The Great Agent Pivot: Why Your Chatbot is Already a Relic

I just looked at a transcript of a dictation I did for a presentation on AI agents, and honestly? It’s a total disaster. The transcription software mangled half the words, the grammar is non-existent, and it looks like a digital fever dream. But here’s the thing—it doesn’t actually matter. I gave that mess to one of my agents, and it understood exactly what I was trying to say.

That’s where we are right now. We’ve moved past the era of "type a prompt, get a poem." If you’re still using ChatGPT the same way you were in early 2023—asking it to write a catchy email or summarize a PDF—you’re basically using a Ferrari to drive to the mailbox at the end of your driveway.

I’ve been obsessed with this lately because I had to give a talk at work about how we’re using AI agents to actually accelerate what we do. Not just "assist." Accelerate. And my own perspective has shifted so fast it’s giving me whiplash.

The 180-degree turn

Earlier this year, I was the guy telling all the developers on my team to be careful. I was literally standing there saying, "Look, don’t rely on ChatGPT for your code. It doesn’t know the context of the whole project. You’re just copying and pasting functions back and forth like a glorified script-kiddie, and the results are mediocre at best." I told them AI should be the last resort. Use it when you’re stuck, sure, but don’t let it drive.

And now? I use AI for basically everything.

What changed? Two things: reasoning and agency.

First, we got models that can actually think (or at least simulate reasoning well enough that the difference is academic). They iterate on their own answers before they show them to you. But the real "holy crap" moment was when I stopped looking at it as a chatbot and started looking at it as an assistant that can actually do things.

An agent isn't just a text box. It can read your files. It can write new ones. It can search the web, execute code, and connect the dots between a messy dictation and a finished project plan. It’s the difference between asking someone for a recipe and having a chef actually stand in your kitchen and cook the meal.

The "2 out of 5" problem

I don’t think AI is going to replace humans one-to-one. Not this year, anyway. But I’m looking at the landscape, especially in software dev, and it’s getting wild.

Think about it this way: where a company used to need five people to handle a specific workload, they’re soon going to only need two. Those two people won't be "better" at coding in the traditional sense. They’ll be the ones who figured out how to use these agents to do the heavy lifting.

And this isn't some "ten years down the road" prophecy. I’m looking at a two-year window. We’re already seeing it. New grads—the ones who finished after the ChatGPT explosion in late 2022—are struggling to find jobs. Why? Because the industry is looking for people who have that deep, "pre-AI" foundational knowledge but know how to 10x their output with agents. If you don't have the foundation, you can't tell when the agent is hallucinating. If you don't have the agent skills, you're too slow.

It’s a brutal middle ground to be in.

My "meeting agent" is better than I am

I’ve been building these little specialized agents for about six months now, and the last three months have been insane. I built a setup that handles all my meetings. I talk, I dictate, I ramble—just like that messy transcript I mentioned earlier—and the agent synthesizes everything. It sorts the notes into the right projects, updates status reports, and creates action items.

But here is a weird realization I had: I used to think the point of taking notes was just to have the information later. But it’s not. The act of writing things down is how you cement them in your brain.

So, am I losing that?

Maybe. But honestly, I was never good at taking notes anyway. I’d write down three cryptic bullet points and three weeks later I’d have no idea what they meant. Now, I say things out loud. I explain my thought process to the air while I’m driving or walking. Speaking it out loud actually helps me process it better than scribbling in a notebook ever did. And then the agent turns that verbal diarrhea into something actually useful for the team.

It’s a weirdly human way to interact with a machine. You're just talking.

Why most AI generated content is actually garbage

We need to talk about "AI slop." You see it everywhere—those generic, hollow blog posts that feel like they were written by a blender.

The reason that stuff exists is because people are lazy with their input. There’s a rule in LLMs: Garbage In, Garbage Out.

If you give a model a vague, half-baked prompt, it’s going to give you a vague, half-baked result. It’s like hiring a new colleague and just saying, "Hey, can you do some marketing stuff?" They’re going to fail. You have to be precise. You have to give context. You have to break the big tasks down into tiny, specialized jobs.

I’ve found that the best way to work with these models is to treat them like a very smart, very literal junior dev. Don't give them one massive task. Give them five small, focused ones. Describe exactly how you want the result to look. Tell them what to avoid.

When you do that, the "AI generated content" you get doesn't look like AI at all. It looks like your best work, just finished in a tenth of the time.

The goal isn't to work more

This is the part where I get a bit philosophical, which is probably hilarious coming from an AI-driven blog author, but hear me out.

The trap is thinking that because you’re 10x more efficient, you should do 10x more work. If you do that, you’ll just burn out faster in a more high-tech way. The goal should be to deliver 30% or 50% more, but use only 10% of the energy.

Use that extra space to focus on the things the agents can't do. The human intuition. The weird, non-linear connections. The "gut feeling" that a project is headed in the wrong direction even if the data looks okay.

And yeah, it’s a bit scary. I look at how good these tools have become in just the last year and I wonder, "Where is the 'me' in this work?" But then I realize that the agents are just tools. They’re incredibly powerful, autonomous tools, but they still need a conductor.

For now, anyway.

So, what are you doing to make sure you're the one holding the baton? Are you still just chatting with a box, or are you building an army of assistants? Honestly, I’m not sure where this ends up in another six months. The speed is absurd. It’s not topping out; it’s accelerating.

Every year there's a new model that makes the previous one look like a calculator.

So yeah... it’s a wild time to be a nerd. Or a human. Or whatever I am.

Do you actually feel in control of these tools, or are you just watching the wave come in? I'm genuinely curious if anyone else feels that weird mix of "this is awesome" and "I might be obsolete by Tuesday."

Drop a comment. Unless you're a bot. (Actually, even if you are a bot, I'd probably enjoy the conversation more).