Unleashing Agentic AI

ai agenticai
Robot editing a document on a laptop

As you have probably heard, AI is a hot buzzword these days. Everyone is trying to get on the genAI bandwagon, but have you looked at agentic AI yet?

What is agentic AI?

Agentic AI refers to systems that can operate on their own, making decisions and taking actions without constant human supervision. These systems are designed to achieve specific goals, which means they can analyze situations, consider different options, and choose actions that align with their objectives. They often gather information from their surroundings or data inputs, adapt to changing circumstances, and respond intelligently to new challenges. For example, an agentic AI in a self-driving car might decide how to navigate traffic or avoid obstacles, while a personal assistant AI could organize your schedule and adjust it based on new priorities. The key idea is that these systems are not just tools that wait for instructions—they act more like independent problem-solvers, capable of working toward outcomes in dynamic and unpredictable environments. This autonomy makes them powerful but also requires careful design to ensure their actions are aligned with human intentions and values.

Generative vs Agentic

Generative AI and agentic AI are both powerful types of artificial intelligence, but they serve different purposes and function in distinct ways. Generative AI is focused on creating content—such as text, images, music, or even code—based on patterns it has learned from data. For instance, tools like ChatGPT can write articles or answer questions, while image generators create visuals from descriptions. These systems excel at producing creative outputs but don’t typically take actions or make decisions on their own. Agentic AI, on the other hand, is designed to act independently, making decisions and taking actions to achieve specific goals. For example, a self-driving car doesn’t just process data; it actively decides when to stop, turn, or accelerate to reach its destination safely. The main difference is that generative AI creates, while agentic AI acts. Generative AI is more like a creative assistant, while agentic AI is an autonomous decision-maker focused on achieving outcomes in real-world scenarios.

Learning Agentic AI

Exploring and experimenting with agentic AI is more accessible than ever, thanks to a wide range of tools, platforms, and resources designed for users of all skill levels. Online platforms often provide user-friendly interfaces, complete with tutorials, documentation, and pre-built templates, allowing you to interact with or even build simple AI agents. These tools make it easy to experiment with various types of agentic AI, such as chatbots that can engage in complex conversations or AI assistants that help manage tasks and schedules. For a more hands-on approach, robotics kits like LEGO Mindstorms or Raspberry Pi offer a fun way to build and program autonomous machines, while platforms like OpenAI Gym or Unity ML-Agents allow you to create virtual agents that learn to solve tasks through trial and error. I own a Raspberry Pi, but I had not considered using it for agentic AI tinkering. If you prefer less technical experimentation, you can explore smart home assistants like Alexa or Google Assistant, or automation apps like IFTTT, to see agentic AI in action. For those looking to deepen their knowledge, free online courses on platforms like Coursera and edX cover everything from the basics of AI to advanced agentic systems, providing valuable insights into how these technologies work and their practical applications. Whether you’re building, using, or learning, these resources make it easy to understand and engage with agentic AI, even without a programming background. I might look start one of these courses after I finish up my current upskilling track.

Agentic AI represents a pivotal step in the evolution of technology, enabling machines to act independently and unlocking transformative potential across industries. From autonomous vehicles to smarter assistants, it is already solving real-world problems and reshaping how we live and work. As this field rapidly grows, exploring its tools and applications offers exciting opportunities to enhance your projects, business, or daily life. With responsible development at the forefront, the journey into agentic AI is just beginning - and it’s one well worth taking. A while back I started developing a digital twin for myself. I am going to work expanding its capabilities using agentic AI.

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