Earlier, LLMs like ChatGPT, Gemini, and Claude were evolved as conversational AI chatbots. We ask questions, and they respond with the most probable answer. Besides, they have also been assisting us in many other ways like writing articles, summarising information, and generating code.

However, recent advancements have even enabled them to complete a particular task on our behalf. Today, these LLMs can search the web, analyse documents, create images, create beautiful presentations, write code, generate files, process spreadsheets, and even schedule tasks , all without making much effort by humans themselves. This naturally raises an important question: Are today’s LLMs evolving into AI agents?

Are today’s LLMs evolving into AI agents?

What is an agent?

An AI agent takes actions to achieve a specific goal. An agent uses tools, makes decisions, and performs multi-step tasks. Today, they have access to your calendar, the ability to book flights, can send emails, and generate reports on your behalf with minimal supervision.

What makes a system a true AI Agent?

For a system to be qualify as a true AI agent, it must possess the following three key capabilities working together.

Tools: Tools provide the way which makes agents capable to interact with systems beyond the conversation itself, such as web browsing, file management, API access, and code execution.

Memory: This gives the agent the ability to retain context across conversations, tasks, and time. A system that forgets everything when a session ends can not be treated as a true AI agent; but becomes more like a chatbot .

Autonomy: This is an important aspect of a true AI agent. This is what makes an AI agent capable of taking decision to break the goal into smaller steps and execute those steps. It can adapt to unexpected situations, and can complete tasks with minimal human involvement.

Why Modern AI Feels More Like an Agent

Today’s LLM system can work beyond just answering questions. Earlier, you asked chatbot how to create a PowerPoint presentation, it would simply explain how to do that. Today, your favourite AI assistant can create that presentation for you.Earlier, you asked chatbot how to convert a transcript into subtitles. But today your favourite AI assistant can convert the transcript itself and generate the subtitle file in the correct format. Recently, I needed to generate a new subtitle for one of my YouTube videos. I asked ChatGPT how to create subtitles from the transcript. It mentioned to me the ways to do that. At last, it also suggested that it could generate the subtitles for me. Rather than doing it manually, I decided to let ChatGPT handle the task. Within a few seconds, it processed the transcript, formatted it into the SRT format, and generated a downloadable subtitle file for

1. I did not need to make any effort to do the same.

This shows how LLM models have been shifted from merely providing answers to systems that can actually complete tasks letting the user just sit and relax and doing other chores.

Thus, the ability to use tools and perform complete workflow itself is making these systems feels agent-like.

Are ChatGPT , Gemini and Claude True Agents?

Not yet. It is true that today they can perform actions using tools as needed , and complete tasks on user’s behalf. But they still require user instructions and can operate only within pre-defined boundaries. They can not independently pursue goals for days or weeks without user involvement. Thus, they do not possess the capability of being autonomous that a true AI agent must have.

The Future of AI Agents

The future of AI is moving towards developing capable agents. In the future, users may no longer need to assign individual tasks to AI systems. Instead , users assign a goal and allow the AI to determine the necessary steps.

Take a typical business workflow: research a topic, create a presentation, generate supporting visuals, write speaker notes, and prepare a summary report. Here each task is not being performed separately. Instead, an advanced AI agent is involved in execution of the entire workflow from start to finish. As tool usage, memory, reasoning, and automation continue to improve, the distinction between  chatbots and agents will become less clear.

The challenges of Agent Era

When a chatbot gives you a wrong answer, what would you lose? Only your precious time. You read the given response, determine that this is incorrect, discard it, and move on to give the next prompt. However, when an AI agent performs a wrong action, the consequences may be drastic. You can imagine the consequences if it somehow booked the wrong flight, sent an incorrect email, or deleted an important file—

This shift has raised a new set of questions :

1. Who will be held responsible when an AI agent makes a mistake?
2. How can users audit an agent’s actions?
3. How do we grant an agent only the necessary access to take an action without causing serious harm?

These are among the most important challenges that AI companies are currently facing and are actively working towards finding the appropriate answers in the process of developing more capable agents.

Conclusion

Wrapping up, ChatGPT, Gemini, Claude etc are not just chatbots; they can perform many actions on your behalf. But they are not yet fully autonomous agents. Their ability to use tools, perform multi-step tasks, and act on behalf of users make them more agent-like than just a conversational assistants.

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