(9/10) Browser Use
give the agent eyes and hands inside a real browser
▸ https://t.co/HJVEAHv7ya
(10/10) AgentOps
trace decisions, inspect failures and measure what the agents actually did
▸ https://t.co/DGNRMOkF79
the architecture:
Grok
→ tools
→ workflow
→ agent team
→ memory
→ browser
→ traces
→ verified action
none of these repositories is Grok Bot’s private source code.
they are the open building blocks for recreating the same primitives around the model.
Grok supplies the intelligence.
the stack supplies the memory, hands, eyes and nervous system.
the model produces an answer.
the infrastructure decides whether that answer can move a real machine.
save this before your Grok agent gets a brain — but no strings to pull ↓
OTD 20 years ago, the Cardinals and Mets played one of the most memorable Postseason games ever
An unbelievable catch, a clutch home run from an unlikely source and the game ending with the bases loaded? Game 7 of the 2006 NLCS had it all 🍿