🚨 $BETR at $41.50 - everyone's missing the REAL scale here They already did $60B volume in 2021 📊 Now with partnerships superior AI, the path: 📈 6% rates: $40B (7X) → $1B revenue 🚀 4% rates: $100B (17X) → $2.5B revenue 🤯 2% rates: $200B (33X ) → $5B revenue Eric Jackson target: $12,000/share (289X) Here's why it's possible 🧵👇 Long $BETR

That was a dick move in the end Josh Hokit!

President Donald J. Trump arrives for HISTORY AT THE WHITE HOUSE, @UFC Freedom 250.🇺🇸

"We take the stars from heaven, the red from our mother country, separating it by white stripes, thus showing that we have separated from her, and the white stripes shall go down to posterity, representing our liberty." —George Washington

They chose that headline and photo on purpose. It’s clear they are hoping to inspire the next Luigi Mangione. We still don’t hate journalists enough.

Happy Flag Day 🇺🇸

The National Anthem at the White House was absolutely epic!!! 🇺🇸🔥 Wait for the flyover!!!!

Happy Birthday to the 45th and 47th President of the United States, Donald J. Trump. A relentless patriot who fights every day for the country he loves, the people he serves, and the American Dream. 🇺🇸🇺🇸

.@DanaWhite and @RealDonaldTrump have arrived at #UFCWhiteHouse.

UNBELIEVABLE flyover at @UFC Freedom 250 🇺🇸 God Bless America.

Land of the free. Home of the brave. 🇺🇸 @UFC Freedom 250 has KICKED OFF!

Who’s watching @ufc on @paramountplus ?

If I had 6 months to become an Agentic AI Engineer. I'd do this. Stage 1: Python Async Foundations asyncio, FastAPI, event-driven architecture, error handling, API integration patterns. Stage 2: LLM Fundamentals for Agents Context management, model routing, token economics, latency tradeoffs, failure modes. Stage 3: Tool Calling Structured Outputs Pydantic validation, function calling schemas, error recovery, dynamic tool discovery. Stage 4: Memory State Management Short-term buffers, long-term vector recall, context compression, cross-session sync. Stage 5: Single Agent Workflows ReAct loops, plan-and-execute, self-reflection, iteration limits, graceful degradation. Stage 6: Multi-Agent Orchestration LangGraph/CrewAI, supervisor patterns, message passing, conflict resolution, handoffs. Stage 7: Human-in-the-Loop Systems Uncertainty detection, approval gates, audit trails, resume logic, intervention points. Stage 8: Evaluation Quality Assurance Automated eval harnesses, LLM-as-a-judge, regression testing, hallucination metrics. Stage 9: Observability Tracing Distributed tracing (LangSmith/Arize), cost dashboards, latency monitoring, alerting. Stage 10: Security Guardrails Prompt injection defense, output filtering, PII redaction, sandboxed execution, compliance. Stage 11: Production Deployment vLLM/SGLang, Kubernetes scaling, CI/CD for agents, canary releases, rollback strategies. Stage 12: Open Source Portfolio Ship autonomous agents publicly, write architecture docs, record demos, contribute to libs. Most people stay stuck watching tutorials. Builders get hired. (Bookmark it)

California is one of the most dynamic places on the planet. But it is a case study in how a rich society can spend more and more while producing less and less of what its ordinary citizens need. My take:

🚨 Friedberg on Los Angeles ‘Elections’ “Your rights to have an election are gone. You are a citizen of those who tell you who your overseers are … So enjoy the ones that have been made appointed by those who have constructed the matrix.”

Just a reminder that our Native Senator who hates the oligarchs flies private.

His mom taught computer science. He built the infrastructure that powers the world's AI. Meet Rahul Patil, current CTO of Anthropic. > Born and raised in Bengaluru. Mom was a computer science teacher. > Studied at Baldwin, Joseph and PES University. > Not an IIT kid. Not a Stanford dropout. > Just a kid who grew up watching code at home. > Worked at Microsoft. > Then Amazon. > Then Oracle. > Then Stripe as CTO for 5 years. > 20 years building invisible infrastructure. > The systems nobody sees but everyone depends on. > October 2025, Anthropic called. > Not for research. Not for AI breakthroughs. > For infrastructure. > Compute. Inference. Scaling. > The unglamorous work that makes everything else possible. > Why Anthropic hired him? > Because Claude's infrastructure is cracking under demand. > OpenAI and Meta are spending billions on compute. > Anthropic needs someone who's scaled systems at the biggest tech companies. > "Impossible things are possible in India." > That's what he said at the developer summit. > A Bengaluru kid. A CS teacher's son. > Now building the backbone of AI. Absolute legend.

FOR THE FIRST TIME IN 53 YEARS, THE KNICKS ARE NBA CHAMPIONS 🏆 New York defeats San Antonio 4-1 in the NBA Finals, capturing their third championship in franchise history!

I don't care what kind of hardware you have, you should be running local models Governments are now banning models. They’re determining what technology you can and can’t use With local models, you are free and nobody can control you Even if you're on the cheapest Mac Mini you can be doing this Here's a complete guide: 1. Download LMStudio 2. Go to your OpenClaw/Hermes and say what kind of hardware you have (computer and memory and storage) 3. Ask what's the best local model you can run on there (probably will be Gemma 4 or Qwen. if you have a big computer, it will be GLM) 4. Ask 'based on what you know about me, what workflows could this open model replace?' 5. Have OpenClaw walk you through downloading the model in LM Studio and setting up the API 6. Ask OpenClaw to start using the new API Boom you're good to go. You just saved money by using local models, have an AI model that is COMPLETELY private and secure on your own device, did something advanced that 99% of people have never done, and have entered the future. If you are on smaller hardware you probably are not going to replace all your AI calls with this, but you could replace smaller workflows which will still save you good money Own your intelligence.