Do you ever feel like the AI world has moved forward a little too quickly? You hear about self-healing systems and autonomous agents and start wondering whether we've already built Skynet or everyone around you is just messing with you. When someone mentions HITL or MCP, you no longer know whether it's some secret code used by an AI cult or maybe the stage names of famous DJs.
In this article, I'm deliberately using a lot of simplifications. My assumption is simple: either you already know these terms and don't need another five-paragraph academic explanation, or you don't really know what they mean. And in that case, the last thing you need is an academic definition.
And yes, this is already my third listicle in a row. Believe me, this is NOT some growth hacking strategy xDDD. Pure coincidence. It just so happens that in two weeks (HOLY SHT!!!), I'll be speaking at AGNTCon + MCPCon Europe, where I was invited because of this wonderful article that I wrote here on DEV. I swear I had at least as much fun writing it as people apparently had reading it. So yes, I know WebMCP reasonably well, but I'm planning to attend a lot of other talks there too, so apparently a refresher won't hurt me either. 😅
Anyway, back to the point. I strongly believe that people remember things best through examples. And for many people, the ultimate examples are rich people, otherwise known as successful people.
So let's imagine that our hypothetical protagonist is very, very, disgustingly rich. He's actually a billionaire. He earned his fortune through hard work and by running several companies. He makes cars and rockets, bought his own social media platform, and recently even acquired an AI coding company. A person like this would obviously need his own AI agent.
And because our protagonist needs a name, let's call him Elon Mózg. Mózg means brain in Polish, which works beautifully here.
One more thing: my examples could probably also serve as prompts for a coding agent that could build this whole uber-agent. If some billionaire wants to buy the idea, I'll happily sell the rights for, let's say, a modest $10 million. Special offer.
An AI system that gets a goal and can decide how to achieve it. Unlike a simple chatbot, it doesn't have to stop after generating one response. It can plan the next steps, use tools, inspect their results, and continue working.
A regular chatbot would probably start telling him stories, give him a theoretical lecture, and maybe even say something ridiculous like that's currently impossible.
An agent, on the other hand, would start figuring things out: check the nearest available rocket launch slots, inspect the rocket's technical condition, recruit engineers, order the necessary equipment online...
Okay, maybe it wouldn't go quite that smoothly. But what if we put a really powerful model in there? xDDD Agentic Workflow
An agentic workflow is a multi-step process in which we use AI to perform parts of the work. The sequence of those steps can be largely designed in advance by a developer. The model doesn't necessarily have to decide what to do next every single time.
Elon Mózg is a very busy man. Every morning, he wants a summary of what's happening across his empire.
AI performs several tasks here. It analyzes the data, selects the most important information, and prepares the report, but it doesn't invent the entire process from scratch every morning. We already decided which steps should happen and in what order.
But we're still moving through a workflow that we designed beforehand. Agent Loop
I once wrote an article demonstrating that you can build a basic AI agent as a loop in roughly 80 lines of code. An agent loop is the mechanism that allows an agent to perform an action, observe the result, and decide what to do next based on what happened.
The loop continues until the agent decides that it has achieved its goal, or until we tell it to stop. In a real system, setting a maximum number of iterations is definitely a good idea. 😅
This time, we haven't programmed the exact path leading to the solution. The agent has to find it itself.