Artificial Intelligence (AI) is everywhere today  – from helping people write emails, images creation, customer interactions, or managing businesses. But the real questions is why? 

Let’s break it down into three key ideas:

  •  LLMs (Large Language Models)
  • AI Workflows 
  • AI Agents 

1. Large Language Models (LLMs): The Brain of AI

LLMs are computer programs that understand and write human language.You can ask them questions or give instructions, and they reply in a way that sounds like a real person.

What’s the process? 

  • To train LLMs, texts from books, articles, and websites are utilized on a large scale. 
  • Their heads are not understanding like humans, but recognizing elements of speech and writing that patterns enable will do wonders for AI’s comprehension. 
  • AI understands these patterns enabling them to intelligently guess what words ought to be next in the sentence and know the best way to respond to your queries. 

What do they do? 

  • Comprehension: From your text, comprehension is reading widely in demand in the modern working world. 
  • Creation: Emails, stories, summaries, and code can be automated, written, generated, and created. 
  • Translation: Many languages or LLMs will swish back and forth between enabling you to code freely without being held back by language barriers.
  • Answer questions: You can ask historical questions, scientific questions, or even have it explain a cooking procedure for you.

For Example:

Let’s comparing how different AI models perform on the same question.

 This site  https://lmarena.ai/ — a platform that lets you compare responses from multiple AI models side-by-side.

I type in:
“Explain LLM”

2. AI Workflows: The Recipe That Gets Things Done  

An AI workflow is a list of instructions organized in a specific way for the AI to follow. It is a systematic approach broken down into mini steps to complete a task and achieve a goal.  

How does it work?  

Let’s say you want to read product reviews and their good or bad rating:  

  • A new review arrives.  
  • The AI scans through it.  
  • The AI accesses whether it’s good or bad.  
  • It is kept in file or database.  

This is a workflow— a specific plan defining AI tasks and the sequential order to execute them.  

Why do we use workflows?  

  • Automation: Tasks are done without human intervention ever since they were set up.  
  • Consistency: Every time the task is completed, the same outcome is reached.  
  • Efforts and Time: Achieving the task takes much less time and the chances of making errors are virtually eliminated.  
  • Link different tools: An LLM can be used with other tools such as Excel, Gmail, or Docs to enhance its functionalities.  

Simple Example of an AI Workflow:

Suppose you want to generate responses using a language model (LLM):

  1. You open a chatbot interface.
  2. You enter a prompt (e.g., “Summarize this paragraph”).
  3. The LLM (such as Gemini or ChatGPT) processes the prompt using an API key.
  4. The AI returns a summary as output.

This is a basic example of an AI workflow, where each step—from user input to AI response—is clearly defined and executed automatically.

3. AI Agents: The Smart Workers

An AI agent is a type of a smart assistant which is goal oriented and knows how to achieve the goal. Instead of following a sequential list, it makes choices, employs tools, and alters its strategies when necessary.

How does it work?  

An AI agent can:

  • Plan – think of how its goal can be achieved step by step.  
  • Act – employ a LLM, a search engine, or other software applications.  
  • Adjust – try employing a different approach when there are hurdles blocking the way.  

This is called the ReAct framework – Reason and Act.  

Example:

Imagine a case where an AI agent is instructed to update an Instagram account with an company picnic post.

Here’s how it might work:  

  • Step 1 (Get info): Use webs to fetch photos and details of the event.  
  • Step 2 (Use LLM): Provide the gathered data to LLM, request a catchy few sentences and relevant hashtags.  
  • Step 3 (Organize): Store the caption and photo in Google docs.  
  • Step 4 (Schedule): Monitor user activities and determine the best time to post.  
  • Step 5 (Post): Sign into the Instagram account and execute the post.
  • Step 6 (Monitor): It tracks the likes and comments and reports back.

In the case of one step failing (for example, no photographs being taken), it can return to capture other pictures and continue from where it left off.

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