"3 Key Takeaways from Generative AI Workshop"

The journey of building and deploying AI Agents for enterprises is rarely a straight line. It comprises learning, course correction and change management. Context is key, and true value comes from decision-based, not rules-based, automation. LLMs have their own "brain," so focus on defining outcomes and empowering users to validate responses. I'd love to hear your stories—what has the human element of AI deployment looked like for you? #AI #AIAgents #LLM #AgenticAI #MachineLearning #TechLearning #SoftwareDevelopment #Innovation #DecisionAutomation #AIStrategy https://lnkd.in/gWheQEdR

🚀 𝗛𝗼𝘄 𝘁𝗼 𝗦𝘁𝗮𝗿𝘁 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 AI Agents are becoming the backbone of next-generation applications, from intelligent assistants to autonomous decision-makers. But with so many concepts to grasp, where should you start? Here’s a 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗽𝗮𝘁𝗵 to help you go from beginner to building powerful AI agents: 🔹 𝗟𝗲𝘃𝗲𝗹 𝟭: 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 – 𝗚𝗲𝗻𝗔𝗜 & 𝗥𝗔𝗚 1 Understand 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗯𝗮𝘀𝗶𝗰𝘀 – what it is, where it’s used, and its limitations. 2 Learn the 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀 𝗼𝗳 𝗟𝗟𝗠𝘀 (how they work, fine-tuning, embeddings). 3 Master 𝗣𝗿𝗼𝗺𝗽𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 to communicate effectively with models. 4 Dive into 𝗗𝗮𝘁𝗮 𝗛𝗮𝗻𝗱𝗹𝗶𝗻𝗴 & 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 – because good AI is built on clean, well-structured data. 5 Explore 𝗔𝗣𝗜 𝗪𝗿𝗮𝗽𝗽𝗲𝗿𝘀 & 𝗥𝗔𝗚 𝗘𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹𝘀 – critical for connecting external knowledge sources. 🔹 𝗟𝗲𝘃𝗲𝗹 𝟮: 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗦𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 1 Get an 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝘁𝗼 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 – their purpose, structure, and real-world applications. 2 Learn 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀 (LangChain, LlamaIndex, Haystack, etc.). 3 Practice by 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗦𝗶𝗺𝗽𝗹𝗲 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 – start small, then iterate. 4 Understand the 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 – planning, reasoning, execution. 5 Explore 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗠𝗲𝗺𝗼𝗿𝘆 & 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻 – giving agents context and feedback loops. 6 Move into 𝗠𝘂𝗹𝘁𝗶-𝗔𝗴𝗲𝗻𝘁 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻 & 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚 – scaling intelligence through cooperation. ✅ By following this path, you’ll not only gain theoretical knowledge but also build the practical skills needed to design scalable, reliable, and context-aware AI agents. 🌍 The AI ecosystem is evolving rapidly, those who master agents will define the next wave of innovation. 👉 What stage are you currently at in your AI Agent learning journey? #GenAI #AgenticAI #AIAgents #LLM

🚀 Day 41 of #50DaysOfAI Prompt Chaining Ever tried asking AI to do everything at once and got a messy result? 😅 That’s where Prompt Chaining comes in! Think of it like building with LEGO blocks 🧱: instead of trying to create a whole castle in one piece, you build it step by step, connecting each block carefully. That’s exactly how prompt chaining works. What it is: Prompt chaining = breaking a complex task into smaller prompts, then feeding the output of one prompt into the next. This helps guide AI to a more accurate, structured, and creative outcome. 🎯 Why it matters: ✨ Reduces confusion for the AI (and for you!) ✨ Improves accuracy and control ✨ Mimics how humans solve problems step by step ✨ Perfect for multi-stage workflows: summarization → analysis → visualization Example: Imagine you want to analyze customer feedback: 1️⃣ Prompt 1: “Summarize these 100 reviews into key themes.” 2️⃣ Prompt 2: “From those themes, identify the top 3 customer pain points.” 3️⃣ Prompt 3: “Suggest product improvements to address these pain points.” Instead of asking “What improvements should we make from 100 reviews?” all at once (chaos guaranteed 😅), you guide the AI step by step. Real-world uses: 💡 Data analysis pipelines 💡 Research & report writing 💡 Code generation (design → pseudocode → implementation → debugging) 💡 Chatbots that remember context over long conversations 🔗 Fun tip: think of prompt chaining as holding the AI’s hand through a maze 🌀it’ll get to the exit smoothly if you guide it carefully. #GenerativeAI #PromptChaining #AI #ArtificialIntelligence #AIEducation #DataScience #MachineLearning #AIforBusiness #TechTips #AIWorkflow #AIProductivity #StepByStepAI #AIExplained #LearningAI #AICommunity #DigitalTransformation #FutureOfWork #AIInsights #TechLearning #AIBeginners

Starting with AI and LLMs can greatly improve your efficiency. Begin by automating repetitive, text-centric tasks like drafting emails and content creation. Utilize beginner-friendly tools, refine your skills, and gradually explore advanced AI applications for impactful automation in your workflow. - 📧 Automate email drafts effortlessly. - 💼 Streamline content creation tasks. - 📊 Enhance data analysis with AI. - 🛠️ Use beginner-friendly AI tools. - 🔄 Iteratively refine prompts and workflows. - 💡 Experiment for real-world applications. - 🌱 Gradually expand AI expertise. Need AI Automation services? Free 30 min chat. https://technoflow.co.uk/

You’re either using AI to scale… or competing against those who are. Two approaches are emerging: Sakana AI’s M2N2 – merges specialized AI models into hybrids. No retraining. No massive datasets. Just efficiency. Think math + reasoning + multi-language vision, combined in one system. LegacyStack.ai – not about building models, but about building businesses. Funnels in minutes. Automated follow-ups. AI CRM that learns and adapts. Both solve different problems. M2N2 = engineering breakthrough for AI creators. LegacyStack = operating system for entrepreneurs. If you’re coding models, M2N2 is impressive. If you’re running a business, LegacyStack is how you stay alive in the next decade. 👉 Pick your path. The world won’t wait. Quick Read: https://lnkd.in/eKjrEE6U

I recently shared this on other forums, and I think it’s worth bringing here too. Right now, AI is splitting into two paths: On one side, we have engineering breakthroughs like Sakana AI’s M2N2, pushing the limits of what AI models can do. On the other side, we have business platforms like LegacyStack.ai, focused not on building models but on helping entrepreneurs and small business owners build businesses that actually scale. Both matter. But here’s my perspective: Most business owners don’t need to code models. They need clarity, systems, and time back. That’s where LegacyStack comes in. 👉 Check out the original post here: https://lnkd.in/e3Mv5v7Q Curious to hear from my network: When you think about AI, are you more excited about engineering breakthroughs… or about the practical tools that help us work smarter right now? #AI #BusinessGrowth #Entrepreneurship #LegacyStackAI

Step into the world of AI and LLMs by starting small and practical. Identify repetitive or text-heavy tasks in your workflow for automation like drafting emails or content creation. Experiment with beginner AI tools, and gradually explore advanced applications. Pro Tip: Apply AI to real-world problems for immediate benefits. - 🧠 Start with practical tasks for AI automation. - 📧 Ideal for drafting emails and creating content. - 🔍 Use beginner-friendly AI tools to guide you. - 🔄 Iteratively refine prompts and workflows. - 🚀 Explore advanced AI: agentic, predictive, automated. - 🏆 Practical applications yield immediate benefits. Visit technoflow.co.uk for more.

Tried out some cool automation tools last week, and wow—a good to try space beyond common AI prompting use cases. Common ones so far: Gumloop, Make, and n8n. Gumloop: Super simple. A buddy you can use natural language with Make: Super visual designer friend, with tons of templates to get you started quick n8n: Crazy flexible for complex stuff, but you’ll want to know your way around nodes Curious—if you had to pick an automation buddy, which one would it be? #AI #Automation

AI isn’t just the future it’s already reshaping how we work today. I experienced this firsthand on Day 1 of the Outskill Generative AI Mastermind an intense, practical dive into the tools and techniques transforming business right now. Here’s a snapshot of what we covered: - Prompt Engineering : Crafting the right inputs for powerful outputs. - SEO Auditing with AI : Smarter, faster ways to uncover gaps. - Intelligent AI Agents : Automating lead enrichment and repetitive tasks. - Video & Image Generation : Creating high-quality assets in minutes. What stood out to me wasn’t just the tools, It was the possibilities: - Automating work we spend hours on today. - Unlocking creativity at scale. - Embedding AI into everyday business processes. And we’re only halfway through. Day 2 is where we go even deeper, and I’ll be sharing specific tools, my key takeaways, and real applications once the program wraps up. If you’ve been curious about how Generative AI can actually work for you not in theory, but in practice. Stay tuned. #GenerativeAI #AITransformation #Outskill #SkillsUnlocked #ProfessionalGrowth