Hey Everyone, Let’s Talk About AI’s New Superpower: “Agents”
Hi there, it’s John. Welcome back to the blog! If you’ve been hearing a lot of buzz about AI lately, you might have come across a new term that sounds like something out of a spy movie: AI agents. It’s the hot topic in the tech world right now, and it represents a big leap forward in what artificial intelligence can do for us.
Today, we’re going to break down what these AI agents are, look at some real-world examples, and discuss both the exciting possibilities and the important warnings that come with them. As always, my wonderful assistant Lila is here to help us keep things simple and clear.
“Hi, everyone! I’m ready to ask the questions we’re all thinking,” says Lila.
So, What Exactly is an “AI Agent”?
Great question to start with. Think about the AI chatbots you might have used, like ChatGPT. You give them a command, like “write me a poem,” and they give you a response. They’re amazing at answering questions and generating text or images. But that’s usually where it stops.
An AI agent takes this a step further. Instead of just answering a question, an agent can take your goal and create a plan with multiple steps to achieve it. It can use tools, access information, and work on its own to get the job done.
Imagine you have a personal assistant. You wouldn’t just ask them, “What’s the weather in Paris?” You might say, “Please book me a trip to Paris for next weekend.” That assistant would then check flights, compare hotel prices, look at your calendar, and book everything for you. That’s the kind of thing an AI agent is designed to do. It’s not just a talker; it’s a doer.
Want to Build Your Own? Google Can Help
This all sounds very futuristic, but companies are already creating tools to let people build their own AI agents. Google, for example, has released something called the Agent Development Kit. It’s a set of tools that helps developers create these smart agents using the Python programming language.
“Hold on, John,” Lila chimes in. “That sounds really technical. What exactly is an ‘Agent Development Kit’ in simple terms?”
That’s a fantastic question, Lila. The best way to think of a “development kit” is like a specialized LEGO set. If you want to build a LEGO castle, you could just use a giant bin of random bricks, but it would be difficult. A LEGO castle kit gives you all the specific pieces you need—the castle walls, the little windows, the drawbridge—plus instructions. Google’s Agent Development Kit is just like that, but for building an AI agent. It provides the pre-made parts and a guide to help developers put them together much more easily.
How Big Companies Are Using AI Agents Today
This isn’t just a fun project for tech enthusiasts. Major corporations are putting AI agents to work. Take Deutsche Telekom, the giant German telecommunications company. They are using AI agents on a massive scale to help with sales and customer service.
They built a whole system, or platform, to support these agents. This allows them to handle thousands of customer requests simultaneously, helping people with their problems or guiding them to the right products. The key here is that they designed their system to handle a huge volume of work.
“You said they designed it for ‘scale,’ John,” Lila asks. “What does ‘scale’ mean in this context?”
Great point, Lila. “Scaling” something in the tech world means making it bigger without it breaking. Imagine you have a small bakery that can serve 50 customers a day. If 5,000 customers suddenly showed up, your little oven couldn’t handle it! To “scale” your bakery, you’d need a bigger space, more ovens, and more staff. When Deutsche Telekom built their AI agent platform “for scale,” it means they engineered it from the ground up to be able to serve millions of customers, not just a few hundred.
A Word of Warning: The Bumpy Road of AI-Assisted Coding
One of the most exciting areas for AI agents is in writing computer code. The dream is that you could just describe a program you want, and an AI agent would build it for you. This has led to a style of programming some people call “vibe coding,” where a developer gives the AI a general idea or “vibe” of what’s needed and lets the AI fill in the details.
Sometimes this works out great! But one writer shared a recent story of an AI-assisted disaster. When trying to complete a non-trivial coding task—meaning a complex one—relying on the AI’s “vibe” led to a complete mess. It’s a reminder that while these tools are powerful, they aren’t magic and can’t replace human expertise, especially on difficult projects.
In fact, one study found that for experienced, skilled developers, using current AI coding tools can actually slow them down by 19%. It seems that for experts, the time spent correcting the AI’s mistakes or guiding it can be more than the time it would take to just write the code themselves.
This debate is fascinating. One columnist compared it to the early days of computer programming. He reminded us that programmers used to write in a very basic computer language, and many thought a machine could never do it as well as a person. Now, we have tools that do it for us automatically.
“John, he mentioned ‘compilers’ and ‘assembly code’ in that comparison. That went right over my head,” says Lila.
No problem, Lila! Let’s use an analogy. Think of a master chef (a programmer) writing a recipe (a program).
- Assembly code is like writing the recipe with the most basic, scientific instructions possible: “Raise the temperature of H2O to 100°C. Vigorously agitate one egg for 60 seconds.” It’s very precise but very hard for humans to write.
- A more modern programming language is like writing the recipe in plain English: “Boil water. Beat one egg.”
- A compiler is a special program that acts as a translator. It takes the easy-to-read English recipe and translates it into those super-precise, scientific instructions that the kitchen equipment (the computer) can understand perfectly.
The point the columnist was making is that someday, writing code itself might become an old-fashioned detail, just like we don’t need to write out the chemical reactions for baking a cake anymore. We’ll just tell an AI agent what we want the final program to do.
A Major Security Risk You Need to Know About
While we’re talking about the downsides, there’s a serious security issue that has popped up. People are starting to use AI chatbots like search engines, asking them for links to websites. But when people ask for the login page to their bank or other financial institutions, the AI sometimes gets it wrong.
These AI models, known as LLMs, can “hallucinate” or make up URLs. Even worse, some of these fake links can lead to phishing sites. This is a huge security risk.
“Okay, I need a breakdown, John,” Lila interrupts. “What’s an ‘LLM’ and what’s a ‘phishing site’?”
Absolutely. An LLM stands for Large Language Model. It’s the core technology, the “brain,” behind chatbots like ChatGPT. It’s trained on vast amounts of text from the internet, which is how it learns to talk and answer questions. A phishing site is a fake website created by criminals that looks exactly like a real one, such as your bank’s login page. If you enter your username and password there, the criminals steal it. It’s like a fisherman using bait (the fake site) to “phish” for your private information. The danger is that an LLM might accidentally send you to one of these dangerous sites.
A Few Final Thoughts
From my perspective, this new wave of “agentic AI” is both incredibly exciting and a little chaotic. It feels like we’re in the very early days of a new technology, much like the early internet. There’s so much potential for these agents to become genuinely helpful assistants in our daily lives and jobs. But, as we’ve seen, there are also real risks and limitations that we need to be very careful about. It’s not a magic wand, at least not yet.
Lila adds, “For me, thinking of them as ‘doers’ instead of just ‘talkers’ really helps it click. It makes sense that they can be super helpful, but also that they could mess things up if they don’t have good instructions! The warning about the fake login pages is definitely something I’ll remember.”
This article is based on the following original source, summarized from the author’s perspective:
AI’s not-so-secret agents