What is Agentic AI and How Does it Work?

Summary

This video delivers a no-nonsense explanation of agentic AI versus simpler AI chatbots. Using real company examples, it contrasts reactive RAG-based Q&A systems and tool-augmented assistants with fully agentic systems that set goals, plan multi-step actions, and autonomously execute tasks via APIs. Key agentic traits highlighted are goal-oriented planning, multi-step reasoning, autonomous decision-making, tool access, knowledge/memory, and integration with services like HR, calendars, and ticketing. Practical examples include an HR onboarding agent, travel and coding assistants, and frameworks/tools (RAG, Zapier, n8n, agno, Gemini). The video closes with resources and code links for hands-on projects.

Takeaways

• 😀 Agentic AI is an AI system that can make decisions and take actions autonomously to achieve a goal without being told exactly what to do at every step.
• 😀 A simple HR assistant using a chat system that answers questions from PDFs is not considered agentic AI, but a workflow-based system.
• 😀 To evolve a system into agentic AI, it needs to include features like goal-oriented planning, multi-step reasoning, autonomous decision-making, and access to tools and APIs.
• 😀 A tool-augmented system, like the HR assistant with leave applications, can integrate with various systems (HR, Outlook, etc.) but still requires human input for decision-making.
• 😀 Agentic AI goes beyond simple Q&A systems by integrating multi-step planning, reasoning, and decision-making processes that involve taking action (e.g., scheduling meetings or ordering laptops).
• 😀 Key features of agentic AI include: goal-oriented planning, multi-step reasoning, autonomous decision-making, tool access, and memory.
• 😀 An example of agentic AI in action is AI-driven coding, such as generating a React Native app by analyzing features, writing code, debugging, and executing the code autonomously.
• 😀 Travel assistants can be considered agentic AI when they plan and book trips autonomously, considering factors like weather, budget, and user preferences.
• 😀 The agentic AI system uses reasoning tools and APIs (e.g., weather API, flight booking) to execute its plans step by step to accomplish complex tasks.
• 😀 Generative AI (Gen AI) is a part of agentic AI, handling tasks like text generation or summarization, but agentic AI encompasses broader tasks involving multi-step decision-making and planning.
• 😀 Examples of agentic AI systems include equity research assistants that autonomously gather data, analyze it, and compile reports, as well as low-code/no-code tools like Zapier and N8N for creating complex workflows.

Q & A

What is agentic AI?

Agentic AI is an autonomous AI system that can make decisions and take actions independently to achieve a goal, without being explicitly told how to proceed at each step. It involves multi-step reasoning, goal-oriented planning, and autonomous decision-making.

What’s the difference between a reactive system and an agentic AI?

A reactive system, such as a simple chatbot, reacts to questions or commands without performing any complex reasoning or taking actions. In contrast, agentic AI involves autonomous decision-making, reasoning, and the ability to perform multi-step tasks, making decisions based on a broader goal.

Can you give an example of a tool-augmented system?

A tool-augmented system is one that has access to external tools but still lacks reasoning and planning abilities. For example, an HR assistant chatbot that can answer questions about leave policies by pulling data from a PDF file but doesn’t perform multi-step actions like applying for leave autonomously.

What are some characteristics of agentic AI systems?

Key characteristics of agentic AI systems include goal-oriented planning, multi-step reasoning, autonomous decision-making, access to external tools, and memory. These systems can take actions like sending emails, making decisions, and completing tasks without explicit instructions at each step.

How does agentic AI handle multi-step tasks?

Agentic AI handles multi-step tasks by reasoning through the necessary steps to achieve a goal and then executing those steps autonomously. For example, onboarding a new intern involves steps like scheduling meetings, creating profiles, and ordering equipment, all of which the system handles based on its planning and integrations with other tools.

How does agentic AI differ from generative AI (GenAI)?

Generative AI (GenAI) is a subset of agentic AI that focuses on generating content, such as text, images, or videos. Agentic AI, however, encompasses a broader set of capabilities, including complex decision-making, reasoning, and action-taking to achieve specific goals autonomously, using tools and integrations.

Can agentic AI systems make decisions on their own?

Yes, agentic AI systems are designed to make decisions on their own based on the available data, reasoning, and planning. These systems don’t require constant input or instructions for every step; they can autonomously perform actions that align with their goals.

What role does memory play in agentic AI?

Memory in agentic AI allows the system to retain context and recall past interactions or actions. This is essential for ensuring that the AI can handle ongoing tasks, remember user preferences, and adapt to new situations without needing to be reminded of prior steps.

What are some real-world examples of agentic AI systems?

Real-world examples of agentic AI include HR assistants that autonomously handle leave requests, AI coding systems like Replit that write, test, and debug code, and travel assistants that plan and book trips by making decisions based on multiple constraints like budget and weather.

How can tools like Zapier and N8N be used to build agentic AI?

Tools like Zapier and N8N help integrate different applications and services, allowing you to automate workflows and trigger actions based on specific inputs. These tools can be used to build agentic AI by connecting APIs and automating multi-step processes, such as booking travel or managing projects.