Rigel Tech Group @rigeltechgroup

Anthropic Engineer Andrej Karpathy: "The biggest mistake in AI right now: people are forcing agents to work instead of mastering the model first. We made that mistake in 2016 at OpenAI. It cost us 5 years." What Karpathy actually means: step 1 → stop forcing your agent to do everything. Understand the model underneath first. step 2 → demos are easy; products take a decade. Self-driving proved it. If you skip the foundation, everything breaks. step 3 → the agent is not the product. The foundation is. Build that—and agents emerge on their own. "You're building agents right now. You're at the forefront. Not OpenAI. Not DeepMind. You." watch - bookmark

🚨🚨🚨 COMPUTER EMERGENCY?! 🚨🚨🚨 Frozen screen. Weird pop-up. "Why won't this just WORK." ⚡ Instant Remote Support — available NOW. 📞 Get help before you throw your laptop out the window. #TechSupport #RemoteSupport #ITHelp

Mark Zuckerberg just told the world his own company shouldn’t exist. Zuckerberg: “I just think in the future almost everyone is gonna have the power of a 10,000-person organization.” He runs Meta. 70,000 employees. He just described a future where one person replaces all of them. And he’s the one building it. That is not a prediction about technology. That is a CEO engineering the obsolescence of his own workforce. While they watch him do it. Every company, every government, every university, every hospital on Earth was built on a single premise. No one person could do it alone. That is not a feature of civilization. It is the foundation. Every hierarchy, every org chart, every payroll ever written exists because of that one limitation. Zuckerberg just announced the limitation is ending. So follow the logic where it leads. If one person can produce the output of ten thousand, what is one person worth? Now look at the word “everyone” in his sentence. Because this does not land on everyone. It never has. The printing press was sold as liberation. It built media empires. The internet was sold as liberation. It built trillion-dollar platforms. The tool always arrives as freedom. It always settles as leverage. And leverage always consolidates upward. Zuckerberg does not gain the power of 10,000 people. He already has that. He gains the power of 10,000 organizations. Zuckerberg: “If the intelligence of a 10,000-person company is not greater than the intelligence of a single person, then what are we doing here?” He was making a case for building AI. Read that again as an employee. A man who commands 70,000 people just questioned whether their collective intelligence exceeds one person’s. That is not a vision for the future. That is the most honest thing a CEO has ever said out loud about the people who built his empire.

Try Grok Build x.ai/cli

X Freeze @XFreeze

2 weeks ago

Just press Ctrl + Space in Grok Build and start talking Grok's Speech-to-Text is incredibly accurate, transcribing your prompts in real time as you speak It makes interacting with your coding agents feel completely natural Instead of pausing to type every instruction, you can

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GPT-5.6 is absolutely f*cked at trading. They connected it to live options flow, dark pool prints, and SEC filings through Skills. Then gave it one prompt: "Find me whale trades where institutions are positioning before the move." Look at what it built.

Xynth @xynth_m

2 weeks ago

If you're a trader still not using AI you're f*ckd. We connected Claude Fable-5 and GPT Sol 5.6 to the entire stock market and gave it a virtual machine to go wild. Insane levels of alpha have been generated thus far. Heres how it works:

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THIS DEVELOPER JUST KILLED THE ENTIRE VOICE CLONING INDUSTRY WITH ONE GITHUB REPO Claude now speaks in your own voice across 23 languages through a single MCP call. Free. Local. Offline. ElevenLabs charged $22-$330 a month for what Jamie Pine just gave away under an MIT license. Claude Code, Cursor, and Cline hook in with one command and start replying in your cloned voice straight from the terminal. → developer Jamie Pine dropped the repo jamiepine/voicebox on GitHub 41.6k stars in a matter of weeks → clones any voice from 10 seconds of audio, seven TTS engines to choose from → runs on your own machine via Tauri (Rust, not Electron) voice and samples never leave your computer → Claude Code, Cursor, Cline, and any MCP-aware agent speak back in your chosen clone through a single voicebox.speak call → plus global dictation with one hotkey inside any app → generate content in Arabic, Japanese, or Polish without opening your mouth Replaces ElevenLabs and WisprFlow in one MIT-licensed app. Bookmark this for the moment you want to give your agent a voice, repo below 👇🏻

AdiiX @adiix_official

2 weeks ago

ANTHROPIC JUST CHANGED THE ENTIRE AI-SLOP FRONTEND. It’s called Frontend Design, the official Anthropic skill for Claude Code. And it already has 161,000 stars on GitHub. The problem it solves is simple: Every time you asked AI to build a website, you got the same thing.

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Stop buying expensive $500 courses to learn AI. I’ve already done it for you. With one list: Straight to the point. Zero confusion. And no fluff. Spend a day mastering Claude here: claude101.com Claude 101: ruben.substack.com/p/claude-for-d… Claude Fable-5: ruben.substack.com/p/dont-use-cla… Claude Cowork: ruben.substack.com/p/learn-80-of-… Claude Code: ruben.substack.com/p/the-claude-c… Claude Skills: ruben.substack.com/p/claude-skills Claude Design: ruben.substack.com/p/claude-design Claude for Excel: ruben.substack.com/p/how-to-make-… How to Prompt: ruben.substack.com/p/prompt-47 Claude + Linkedin: ruben.substack.com/p/claude-linke… Be good at Claude: ruben.substack.com/p/s Stop writing like AI: ruben.substack.com/p/its-not-x-it… Claude for your team: ruben.substack.com/p/claude-for-t… Claude Connectors: ruben.substack.com/p/claude-conne… Set up Claude Cowork: ruben.substack.com/p/claude-cowor… Stop Prompting Claude: ruben.substack.com/p/stop-prompti… Claude to sound like you: ruben.substack.com/p/youre-just-a… Stop hitting Claude limits: ruben.substack.com/p/how-to-stop-… Stop using Claude at work: ruben.substack.com/p/how-to-use-y… 1. Save this list for later (three dots, top right). 2. Share it with a friend by ♻️ reposting this image. 3. Subscribe to my free newsletter: how-to-ai.guide.

Ruben Hassid @rubenhassid

2 months ago

x.com/i/article/2057…

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Software Engineering is changing. Not slowly. Structurally. OLD ENGINEER │ ├── Writes code manually ├── Solves isolated problems ├── Focuses on implementation └── Uses AI as a helper ↓ NEW ENGINEER │ ├── Frames the right problems ├── Provides context + constraints ├── Reviews architecture & trade-offs ├── Orchestrates AI agents └── Builds systems, not just code The shift: Autocomplete → Assistants → Context-aware tools → Agentic workflows And now? AI doesn’t just help you code. It helps you think, decide, and execute. 🔥 What actually matters now: • Systems thinking • Architecture judgment • Code review skills • Debugging complex flows • Security & reliability • Task decomposition 🚀 What to learn next: Repo-aware prompting Reviewing AI-generated code Eval + test-first workflows Agentic workflow design Guardrails + safe automation The future engineer won’t just write code. They’ll orchestrate systems at scale. If you're still only coding… you're already behind. 💬 Comment your thoughts ♻️ Repost to help your dev circle

THAT'S RIGHT. 🇺🇸

Building AI Agents from Scratch Tutorial Series (AI Era Edition) in 30 days.( If interested say hi 👋) Master modern AI agent engineering by building production-ready autonomous AI systems from the ground up. 1. Day 1: What Are AI Agents? – LLMs, Agents, Workflows, and Autonomous Systems Project: Build your first AI chatbot agent. 2. Day 2: Setting Up the Development Environment – Python, VS Code, APIs, and Virtual Environments Project: Configure a complete AI agent development workspace. 3. Day 3: Understanding Large Language Models (LLMs) – Prompting, Tokens, Context Windows, and Reasoning Project: Connect your application to an LLM API. 4. Day 4: Prompt Engineering for AI Agents – System Prompts, Instructions, and Few-Shot Learning Project: Build a prompt-driven coding assistant. 5. Day 5: Agent Architecture – Planning, Reasoning, Memory, and Actions Project: Design a reusable AI agent framework. 6. Day 6: Building an Agent Loop – Observe, Think, Plan, Act, and Reflect Project: Create an autonomous task execution agent. 7. Day 7: Tool Calling and Function Calling Project: Build an AI agent that uses weather and calculator tools. 8. Day 8: Memory Systems – Short-Term, Long-Term, and Vector Memory Project: Create an AI assistant that remembers previous conversations. 9. Day 9: Retrieval-Augmented Generation (RAG) Fundamentals Project: Build a PDF question-answering agent. 10. Day 10: Embeddings and Vector Databases – FAISS, ChromaDB, and Pinecone Project: Create a searchable knowledge base. 11. Day 11: AI Agent Planning Strategies – ReAct, Chain-of-Thought, and Tree of Thoughts Project: Build a reasoning-based planning agent. 12. Day 12: Multi-Step Workflows and Task Decomposition Project: Build an AI research assistant. 13. Day 13: AI Agents with MCP (Model Context Protocol) Project: Connect an AI agent to external developer tools using MCP. 14. Day 14: AI Agents with LangChain Project: Build a document analysis agent. 15. Day 15: AI Agents with LangGraph Project: Build a stateful multi-step AI workflow. 16. Day 16: AI Agents with OpenAI Agents SDK Project: Create a customer support AI agent. 17. Day 17: Browser Automation Agents Project: Build an AI web automation assistant. 18. Day 18: Computer Use Agents Project: Create an AI agent that automates desktop tasks. 19. Day 19: Coding Agents and Software Engineering Assistants Project: Build an AI code review assistant. 20. Day 20: AI Agents with APIs and Databases Project: Build an AI-powered CRM assistant. 21. Day 21: Multi-Agent Systems – Collaboration and Communication Project: Build a team of specialized AI agents. 22. Day 22: AI Agent Security, Guardrails, and Safety Project: Secure an AI agent against prompt injection. 23. Day 23: AI Agent Evaluation and Benchmarking Project: Build an automated testing framework for agents. 24. Day 24: Voice AI Agents – Speech-to-Text and Text-to-Speech Project: Build a voice assistant. 25. Day 25: Vision AI Agents – Image Understanding and Multimodal Models Project: Build an AI image analysis assistant. 26. Day 26: AI Agents with Local Models – Ollama, LM Studio, and Open-Source LLMs Project: Run an offline AI agent locally. 27. Day 27: Deploying AI Agents – Docker, Cloud, CI/CD, and Monitoring Project: Deploy a production-ready AI agent. 28. Day 28: AI SaaS Architecture – Authentication, Billing, and User Management Project: Build an AI Agent SaaS platform. 29. Day 29: Scaling AI Agents – Performance, Cost Optimization, Caching, and Observability Project: Optimize an enterprise AI agent deployment. 30. Day 30: Final Capstone Project – Build a Production-Ready AI Agent Platform with Memory, RAG, MCP, Tool Calling, Multi-Agent Collaboration, Authentication, Docker Deployment, Monitoring, and Cloud Hosting. Grab the Building AI Agents from Scratch Ebook: codewithdhanian.gumroad.com/l/jozop #AIAgents #AgenticAI #LLM #ArtificialIntelligence Follow @e_opore to learn more.

99% of people use AI wrong. This Prompt Engineering Cheat Sheet changes everything. 🧠

Everyone talks about prompt engineering. Almost nobody talks about thought engineering. The biggest ROI from AI isn't writing faster. It's thinking better. If your prompts never challenge your assumptions, you'll just automate your existing biases. These 20 prompts are designed to do the opposite:

Who is RTG? We are a small diverse IT staff centered on cross-functional mentorship, clear performance alignment and Supporting small businesses for over 20 years. Our team members have skill sets across many modalities, from Network Cabling to Helpdesk, Networks and Cloud!

June 14, 2026

@EngineeredEV They need to understand an engineer's value in this economy.

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