AI

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Agentic AI vs AI Agents: A Practical Walkthrough with Amazon Bedrock

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Introduction

AI is evolving—from static, rule-based agents to autonomous systems that can reason, plan, and act. If you’ve heard terms like AI agents and Agentic AI and wondered what’s the difference, this blog is for you.

We’ll compare the two paradigms, and more importantly—show you live code using Amazon Bedrock and LangChain.

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What’s the Difference?

AI Agents

These are task-specific, rule-driven programs that respond to user inputs based on predefined logic. They do not plan, learn, or adapt. Think of them like an interactive FAQ bot or a form-filling assistant.

Agentic AI

Agentic AI systems go further. They understand goals, break down complex instructions into subtasks, and may even call external tools/APIs to gather info, compute, or act. It mimics how a human assistant would approach a problem.

AI Agent – Basic Streamlit Example

Let’s start with a simple AI Agent: a Travel Assistant that replies based on fixed logic.

Code

 

Agentic AI – Powered by LangChain + Amazon Bedrock

Let’s build an Agentic AI version of the same travel assistant. It will interpret goals, reason about steps, and respond dynamically using Bedrock’s foundation models like Claude or Titan.

Prerequisites

Make sure you have:

  • An AWS account with Bedrock enabled
  • AWS credentials configured
  • Python libraries installed:
  • pip install langchain boto3 botocore

 

Step 1 – Set Up Bedrock LLM

Step 2 – Load Agent Tools

Step 3 – Give it a Goal

Tip: Use Skyscanner and Google Flights to monitor deals.

The model breaks down the goal, reasons through tasks, and presents a complete plan. This is Agentic AI in action.

 

Key Differences

AI Agents:

  • Predefined logic
  • Fixed answers
  • No planning or dynamic behavior

Agentic AI:

  • Understands natural language goals
  • Can plan multi-step tasks
  • Uses tools or APIs to complete objectives

Conclusion

Agentic AI is more than a chatbot. It’s a framework where LLMs become proactive assistants, capable of understanding, reasoning, and executing.

With Amazon Bedrock + LangChain, you now have the power to build these intelligent systems securely and at scale.

 

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About CloudThat

CloudThat is a leading provider of Cloud Training and Consulting services with a global presence in India, the USA, Asia, Europe, and Africa. Specializing in AWS, Microsoft Azure, GCP, VMware, Databricks, and more, the company serves mid-market and enterprise clients, offering comprehensive expertise in Cloud Migration, Data Platforms, DevOps, IoT, AI/ML, and more.

CloudThat is the first Indian Company to win the prestigious Microsoft Partner 2024 Award and is recognized as a top-tier partner with AWS and Microsoft, including the prestigious ‘Think Big’ partner award from AWS and the Microsoft Superstars FY 2023 award in Asia & India. Having trained 650k+ professionals in 500+ cloud certifications and completed 300+ consulting projects globally, CloudThat is an official AWS Advanced Consulting Partner, Microsoft Gold Partner, AWS Training PartnerAWS Migration PartnerAWS Data and Analytics PartnerAWS DevOps Competency PartnerAWS GenAI Competency PartnerAmazon QuickSight Service Delivery PartnerAmazon EKS Service Delivery Partner AWS Microsoft Workload PartnersAmazon EC2 Service Delivery PartnerAmazon ECS Service Delivery PartnerAWS Glue Service Delivery PartnerAmazon Redshift Service Delivery PartnerAWS Control Tower Service Delivery PartnerAWS WAF Service Delivery PartnerAmazon CloudFrontAmazon OpenSearchAWS DMSAWS Systems ManagerAmazon RDS, and many more.

WRITTEN BY Priya Kanere

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