What Is Agentic AI? - Simply Put AI Series

Description

Agentic AI is an autonomous system that actually executes multi-step workflows on your behalf instead of simply providing instructions or assets like generative AI. By combining advanced reasoning with tool calling, AI agents can independently plan, troubleshoot, and complete complex tasks with minimal human supervision. Video Chapters: 0:00 – The Baking Example: Generative AI vs. Agentic AI 0:51 – What is an AI Agent? (Autonomous Execution) 1:23 – Skill 1: Perception and Structured Planning 2:06 – Skill 2: Tool Calling (Bridging the Digital and Physical) 2:55 – Skill 3: Reasoning, APIs, and Self-Correction 3:52 – Parallel Workflows: Sharing the Workload 4:09 – Summary: Moving from Manuals to Digital Teammates Full Transcript: "Imagine you're hosting a party and you need to bake a complex, three-tier strawberry cake for 20 people. The clock is ticking, and the kitchen is waiting. You open a standard AI chatbot to ask for help. You type in, 'Give me a step-by-step plan to bake a three-tier strawberry cake.' The AI instantly replies with a perfect recipe. But look at this wall of text. It is a massive block of instructions, and reading through it only adds to your stress. The AI gave you the correct information, but it hasn't actually baked anything. You must measure the flour, preheat the oven, and mix the batter yourself. Standard generative AI operates like a fast encyclopedia. It hands you the instruction manual, but it leaves you to do the physical work alone. But what if the AI could actually help you crack the eggs? That is the difference with Agentic AI. An AI agent is an autonomous system built to take a high-level goal, gather the necessary resources, and execute the steps on its own with very little human supervision. Instead of just predicting the next word in a sentence to give you a text response, an agent acts. It moves from answering your questions to completing your tasks. This shifts the technology from a static guidebook you have to follow, into a digital teammate that shares the actual workload. To understand how an agent works, let's look at its first major skill: perception and planning. An agent starts by looking at your goal and assessing the environment it works in. The AI takes your central goal, baking a cake, and splits it into smaller sub-tasks. The nodes then rearrange because the agent recognizes dependencies. It knows the oven must be preheated first and eggs cracked before they're mixed. Think of it like a master chef preparing to make a meal. The agent gathers its ingredients and lays out the precise order of operations. This structured planning phase ensures the AI doesn't act blindly. It orchestrates a logical path to success before executing a single step. Once the plan is set, the agent has to do the work. To do that, it uses a capability called tool calling. Because an AI lives in code, it needs external instruments to affect the real world. For every step in its plan, the agent searches its available toolbox and selects the exact right instrument for the job at hand. The agent interfaces directly with the stand mixer. It sends a signal, and the appliance spins to life, mixing the batter entirely on its own. In an office, these tools aren't kitchen appliances. Corporate AI agents use web browsers, calculators to run complex math, or databases to pull customer records. Tool calling is the bridge between the digital and the physical. It allows the AI to break out of the chat window and create a tangible impact on your actual environment. [...] When the plan hits a roadblock, the agent detects the error, analyzes the problem, and autonomously calculates a new path to an alternate solution. To solve the strawberry shortage, the agent independently connects to a grocery delivery API. An API is an application programming interface—essentially a way for different software systems to talk to each other. The agent orders the berries, and the plan stays on track. Because the agent has memory and the ability to reason, it can self-correct. It adapts to unpredictable variables instead of just following a rigid script. This creates a system of parallel workflows. While the agent handles the routine mixing and baking in the background, you can focus on the creative piping and detail in the foreground. The complex cake is finished perfectly on time, and you didn't have to micromanage a single foundational step to get there. Generative AI tells you what you need to do. Agentic AI actually helps you do it. By combining planning, memory, and tool calling, agents handle the execution. They free you from the burden of repetitive tasks, allowing you to step back and focus on the goals you want to achieve. ------------------ About AI Wisdom with Ivo Jackson: We provide deep-dive insights into artificial intelligence, focusing on the the needs of non-technical beginners learning AI. Website: https://youtube.com/@ai-wisdom-ivo Contact: https://www.linkedin.com/in/ivojackson/