Until a year or two ago, when it came to IT jobs, the roles most often mentioned were front-end developer, back- end developer, full stack, QA engineer, and data analyst . But now there is a big change happening in the job market . Hey guys, welcome to a little clarity and a little reality with you, Sravani. So in recent times, the roles we saw a lot two years back are now fading out. New roles are being heard. If you carefully observe LinkedIn, Naukri, Indeed, and open similar portals and look for openings, hirings for roles like Generative AI Engineer, AI Agentic Developer, and Agentic AI Architect have increased rapidly. Actually, let's do a small reality check in this video . Let's open and compare traditional software job openings with AI openings . Once you open LinkedIn and compare traditional software job openings, you'll understand how much demand for AI-related roles has increased. And for those who watch in general and don't know these roles, there will be confusion. What is a GenAI? What is an AI agent? What exactly is this agentic AI? You might be wondering if all of this is part of AI. And honestly speaking, many people think of AI as a single technology. But the reality is that AI has evolved in many stages . Imagine exactly like the early days of the internet. In the early days of the internet, there were only websites. After that, the yups were built. Then came the cloud, then came social media, and now AI is evolving in exactly the same way. And in this video, I will explain to you the five stages of AI evolution . From AI answering questions to AI working as an employee, I will explain it in a way that is understandable to complete beginners and entry-level people. And trust me, after completing this video, you will clearly understand the exact difference between these three: Generative AI, AAI, Agents, and Agentic AI. So watch the video till the end and do n't forget to hype the video. And along with that, let's also discuss why software jobs are changing so quickly and why experts are saying AI agents are the next trillion-dollar industry . First, let's understand stage one. Before the advent of AI, how did a human apply for a job? Let me explain with a simple example. Imagine a student is searching for a job. First, he creates a resume, then he opens job portals, creates a profile, updates the profile, searches for jobs, and customizes the resume according to the job description. Using this customized resume, he applies for jobs and then starts interview preparation. So, let's observe here that everything is manual. We log in to the portal ourselves, update our resumes ourselves, and apply for jobs ourselves . So here everything is manual. So before, everything had to be done manually. But at the same time, SlogaAI entered. And AI involvement has increased significantly at literally every stage. Let us now look at exactly the same evolution stage-wise. Stage one generative AI. What is first generative AI ? This is the AI ​​category that a lot of people use right now . What is the best example of this? Open AI, ChargePita, Gemina, YantraPic Cloud, all such tools are examples of generative AI. What do these tools actually do? As the name suggests, generative AI tools generate content. Generates any kind of content text and generates images. They also help with code fixes in email drafting. Simply put, it generates an answer to what you ask. You AskAI Answers That It's a Generative Ace for example, you can rewrite my resume according to the job description, which means it will rewrite your resume according to that job description . Basically, it will generate a response for you no matter what question you ask . But this generative AI has an important limitation: we have to tell it every next step, we have to give instructions through prompts. For example, we told it to rewrite its resume. What to do next? We need to search for a job in a manual process . It only generates a resume . What jobs don't search for. So again, I have to tell you to search for a job that suits my role . And then we have to submit the application ourselves . I haven't worked as an independent here . It waits for instructions from a human exactly like a calculator. The calculator is useful and also performs calculations quickly . But it will give a clear answer only if we clearly state that it is still dependent on humans. Now let's see what use cases generative AI can help with in real time. When it comes to students, it helps them in things like explaining any chapter, generating any assignment content, or giving any ideas for projects . And employees need to create any websites, that is, HTML5 generates JavaScript codes. So in places like this, we use generative AI . But do you know what the biggest strength of generative medicine is? Speed. It responds very quickly. And you know what the biggest weakness is, there is no liberty and freedom. It didn't do anything on its own without our instructions. So it definitely needs our instructions. And if we gave this generative ace some websites or some links and told it to give us the data or access it, it didn't do it. Because it does n't have those capabilities. Now Let's C Stage 2 Generative AI Plus Tools In this stage, generative AI is integrated with external tools . Initially, generative AI did not have direct access to the internet . It was mostly generating answers for us based on the train database. No matter what you ask about the current live broadcast, it won't answer. Because it wasn't trained on it, but now they are integrating GenAS with external systems. Like web search, PDFs are connecting to databases, drives, emails, and internal documents with external systems . So through these tools, AI can access real-time information. Previously, you would give a generic prediction and answer about the best laptops in 2026. But with the current generative AI capabilities, this tool can search the web live, compare the latest laptops, and analyze real-time reviews to give you a better answer. For example, suppose you give your resume and a job description to a current generative AI and ask it to analyze it. The AI analyzes the job description and also analyzes your resume. The AI ​​identifies skill gaps as per the job description and also suggests improvements to your resume . But we still have to give manual prompts, which means we have to do all this, but the intelligence level has increased enormously. Previous Current Tool Usage for GenAI Let's now see how GenAI integrates and uses these tools in real time . Imagine an employee's ZNAI integrates the real-time calendar into company documents. Now the employee tells the ZNAI to prepare a summary for tomorrow's meeting . Then the AI ​​analyzes previous emails . Checks calendar events . Reads relevant documents . And finally prepares the summary. Productivity here has increased massively. But still, human instructions are needed for every step . Now here comes Stage 3 of AI evolution, the Single AI Agent stage. This is a very important stage because here AI doesn't just give answers. Does actual work . Let's first look at what a single AI agent is . Here, AI handles our workflow . It will complete the task according to the instructions we give it . The best example job search agent is if you search for Simply Fine Remote AL Developer Jobs, the agent will search for the job. It filters jobs relevant to your profile and tailors your resume and even prepares a cover letter. And also prepares job applications. And there is minimal human involvement here . Let's look at examples for a real-time single agent . Create an Agent Example Suppose you tell Agent to create an e-reel for an e-post. The agent searches for trending topics. It also generates the script and provides captions. It generates thumbnails, previews, and hashtags. For example, if we build a coding agent, it will identify bugs, generate fixes, and even write test cases. And another interesting thing is that companies are already using this system . And what are the tools used by these agents? There are popular agent frameworks in the current market. What is Microsoft Autogen Long Chain Crew? These tools are used by developers to build AI agents . Now we are going to see another next level evolution of stage four multi-agent systems. There is a software company called Imagine that specializes in multi-agent systems. A single employee can't manage everything in that company, there are different teams. HR team, management team, finance team, development team, technical team, customer support team, all these teams together form a software company. Exactly the same concept has also entered the AI ​​world. That's what multi- agent systems are all about: different AI agents with different responsibilities working towards a single goal. For example, in the job search system we've talked about so far, one agent does the job search. Another agent analyzes the resume. Another agent tailors the resume to fit the job description . Another agent submits the application. And another agent prepares for the interview. And another thing is that these agents also communicate with each other. Just as internal teams discuss and correct each other if they make any mistakes, these multi-agents will also behave in a similar way. They will correct each other by communicating with each other and can think like digital employees. Startups and small companies are already building these. This option is also available in And Perplexity . Now Stage Five Agency This is the final stage This is where the entire world is moving. Imagine an agent with AI that continuously pursues goals without constant prompts. Suppose you simply say, "Get me a better remote software testing job in six months," and then the system continuously tracks openings in the market. Monitors new openings. It also updates the resume and provides relevant certification suggestions. Salary negotiations do it all with this single prompt. You don't need to give a prompt again and again . When we first started, we gave Jenaya step-by-step instructions on how to tailor her resume, change it to match the job description, and find jobs . But AgenticAI doesn't need that. There is no need to give prompts again and again here . And this becomes a digital life operator because agentic AI is different from other AI evolutions. Do you understand what the biggest difference here is that generative AI reacts? AgenticAI takes the initiative . That changes everything, which is exactly why companies are investing billions. In the future, we are going to see agentic AI in many domains. Health agents track your sleep . An agent can track the manual steps you take in your personal life, from monitoring food to analyzing medical reports to managing doctor appointments . And it's not impossible, it's possible, and it's happening right now. This agent is using Age to generate videos on YouTube . While it is possible to generate a complete YouTube video through an agent, it is also highly possible to manage your personal things. And if you want to build a finance agent, it can help you track your finances, monitor bills, optimize investments, and even help with tax planning . Similarly, if you are running a business, you can build a business agent. It handles customers. Automates marketing. Manages your inventory. It also optimizes operations. Basically, all of life becomes like an operating system. Now what is the biggest fear and biggest reality. The reality now is that there might be a chance that repetitive jobs will be reduced. But at the same time, completely new job opportunities will definitely arise. For example, if we go back 20 years, if we had to dig a hole in a construction field, it would not have been completed even if five to 10 members had done all the work manually and worked hard from morning to evening . Now, what happened after 10-15 years is that the Jaybees came. A JSB driver replaced the work of these 10 members . But at the same time, we think that one person replaced the jobs of 10 members here. But JCB had to be manufactured to replace this manual work . A JCB needs to be a manufacturer, which means it has many manufacturing companies that make tires and spare parts. And if running a JCB is a skill for these 10 members, if these 10 members had learned that skill, they would have been in 10 different sides with their skill. So if these 10 members had learned, they would have been in a better position, but because they didn't learn, they feel like they've been replaced. So imagine if the same thing happens in the current situation . Currently, we are only looking at jobs that are being replaced, but we are ignoring the huge opportunities that will be created in the future. Today we learned about the stages of evolution in this video . What is GenAI? What can AI do with tools? What is a single AI agent? What are multi-AI agents? What is agentic AI? I hope you have a complete idea. And remember, we are not in the era of simple chat bots at all. We are entering into the digital workforce era. So I have a question for you: are you still using AI or are you building any such agents? So wherever you look outside, you see all these things being built by agents at huge cost . But in my next upcoming videos, I will do a complete beginner-friendly practical demo on the topic of how to build an agent for free without a single line of code . It's an easy-to-understand way even for those without a coding background. So comment "Build Agent" in the comments. The more comments we get, the sooner the video will come out. And if you find this video useful in any way, don't forget to hype it. And if you are watching our channel for the first time, please subscribe to our channel guys stay tuned for upcoming videos.