Kevin Dean’s Post

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CEO | Gen AI | Channel | Business Strategist | Process Automation | Speaker

🧠 The future of AI is here, and it's more autonomous than ever! Meet Agentic AI – a revolutionary advancement in AI systems capable of acting with minimal human intervention. These intelligent agents don't just react—they proactively make decisions, execute tasks, and adapt to dynamic environments, driving efficiency and innovation across industries. 🚀 In our latest blog post, we explore what Agentic AI really means and how it’s built on language models (LLMs) that can use tools, remember past interactions, and autonomously execute complex workflows. From automating routine tasks to handling sophisticated processes, Agentic AI is set to redefine how we think about automation and intelligence. We break down everything you need to know, including: How Agentic AI works: Understanding the core components like tools, memory, and function calling that enable these agents to perform tasks independently. 🎇 Planning your initiative: Identifying key use cases where Agentic AI can deliver value to your organization. 🎇 Designing your systems: Creating modular, goal-oriented agents equipped with the right tools and capabilities. 🎇 Implementing with confidence: Testing, prototyping, and selecting the right models to power your Agentic AI workflows. 🎇 Scaling effectively: Leveraging cloud infrastructure and continuous optimization to grow your AI initiatives seamlessly. 🔥 Ready to unlock the full potential of Agentic AI for your business? Start here with our comprehensive guide 👉 The Rise of Agentic AI https://lnkd.in/gXa-A6pP The future of AI isn’t just about faster data processing—it’s about systems that can act, adapt, and execute with autonomy. What possibilities do you see for Agentic AI in your industry? Let’s start a conversation in the comments! 👇 #ArtificialIntelligence #Automation #BusinessStrategy #AgenticAI #AIInnovation #Leadership #GrowthStrategy #DigitalTransformation

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Godwin Josh

Co-Founder of Altrosyn and DIrector at CDTECH | Inventor | Manufacturer

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Agentic AI's reliance on LLMs with tool integration and memory presents a fascinating evolution beyond traditional rule-based systems. The concept of modular, goal-oriented agents aligns well with the principles of "intelligent automation" and "autonomous workflows." However, how will we ensure these agents navigate complex ethical dilemmas inherent in real-world decision-making processes, especially when dealing with unforeseen edge cases? Can we effectively implement robust "explainability" mechanisms within these LLMs to provide transparent justifications for their actions, particularly when dealing with high-stakes scenarios involving "value alignment" and potential biases?

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