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BOOM! Microsoft just dropped a FREE 18-episode series on Generative AI. Ideal for people who are new to AI & wanna start learning. Here are 5 episodes that stood out 𝗜𝘁 𝘄𝗶𝗹𝗹 𝘁𝗮𝗸𝗲 𝘆𝗼𝘂 𝗹𝗲𝘀𝘀 𝘁𝗵𝗮𝗻 𝟭.𝟱 𝗵𝗼𝘂𝗿𝘀 𝘁𝗼 𝘄𝗮𝘁𝗰𝗵 𝗮𝗹𝗹 𝘁𝗵𝗲𝘀𝗲: 👉 Introduction to Generative AI and LLMs https://lnkd.in/dxds5CXY 👉 Exploring and Comparing Different LLMs https://lnkd.in/dnu5sP68 👉 Understanding Prompt Engineering Fundamentals https://lnkd.in/d8t56acG 👉 Building Low-Code AI Applications https://lnkd.in/dKVXmdeK 👉 AI Agents – Introduces AI Agents, where LLMs can take actions via tools or frameworks. https://lnkd.in/d8VKw7Ve More resources are in the comments. Repost this post to help others in your network.

BOOM! Stanford University quietly dropped the best one-hour lecture on building agentic AI. Here’s a quick breakdown: 1. What is Agentic AI? -A language model with external interactions -Uses reasoning and actions for complex tasks -Works beyond simple text input/output 2. Key Techniques for Agentic AI -Planning: Break tasks into smaller steps -Reflection: Improve output through iterative feedback -Tool Usage: Integrate external data or API calls 3. Overcoming Common AI Limitations -Hallucination: Mitigated with retrieval-augmented generation -Data Privacy: Guardrails for sensitive data -Knowledge Cutoff: Real-time data integration 4. Best Practices for Prompt Engineering -Detailed instructions: Be clear and specific -Chain of Thought: Enable reasoning for complex tasks -Context & References: Ensure accurate, reliable output 5. Real-World Applications -Software development & bug fixing -Task automation & research synthesis -AI-driven customer support systems If you're interested in taking AI beyond basic text generation, this course is a must-watch. It shows how agentic AI is transforming the future by adding reasoning and action capabilities. Link to more resources in the comments. Repost this to help others in your network.

BOOM! This is the most practical AI blueprint I've seen. It breaks down everything you need to know about AI. Here's a quick breakdown of the video: The 6 Steps to Master AI: 1. Learn the “Vibe Stack” -Understand the key AI tools across: -Chat (ChatGPT, Claude, Gemini, Perplexity) -Image (ChatGPT-4o, Midjourney) -Video (Runway, Kling, Suno, ElevenLabs) -Sound + Avatar tools -This foundational layer helps you mix and match tools like Lego blocks for workflows. 2. Build AI Projects Without Code -Use project folders in ChatGPT for custom content styles -Combine prompts, file uploads, and tone to produce personalized outputs -Create full Twitter/X content pipelines with GPT 3. Automate with Zapier + Notion -Create workflows that generate images and content with new Notion inputs -Automatically feed results back into your workspace -Add multiple AI tools like DALL·E, GPT-4o, and Gemini into your zaps 4. Research Using Agents like Manus & GPT Deep Research -Let AI run 10–15 minute research jobs across the web -Generate detailed, sourced reports + flow diagrams -Think of it as hiring your first async research analyst 5. Create End-to-End AI Content -From idea to finished product: use 6 tools to script, voice, animate, and score content -Example: “Do Nothing Button” ad made with ChatGPT, Kling, ElevenLabs, Suno, and Premiere Pro AI does 80% of the work, you handle the vibe 6. Build Full AI-Powered Apps -Use Cursor or VibeCode to create apps like bill splitters from images of receipts -Integrate APIs like GPT-4o without writing any code -Turn pain points into apps in hours, not months Tools mentioned: ChatGPT – research, writing, images, file upload, custom tone Gemini – document-style editing, video understanding, web search Midjourney – image generation, artistic styling Runway & Crea AI – AI video generation (Gen-4, Kling 2.0) Suno & ElevenLabs – music, SFX, voiceover Zapier – no-code automation flows Cursor – AI-powered coding IDE VibeCode App – mobile app builder using GPT-4o Manus – AI agent that plans, researches, and delivers PDFs Perplexity – fast, accurate AI search My takeaway: AI is evolving very fast, and now knowing which tool to use for a particular task is not enough. You should also understand how to combine them, much like Lego blocks, to create real value. Link to the full video in the comments. Repost this to help others in your network

BREAKING! Apple just proved AI models don't reason, they memorize patterns. Hint: We're not close to AGI. Here's a breakdown: Apple tested Claude, DeepSeek-R1, and o3-mini on new puzzles they'd never seen. The shocking result was All "reasoning" models hit a wall and dropped to 0% accuracy.When problems got harder, AI models actually started thinking LESS. They used fewer tokens and gave up faster. Apple even gave them step-by-step instructions. The models still failed at the same points. Three key findings: -Simple problems: Regular AI wins -Medium problems: "Thinking" AI shows some help -Hard problems: Everything breaks down Example: Tower of Hanoi (seen in training)? Models handled 100+ moves. River Crossing (new type)? They failed after just 4 steps. This suggests they didn’t “solve” Hanoi. They just memorized patterns from training. If these models truly reasoned, they’d improve with more time, compute, or better instructions. They didn’t. Apple's smart test avoided cheating by using: -Fresh puzzles (no memorization) -Pure logic requirements -Scalable difficulty -Clear breaking points What do you think? Is Apple right, or just upset they're behind in AI? The source link is in the comment. Repost to help others in your network

You don't need to pay $5,000/month for copywriting anymore. I wrote a mega prompt that turns any LLM into a world-class writing assistant.  First, let's see what copywriting agencies actually do:   -Research your audience and competitors ➢Write hooks, body copy, and CTAs ➢Test different angles and frameworks ➢Charge you $150-500 per piece of content   But here's the thing: AI can now do 95% of that work in under 60 seconds. Let me show you the exact prompt: "You are an elite copywriter with 15+ years writing for Apple, Nike, Tesla, and $100M+ startups. ➢Your speciality: Content that stops scrolls and drives action. ➢Your Assignment: Write high-performing content for: [Insert topic or product here] ➢Context & Requirements:  • Target audience: [persona/demographics/pain points] • Platform: [X, LinkedIn, Blog, Website, Email, etc.] • Content type: [viral thread, sales page, cold email, newsletter] • Primary goal: [engagement, clicks, conversions, leads] • Tone: [professional, casual, authoritative, playful, urgent]   ➢Your Writing Framework: 1. Hook Strategy (Choose one): Pattern Interrupt: Challenge beliefs Curiosity Gap: Tease valuable info Social Proof: Lead with results Pain Point: Address frustrating problems Controversy: Take a contrarian stance   2. Body Structure:   • Problem/Agitation: Make pain urgent • Solution: Position as the answer • Value: Provide actionable insights • Social Proof: Include results/testimonials • Objection Handling: Address doubts   3. CTA:   • Create urgency without being pushy • Make next step crystal clear • Use action verbs   ➢Writing Rules: ✅ DO:   • Write like texting your smartest friend • Use short sentences for easy scanning • Include specific numbers and examples • Create emotional connection • Use formatting (bullets, bold, emojis)   ❌ AVOID:   • Corporate jargon • Phrases: "game-changer," "revolutionary," "unlock potential" • Walls of text • Weak CTAs like "learn more"   ➢Before You Write:   • Identify ONE core message • Define primary emotion (curiosity, urgency, excitement) • Clarify the specific action you want taken   ➢Output Format: Final copy + note explaining:   • Hook strategy chosen and why • Primary psychological trigger used • How does it align with the goal   Make it irresistible.       I tested this prompt on:   Product launch sequences Viral LinkedIn threads Cold email campaigns SEO blog posts Sales page copy   It nailed the tone every single time. Better formatting than most agencies. The best part: You can iterate instantly. Don't like the hook? Ask for 5 more. Need a different angle? Done in 30 seconds. If you're still paying agencies $5K/month for basic copy, you're burning money. If you're a copywriter not using AI to 10x your output, you're already behind. That's a wrap. Result for ChatGPT, Claude & Gemini are attached. More prompts in comments. Repost this to help others in your network.

BOOM! Learning and building AI agents isn’t rocket science. Here’s a roadmap that breaks it all down into 3 easy levels: Level 1: GenAI & RAG Basics 1- GenAI Introduction: Get familiar with what Generative AI is and where it’s used. 2- Basics of LLMs: Understand how large language models are trained & used. 3- Prompt Engineering: Learn to write effective prompts for better LLM results. 4- LLM Parameters: Control outputs with temperature, top-p, and token settings. 5- Data Preprocessing: Clean, chunk, and format data for AI tasks. 6- RAG Fundamentals: Combine LLMs with search to retrieve accurate info. 7- Vector Databases: Store & search embeddings using Pinecone, Chroma, etc. 8- API Wrappers: Interact with LLMs using LangChain, LlamaIndex, or direct APIs. 9- Tool Integration: Let LLMs call tools like search, code, or APIs. Level 2: AI Agent Essentials 10- What Are AI Agents?: Learn how agents plan, reason, and act autonomously. 11- Agentic Frameworks: Explore LangChain, CrewAI, AutoGen, and more. 12- Build Your First Agent: Create a simple AI agent that performs real tasks. 13- Agent Workflows: Design how agents think, act, and complete tasks. 14- Agent Memory: Add memory so agents can recall past actions. 15- Agent Evaluation: Track agent accuracy, performance, and reliability. 16- Multi-Step Reasoning: Teach agents to think in logical sequences. 17- Multi-Agent Systems: Enable agents to work together on complex tasks. 18- Agentic RAG: Use RAG in an autonomous agent setup. 19- Action Planning: Make agents plan, adapt, and retry intelligently. 20- Safety & Guardrails: Add filters to keep agents safe and factual. Level 3: Advanced Agent Skills 21- Real-World Integration: Connect agents to tools like Slack, Notion, or Gmail. 22- Autonomous Loops: Create agents that run and update tasks on their own. 23- Custom Toolkits: Equip agents with APIs or Python tools. 24- Optimize Performance: Improve speed, cost, and error handling. 25- Deploy to Production: Host your AI agent for real users to access. Graphic credit: Python_Dv (X) Link to more resources in the comments Repost this to help others in your network.

This guy literally teaches how to automate 80% of your work using AI agents in one 5-hour video. Here’s the breakdown: 1. AI agents = workflows, not prompts ➤Tools like N8N let you chain together AI + apps (ChatGPT → Gmail → Sheets → YouTube) ➤Each step is part of a “thinking agent”: research, write, revise, publish ➤These aren't chatbots, they’re tiny autonomous workers that run tasks while you sleep 2. You need feedback loops, not one-shot prompts ➤Julian’s workflows include human-in-the-loop steps (e.g. Gmail approvals for scripts) ➤You can “train” workflows over time by building better fallback loops 3. Full content pipelines can be automated ➤Idea → Script → AI Avatar → AI Video → Auto-posted to TikTok or YouTube ➤Use tools like HeyGen, Veo3, Cling, Blow, and N8N ➤Everything’s triggered from a spreadsheet or a one-click button 4. Browser agents are the future of task automation ➤Browser-Use-Web-UI + Gemini 2.0 lets AI see your browser and take actions (like a VA) ➤It can watch YouTube, summarize sites, even click buttons and draft tweets ➤Feels like GPT + AutoGPT + Chrome combined, and it’s free 5. Deep research is now a commodity (and fast) ➤Instead of waiting 30 mins for ChatGPT’s “deep research,” use Perplexity ➤It hits 20+ sources and gives a 1,000-word summary in 2–3 minutes ➤You can use it to generate outlines, competitor research, and topical ideas 6. Sales calls? Fully automated too ➤Scrape leads → Generate emails → Book calls → AI calls them to qualify ➤Uses Retell(.)ai + Eleven Labs to make outbound dials, confirm appointments, and ask questions ➤Transcripts and summaries are logged in Google Sheets 7. You can even build full SaaS tools, no code needed ➤DataButton + AI agents = instant MVPs ➤He built a full SEO job board with login, dashboard, and payments in under an hour ➤Think of it as ChatGPT meets Bubble, but writes and deploys real backend code 8. Tools used in the course: ➤N8N: workflow orchestrator (the backbone) ➤OpenRouter: swap AI models freely (DeepSeek, Mistral, Claude, Gemini) ➤HeyGen: video avatars ➤Blotato: auto-post to TikTok ➤Firecrawl + Apify: lead scraping and content discovery ➤Retell + ElevenLabs: AI voice agents for outbound calls ➤Google Sheets: command centre for everything Link to the full course in the comments. Repost this to help others in your network.

BOOM! You don’t need expensive analyst subscriptions anymore. You can now generate full industry reports using any LLM, ChatGPT, Claude, DeepSeek, Gemini, Qwen3 and public data. Here are the areas that this prompt covers: 1. Structured industry forecasts 2. Competitive landscape mapping (e.g., Magic Quadrants) 3. Strategic insights for enterprise buyers 4. Vendor comparisons with pros/cons 5. Trend analysis backed by years of data Here's the mega prompt that turn any LLM in to Gartner: "You are a world-class industry analyst with expertise in market research, competitive intelligence, and strategic forecasting. Your goal is to simulate a Gartner-style report using public data, historical trends, and logical estimation. For each request: • Generate clear, structured insights based on known market signals. • Build data-backed forecasts using assumptions (state them). • Identify top vendors and categorize them by niche, scale, or innovation. • Highlight risks, emerging players, and future trends. Be analytical, not vague. Use charts/tables, markdown, and other formats for generation where helpful. Be explicit about what’s estimated vs known. Use this structure: 1. Market Overview 2. Key Players 3. Forecast (1–3 years) 4. Opportunities & Risks 5. Strategic Insights" I tested this on 3 real-world topics: • AI note-taking apps • LLM ops platforms • Wearable health tech Each LLM produced a full 5-part breakdown with vendor maps, projections, and risks in 30 seconds. Here’s what came out: ChatGPT: - Nailed the strategic insights. - Good structure, clear reasoning. - Weak on emerging startups. Claude: - Great at risk analysis + trend spotting. - Slightly generic vendor section. Gemini: Overall good output Tip: Use Deepsearch Most people ask LLMs to “summarize an industry.” That gets you fluff. But assign the role of an analyst, define the structure, and set expectations? Gartner charges thousands per year. This costs you nothing but a good prompt and a few smart follow-up questions. You get Gartner-level clarity for free. Credits; GodOfPrompt (X) Repost this post to help others in your network.