A skill is just a prompt that fires itself. If you are still copy pasting instructions out of your notes app before every task, this is the fix, and you only have to set it up once. At its core a skill is four things. A prompt saved in one file called SKILL

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30 AI algorithms every data scientist should know. 🤖📊 Master the right algorithms, and turn data into smarter decisions. Follow me @alexhalescoder for more AI information Which one are you learning next? 👇

«"The biggest AI upgrade for research isn't faster answers—it's seeing how the answer was built."» ScienceBuddy plans the task, retrieves evidence, runs analysis, and shows every step in its Trajectory panel. You can inspect the workflow instead of trusting a black box. #AI #ScienceBuddy #AIResearch

Instead of watching another episode of Netflix tonight… Spend 1 hour listening to Demis Hassabis explain where AI is actually going. This 60-minute Cambridge lecture covers ideas that could shape the future of AI for years to come. From the person leading one of the world's most important AI companies. If you want to understand where AI is heading not just how to use today's tools, this is worth your time. One hour. Free. Potentially perspective-changing. Bookmark it. Watch it. Follow for more free AI lectures, courses, and resources.

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🚨 STOP SCROLLING — If You’re Using Claude AI Without Knowing These Techniques, You’re Probably Using Only a Small Part of What It Can Do. Most people use Claude like a normal chatbot: Ask a question → get an answer → move on. But Claude can be used for much more than simple Q&A. This Claude AI Cheat Sheet brings together the models, prompting techniques, project workflows, artifacts, MCP/connectors, Claude Code, skills, hooks, prompt templates, tools, and learning resources you need to build a much more effective AI workflow. Here’s the breakdown 👇

99 viral image prompts for ChatGPT 🚀 Save this for your next creative project. Bookmark it now—you’ll thank yourself later. 🔖

👀 What if you could get back **10+ hours every week**? These 10 AI websites can help you plan, learn, automate, create, and get more done — without spending a dime. ⚡ **Save this list. Your future self will thank you. 🔖** Which one would you try first? 👇

The difference between average and high-leverage AI users is simple: Average users ask for drafts. High-leverage users demand finished work. Try this instruction on your next task: “Do not give me a draft. Do not give me options. Do not ask clarifying questions unless you are completely blocked. Deliver the finished version only. If you make any assumptions, list them at the end.” One small change. Massive reduction in back-and-forth.

🚨GOODBYE CANVA. Claude designs a full brand identity that looks like a $9,000 studio job. Here are 8 prompts to build yours before Monday:👇

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🚀 Marketing in 2026 is evolving fast. Then: Google, Gmail, Ads, WordPress. Now: ChatGPT, Claude, Gemini, Perplexity + AI-powered automation. The real shift? From using individual tools → to building smarter systems. 🤖⚡ #Marketing #AI #AITools #Automation

🚨 𝗕𝗥𝗘𝗔𝗞𝗜𝗡𝗚: Claude AI can now build your entire startup from idea to launch like a seasoned entrepreneur for FREE. No team. No funding. No excuses. Here are 7 Claude prompts to validate your idea, build your business, and start making money faster than you ever thought

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𝗠𝗼𝘀𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝘁𝗵𝗶𝗻𝗸 𝗔𝗜 = 𝗖𝗵𝗮𝘁𝗚𝗣𝗧. Not even close. ChatGPT is what you see. The real AI revolution is the massive ecosystem being built underneath it. This AI Stack Map captures 100+ tools powering modern AI applications. 𝗧𝗵𝗲 𝗺𝗼𝗱𝗲𝗿𝗻 𝗔𝗜 𝘀𝘁𝗮𝗰𝗸 𝗹𝗼𝗼𝗸𝘀 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗹𝗶𝗸𝗲 𝘁𝗵𝗶𝘀: LLMs → OpenAI, Claude, Gemini, Llama, Mistral Agentic AI → LangGraph, CrewAI, AutoGen, CAMEL, Agno RAG → LangChain, LlamaIndex, Haystack, GraphRAG Embeddings → OpenAI, Voyage, Cohere, BGE MCP → Connecting models with tools, data and systems AI Security → Guardrails, Presidio, Lakera, Prompt Security Observability & Evals → LangSmith, Langfuse, Phoenix, Ragas Memory → Redis, Mem0, Zep, Neo4j, Chroma Agent Frameworks → OpenAI SDK, Semantic Kernel, Google ADK, Bedrock Automation → n8n, Zapier, Make, Airflow, Prefect Vector Databases → Pinecone, Weaviate, Qdrant, Milvus, pgvector But here’s the part that matters more than the logos. 𝗧𝗵𝗶𝘀 𝗶𝘀 𝗻𝗼𝘁 𝗮 𝘀𝗵𝗼𝗽𝗽𝗶𝗻𝗴 𝗹𝗶𝘀𝘁. It’s a dependency graph. Your RAG is only as good as your retrieval + embeddings. Your agent is only as reliable as its tools + evaluations + guardrails. Your memory is useless if you can’t observe when context becomes stale or wrong. Your MCP layer becomes dangerous if permissions and governance are an afterthought. And a “best-in-class” stack can still become a terrible production system. Why? Because AI systems rarely fail only inside one component. 𝗧𝗵𝗲𝘆 𝗳𝗮𝗶𝗹 𝗮𝘁 𝘁𝗵𝗲 𝗵𝗮𝗻𝗱𝗼𝗳𝗳𝘀. Model → Retrieval Retrieval → Context Context → Agent Agent → Tool Tool → Memory Memory → Evaluation That’s where latency compounds, context gets lost, permissions leak, hallucinations propagate and reliability starts falling apart. 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝗺𝗼𝗮𝘁 𝗶𝘀𝗻’𝘁 𝗵𝗮𝘃𝗶𝗻𝗴 𝗺𝗼𝗿𝗲 𝗔𝗜 𝘁𝗼𝗼𝗹𝘀. It’s designing how they work together. A stack map tells you 𝗪𝗛𝗔𝗧 exists. Production engineering decides 𝗛𝗢𝗪 it all survives contact with reality. Which tool in your AI stack has become indispensable? Save this map for your next AI build. Repost it for someone designing an AI architecture. #AI #ArtificialIntelligence #GenAI

AI tools are changing the way we work, create & grow. 🤖✨ From productivity to creativity, Which AI tool do you use the most? 👀 Follow me for more useful AI & tech updates. 🚀 #AITools #ArtificialIntelligence #AI #Tech #Productivity #DigitalSkills

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What if I told you one photo could reveal where else it appears online? 👀 CTA: Upload your photo to FaceGPT and find out → facegpt.ai⁠�

Andrew Ng just dropped a free 2-hour course on complete Graph Engineering. How to go from one prompt to 300 agents that loop, improve, and run without you: • 09:14 -- Build your first AI agent. • 33:11 -- Run agents with loop engineering. • 1:02:46 -- Turn agent loops into graphs. • 1:30:15 -- Build agents that rewrite themselves. • 1:49:05 -- Run the full graph system without you. Most people are still building one agent and calling it finished. Andrew Ng is already teaching everything that comes next: Prompt -> Agents -> Loops -> Graphs -> Self-Improving Systems Single agents are the old workflow. Systems that improve and run without you are the next one. This 2-hour course beats most $700 agent engineering programs. Watch it now and bookmark it for later.