Question 1

How is an 'AI Agent' different from a regular chatbot like ChatGPT?

Accepted Answer

A chatbot responds to your prompts. An AI agent acts on your goals. You tell a chatbot, 'What are the steps to book a flight?' You tell an agent, 'Book me the cheapest flight to Tokyo for next Tuesday.' The agent then performs the steps autonomously, interacting with websites and services on your behalf.

Question 2

Is the Agentic Web just a theoretical concept?

Accepted Answer

No, it's already emerging. Services like ChatGPT Agent, Google's Project Mariner, and Genspark's Super Agent are early examples of agentic systems that can perform multi-step tasks. The underlying protocols and architectures are being built now to support a more widespread agentic ecosystem.

Question 3

Will agents replace jobs like web developers or travel agents?

Accepted Answer

The roles will evolve. Just as the web didn't eliminate all information-based jobs, the Agentic Web won't eliminate developers or service professionals. It will automate tedious tasks, allowing humans to focus on higher-level strategy, creativity, complex problem-solving, and managing the agents themselves.

Question 4

What is the 'Agent Attention Economy'?

Accepted Answer

In the current web, companies compete for human attention (clicks, views). In the Agentic Web, a new economy emerges where services and tools compete for agent attention. An agent choosing to use Service A's API over Service B's becomes the new form of a 'click,' driving value and creating a new marketplace.

Question 5

Is this secure? What are the risks?

Accepted Answer

This is one of the most critical challenges. Security and alignment are key. An agent with access to your digital life could be misused if not properly constrained. Module 5 of this course is dedicated to these challenges, discussing the need for robust permissions, monitoring, and ensuring agents act ethically and in your best interest.

Question 6

Do I need to be a programmer to understand the Agentic Web?

Accepted Answer

Not at all. This course is designed for a broad audience. The concepts are explained in a way that is accessible to everyone, regardless of technical background. It's more about understanding this fundamental shift, similar to how one might learn about the social media revolution without needing to code.

Question 7

What are MCP and A2A, and why do they matter?

Accepted Answer

MCP (Model Context Protocol) and A2A (Agent-to-Agent Protocol) are two open standards that define how agents interact with the world. MCP, created by Anthropic, is a universal connector that lets any agent use any tool through a single standard interface. A2A, created by Google, lets agents from different vendors discover and communicate with each other. Together, they are doing for agents what HTTP did for the web.

Question 8

How can I build my first AI agent?

Accepted Answer

The fastest way to start is with a framework like Google's Agent Development Kit (ADK), LangGraph, or CrewAI. These frameworks handle the complex plumbing, so you can focus on defining your agent's goal, tools, and behavior. Many have getting-started tutorials that let you build a simple research or coding agent in under an hour. You will need basic Python knowledge.

Question 9

What happens to my data when I use an AI agent?

Accepted Answer

This depends on the provider and how the agent is built. Cloud-based agents from OpenAI or Google process data on their servers, subject to their privacy policies. Open-source frameworks let you run agents locally for maximum privacy. The best practice is to give agents the minimum permissions necessary for the task, use sandboxed environments, and never give a single agent access to everything in your digital life.

Question 10

Can agents communicate with each other across companies?

Accepted Answer

Yes, and this is exactly what the A2A protocol enables. Before A2A, an agent built with one vendor's tools could not easily work with an agent from another vendor. A2A creates a common language, Agent Cards, that lets agents discover each other's capabilities and collaborate, regardless of who built them. This interoperability is what will enable the true potential of multi-agent workflows across organizations.

The Agentic Web

Course Curriculum

1. The Core Idea: From Information Web to Action Web

2. The Core Components of Agentic Systems

3. The Three Dimensions of the Agentic Web

4. Applications: The Agentic Web in Action

5. The Future: Challenges and Opportunities

6. Protocols Deep Dive: MCP & A2A

7. Build Your First Agent

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Protocols and Standards

Agent Frameworks

Agent Products

Further Reading

Frequently Asked Questions