EP 582: No, that’s not an AI Agent. Cutting through the Agentic AI marketing hype

Topics Covered in This Episode:

1. AI Agent Hype Versus Reality
2. Gartner Study Exposes Agent Washing
3. Defining True AI Agents vs Workflows
4. Prevalence of Fake AI Agents Market
5. $4 Billion AI Agent Investment Risks
6. Major Tech Companies’ AI Agent Strategies
7. Agentic AI Adoption Failure Rates
8. Narrow vs General AI Agent Use Cases
9. Spotting Fake Agents in Enterprise Software
10. The Importance of AI Literacy for Agents

Keywords:

AI agent, AI agents, agentic AI, agentic AI marketing, AI workflow, pre built automation, chatbot, automation tools, robotics process automation, computer vision, large language model, agent washing, Gartner study, generative AI, AI-powered workflow, agent capabilities, virtual browser, virtual desktop, command line tool, Terminal, AI powered marketing automation, Microsoft Copilot Studio, Google agent space, OpenAI agent mode, Anthropic Claude, Meta superintelligence lab, Salesforce agent force, agentic model, o3, Gemini 2.5 Pro, startup AI agents, narrow AI agent, general AI agent, autonomous agentic AI, enterprise software, investment scam, business decision makers, C-suite, AI strategy, technical reality vs marketing hype, technology adoption failure, FOMO AI investment, AI literacy, AI-powered business processes, scalable AI solutions, narrow task-specific agent, Aqua hire, agent definition, advanced reasoning, planning capabilities, memory systems, adaptive AI, context awareness, workflow automation, business productivity AI, agent integration, AI investment trends, enterprise AI adoption

Podcast Transcript

AI [00:00:01]:
This is the Everyday AI show, the everyday podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business and everyday life.

Jordan Wilson [00:00:17]:
There's a good chance that that agent you're using right now isn't actually an agent. That's because there's thousands of vendors, software providers, marketers, etc, out there just sprinkling a little AI on anything and then calling it an agent. It's getting so bad that I'm literally doing a Hot Take Tuesday episode just to say, no, that's not an agent. So on today's show, we're going to be cutting through the agentic AI marketing hype and telling you what actually is an agent and what isn't, because I'm going to go ahead and spoil it for you. Yeah, there's a chance that the agent that your company just invested in or is looking into is literally nothing more than a marketing automation workflow with maybe a little bit of AI sprinkled in. I'm excited for this one. I hope you are too. Welcome to Everyday AI.

Jordan Wilson [00:01:16]:
What's going on, y'?

Jordan Wilson [00:01:17]:
My name is Jordan. Welcome to this daily livestream, podcast and free daily newsletter helping everyday business leaders like you and me cut through the noise, understand what's happening in the world of AI and then leverage all that good information, the real information, to grow our companies and our careers. So if that's what you're trying to do, it starts here with the unedited, unscripted live stream podcast. But where you take it to the next level is our website at your everyday AI dot com. There you can sign up for our free daily newsletter. We're going to be recapping the highlights from today's show and everything that you need to know, as well as giving you everything you need to know that's happening today in the world of AI. So if you want the AI news, make sure, sure to go check that out in today's newsletter. But let me just get straight into the heart of today's show.

Jordan Wilson [00:02:03]:
So much of what's being marketed and advertised and talked about right now in the AI world is obviously agents. But most of them are lies. Most of them are not actually agents. So here's the facts and the truth about AI agents. Right now in 2025, 95% of companies are claiming to have an AI agent and they aren't. They're lying to you. And I obviously have the receipts to show you that Gartner is one of the largest research organizations in the world. I'VE actually advised them a little bit on agentic AI in their new report, which we're going to go over a little bit today just exposed that only 130 vendors out of thousands that are saying they have agents actually have agents.

Jordan Wilson [00:02:51]:
Yeah, more than 95% don't. Right now we're witnessing, I think the biggest tech marketing scam since, since the dot com bubble, maybe even more so than that. We'll see because it's getting absolutely out of hand. And right now this is a $7 billion market that is built on chatbots and automation scripts and essentially robotics process automation with a little bit of computer vision powered by a large language model, which is not an agent, y'.

Jordan Wilson [00:03:20]:
All.

Jordan Wilson [00:03:20]:
Yeah, you can tell it's hot. Take Tuesday. So here's we're going to be going over on today's show. I'm going to show you how 95% of companies are actually saying they have agents and they don't. And we're going to talk about that Gartner study that exposed a $4 billion investment scam that's happening right now. And I'm going to show you how every major tech company is kind of not making it easy on the rest of us to decide what's an agent and what's not. All right, let's start with the big study. So we covered this a couple of weeks ago in our newsletter and actually I didn't make a big deal of it at the time.

Jordan Wilson [00:03:59]:
This study actually came out in June. We ran it in our newsletter, you know, and I'm like, okay, we're gonna leave that at that. But it like, I don't know what happened. The last six weeks have been absolutely nuts with, you know, all these companies coming out with agents, agents, agents. And I obviously look at them and I'm like, no agent, no agent, no agent. And yeah, that's why I'm dedicating a literal 25 minute episode today to just cutting through all of the BS. Because what Gartner found in this study, they looked at more than 3,000 vendors that were out there marketing AI agents and they actually looked at the capabilities and the features of all of these vendors, all of these different software companies that were saying, hey, we have an agent. And what they found is that only 130 out of the 3,000 plus vendors that they looked at actually had agents.

Jordan Wilson [00:04:56]:
So that means more than 95% of these so called AI agents are just rebranded chatbots and automation tools. And what they're calling it at Gardener is agent washing. I'M calling it the over identification of everything. And I think that we need to stop, right? It's one of those things. And we, we, we have to take a brief look at the technology and the history. Agents aren't anything new even when it comes to the generative AI wave of agents, right? You can go all the way back to right after ChatGPT came out. A lot of earlier companies were promoting agents. And I still think that very few of even the actual agents are having the capabilities of what the future of agentic AI actually is.

Jordan Wilson [00:05:51]:
Right.

Jordan Wilson [00:05:51]:
And I'm going to get a little bit into definitions here in a little bit. But let me just say this. An agent is an AI that goes out, it builds its own solutions and you just give it a task, you give it a goal, you give it an end destination, you make sure that it has the tools that it needs, the information that it may require as well, that may be some credentials, some files, etc, and then it goes out and it builds its own way to the solution. I think today's agents aren't that great, if I'm being honest. I think the agents in a year or two are going to be extremely impressive. But an agent, essentially, it's not a pre built automation, right? That's what so many of these quote unquote agents that were exposed in Gartner study this. That was the number one kind of telltale sign of a company that's just lying to you, right? So if you see all these charts, right? And, and it's like all of these complex workflows and it's like, oh, here's my agent. It's not an agent.

Jordan Wilson [00:06:58]:
That is primarily one of a couple of things. But the biggest liar in the room is those companies that are essentially selling pre built workflows with AI powering them. That is an AI powered workflow, right? An agent doesn't need that. An agent doesn't have a pre built set of decision trees and then it's using, you know, a reasoning model. When it gets to step 13 out of 39, that is not an agent. An agent has a start point, has an end point and the agent finds everything else out in between and it has access in most cases a useful agent at least has access to a virtual browser, has access to a virtual desktop, has access to a command line tool like Terminal and Mac, right? So in other words, an agent has access to the exact same tools that you and I use to do work and they work in roughly the same way, right? There's a start point, there's an end point and us humans are going to go do that work in between. And it might look fairly repetitive. So I'm not saying that AI powered workflows or marketing automation with AI built in, or robotics, you know, RPA robotics, process automation with computer vision and AI.

Jordan Wilson [00:08:21]:
I'm not saying those things aren't agentic because they can be, right? Agentic is describing something, an actual agent that is a noun that is essentially not a replacement per se for an actual human. But an agent is one that can go out and essentially do the same type of work that a human can do without it having to be a pre built workflow. Had to get that off my chest, y'.

Jordan Wilson [00:08:47]:
All.

Jordan Wilson [00:08:48]:
That one been, it's been bugging me. You know, can I, can, can I tell you like a personal story here? I get so many, so many pitches in my email inbox for people, you know, wanting to come onto the show and, you know, tell you, tell you all about how their agent is the best thing since sliced bread, right? Also, I don't mind non sliced bread. Sometimes they just need a big hunk and you know, the old rip and tear French bread from Juwel.

Jordan Wilson [00:09:16]:
All right.

Jordan Wilson [00:09:16]:
And they're like, all right. You know, my, my agent's the best thing ever. Best thing ever. And you know, I get so many of these emails, half the time I don't even look at them anymore. Because I'm guessing if companies just put the word agent in a pitch 50 times, they probably don't know what they're doing. But in the few times that I actually go out and look at it, I'm like, this isn't an agent, this is a feature, right? This used to be, you know, a simple step in a CRM. And now all of a sudden they want to call it an agent, you know, because they're trying to raise money or they're trying to fool you into thinking that they're building something truly valuable. And there's a big difference between something that's agentic and an actual agent.

Jordan Wilson [00:09:57]:
So a little more on this Gartner study. So aside from finding that, you know, 95% of these 3,000 vendors that were selling AI agents, they're not actually selling AI agents. A couple more sobering stats that they found in this research. They found that more than 40% of agentic AI projects that have been launched are going to cancel by the end of 2027, I would say that's.

Jordan Wilson [00:10:20]:
I.

Jordan Wilson [00:10:20]:
Would say it's going to be more.

Jordan Wilson [00:10:22]:
Right?

Jordan Wilson [00:10:22]:
I would say it's going to be more because so many of these projects that are launched right now are launched on agents that number one aren't actually agents. And I think that unfortunately so many small and medium sized businesses aren't using the right agent tool.

Jordan Wilson [00:10:38]:
Right?

Jordan Wilson [00:10:39]:
So if we even look at what agents are available today, I think you have to look at the big players, you have to, right? You have to look at what Google is doing, you have to look at what Microsoft is doing, you have to look at what OpenAI ChatGPT is doing and anthropic and probably meta as well. But if you're looking at AI projects that are going to be successful past 2027 in the enterprise, I would assume the majority of them are going to be one of those five names. Yet I think one of the biggest problems when it comes to agents right now is so many small and medium sized businesses have been swindled by these companies that Gartner kind of exposed in their agent washing study because they're building their whole foundation, these companies on shaky ground.

Jordan Wilson [00:11:34]:
Right.

Jordan Wilson [00:11:34]:
I don't think most of the tech that has come out in the last year or so around quote unquote agents is going to make it. Yes, I think there's some great agent startups, right? Gen Spark, Manus, etc, but I, I do think if you are a decision maker at an enterprise company, especially here in the us you're probably going to have to get on board with one of those five, right? OpenAI I think came out with a pretty capable agent. I wouldn't say it's great yet in their new agent mode, Microsoft has probably been leading the way here with their Microsoft copilot studio. Google, they have great products out there but unfortunately very few people have access to them with their kind of agent space and some of their other agent offerings. And we'll see what ultimately meta with their new Meta superintelligence lab as well as Claude, Claude has more coding agents, right? So they don't have necessarily general use case agents. So we'll see what the big, the big five ultimately end up. You know how much of their future product development is centered around general purpose agents. But additionally this Gartner survey said that by 2028 more than 50% of day to day work decisions will be made by autonomous agentic AI.

Jordan Wilson [00:12:57]:
And that's at a 0% last year in 2024. That's actually a big jump, right? You might look at 2028 and be like oh that's three years away. 15, you know, more than 15% of you know Daily work decisions. That doesn't seem like a lot, but how many decisions do you make a day? Think about that. Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on Genai. Hey, this is Jordan Wilson, host of this very podcast. Companies like Adobe, Microsoft and NVIDIA have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead. And some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use GenAI.

Jordan Wilson [00:13:57]:
So whether you're looking for ChatGPT training for thousands or just need help building your front end AI strategy, you can partner with us too. Just like some of the biggest companies in the world do. Go to your everydayai.com partner to get in contact with our team. Or you can just click on the partner section of our website will help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on Geni. I would venture to guess that most of us make dozens, if not more than a hundred decisions every single day. You may not realize it, right? But oh, it's like when you're looking at that email, all right, which version of the pitch are you going to send? How are you going to reply to. Objection.

Jordan Wilson [00:14:49]:
A.

Jordan Wilson [00:14:50]:
How are you going to steer the next conversation forward?

Jordan Wilson [00:14:52]:
Right?

Jordan Wilson [00:14:53]:
You may not even realize it, but every single important email you look at, you might make 5, 10, 15 decisions. So when it comes to looking at a stat like, okay, more than 15% of decisions, day to day work decisions are going to be made by agents by 2028. I think that's actually a giant number, right? I again, I think it's going to be more because I think that the big, big tech companies, specifically Microsoft and Google, they've already, they've, they've laid their cards out. They're going all in on real agents, unlike a lot of these vendors that are pushing a bunch of garbage. So I do think that number is going to be higher. Also in the Gartner study, they said that by 2028, more than a third of enterprise software applications will embed a gentic AI. And that's right now in 20 or sorry, in 2024, the last full year that was included in the study, that was less than 1%. It's a pretty big jump, right? So yes, not Only are we going to be, you know, having access to real actual AI agents with I think those five big tech companies, but all the other big software providers.

Jordan Wilson [00:16:05]:
Right.

Jordan Wilson [00:16:05]:
Like good example, you have Salesforce with their agent force, which I'm not personally a big fan of, but that's an example, right? That shows, you know, how agents are going to be bleeding into all enterprise software. But what this boils down to, so many companies are just lying about having AI agents. I've literally been on calls with people that are like, hey, you know, look at my agent. And then they show me a, a GPT. Literally they show me a custom GPT and say, look at my agent. Part of that's marketing. Part of its, you could argue part of its semantics and definitions, but I don't think so. Right.

Jordan Wilson [00:16:50]:
There's agentic models that we all use, right? I'd say the most popular agentic models would be OpenAI's o3 and Google Gemini 2.5 Pro. Those models themselves are agentic. So agentic AI sure is everywhere. But there's a huge jump skip in a leap between what constitutes agentic AI and what is an actual agent. So I think that we really have to separate that, right? So right now, startups in 2024 raised $3.8 billion to build agents. And I've used a lot of them and I'll say most of them are either, you know, like you're just making pre built workflows, right? Like if you've ever used N8N, right? Nothing against N8N. I think it's a great platform. But everyone's talking about oh, these agents.

Jordan Wilson [00:17:45]:
I'm like, no, that's a workflow. It's an AI powered workflow, right? And right now also a recent study showed that 88% of executives are investing in Agentic AI without even knowing what they're buying. And that's problematic, right? And I think the companies that are doing it correctly usually have a C suite that's already been bought in to marketing automation.

Jordan Wilson [00:18:14]:
Right.

Jordan Wilson [00:18:15]:
I think the companies that have been using, you know, tools like Zapier or Make, right, some of these more marketing automation platforms for many years before the AI hype and then they're able to quickly decipher between what's actually an agent and what's just, you know, dressed up with a little bit of makeup and fancy language. But so many companies are getting burned on agents right now for that very reason because these companies are just printing money, right? If you're a startup, I wouldn't say the rest of the year. But if you had a startup in mid 2024 to mid 2025 and you said, hey, this is an agent and you had an okay demo, you raised tens of millions of dollars, right? And so now this is, you know, something I get all the time. We do consulting for companies and you know, companies are like, hey, you know, we're looking at these different agents. And I'm like, no, don't do that, right? Don't build your day to day processes around a something that's not actually an agent and say it's agentic AI. Because what happens when we actually have more capable agents than what we have today? All of that work is going to be for Nye, right? You just wasted, you know, however many human hours. When I think we're going to have much more capable true AI agents in 2026, I don't. Unlike everyone else, everyone else has been saying, you know, oh, well, I mean, to a certain extent I did as well, right? But talking about how 2025 is the year of the AI agents, and I think the actual definition of that is just the availability of technology that says, yeah, we're agents, but I don't think this year is the year where we're going to see actual useful gains from real agents because of this problem.

Jordan Wilson [00:20:16]:
And it's deception, right? Another study showed that 85% of companies plan to use AI agents by this year, but only 2% have actually scaled them successfully.

Jordan Wilson [00:20:29]:
Right?

Jordan Wilson [00:20:29]:
So so many companies are using it, but, you know, it's more of like, you give it one task or a group of tasks and you're like, okay, well, we think this is helpful, but we can't really scale this across our organization. So right now, industry analysts predict that over 40%, like I said through the Gardner study, are going to fail. And I think this is one of the biggest disconnects between marketing hype and technical reality that I've ever seen. Like, I literally, you know, a year ago I would get excited, right? Oh, there's a new AI agent. Cool. Now it's just, I don't know, it's vomit inducing because it's like, don't, don't touch it, right? A company that's launching today with, oh, this great AI agent, they're not going to make it, right? I hate, I hate using this as an example because it was a great company, right? But look at Wind Surf. You know, there's obviously at the same time as the agent craze, the vibe coding craze, and I'd say Six months ago Windsurf was probably the second biggest or best company out there when it came to vibe coding.

Jordan Wilson [00:21:43]:
Right?

Jordan Wilson [00:21:43]:
So building applications through natural language without having to know how to, you know, create actual software, you would again, I'd say six months ago you can make an argument, you know, GitHub, Copilot maybe was was ahead of them, but I would say it was probably Cursor was number one and Windsurf was number two. Maybe it was more like nine months ago. So I know a lot of organizations that built their day to day processes, at least on the software engineering side around Windsurf. Great tool, seemed like it had a great future. What happened? Google, Aqua hired their leadership and the rest of the organization kind of just got dissolved or bought up by Cognition. So what happened to those companies that spent six, seven figures and just moved all their processes over to wind surf? You wasted your time. So I want that to be a cautionary tale on these new upand cominging agents because they look so shiny, they look so cool. But y', all, if there's not a trillion dollar market cap in the company that you're building your AI agents on, you're probably in the wrong place, right? And I'd say the only exceptions to that rule would be OpenAI and Anthropic, right? So it's like, all right, you should probably be building on Microsoft, Google Meta.

Jordan Wilson [00:23:15]:
I mean technically you can build on NVIDIA and then probably OpenAI and Anthropic anything like if you're building on, you know, again, nothing against these startup promising AI agent, you know, companies. I personally wouldn't do it and I wouldn't advise anyone else to do it anyways because look what's happening in the space. Some of these smaller, you know, startups that have only been around for maybe a year, maybe a year and a half, even if they have technology that seems great, there's a good chance that they're going to get Aqua hired straight up acquired or maybe just squashed because you never know. What happens when we get the second version of OpenAI's agent mode, the first version, pretty good, right? What happens when Microsoft Copilot Studio gets even better? What happens on the Google side, right, when Google Agent space is generally available?

Jordan Wilson [00:24:11]:
Right.

Jordan Wilson [00:24:11]:
Right now it's not. But what happens when it's generally available in Project Mariner and Agentic browsers?

Jordan Wilson [00:24:17]:
Right.

Jordan Wilson [00:24:18]:
The space is, I think, changing too quickly. So how do we get here? How do we get to this point where I think that this is literally such a toxic and Troublesome environment. Well, number one, there's no definition, there's no agreed upon definition of what an AI agent actually is. And that's problematic, right? And that's, I mean you can make the argument that's anything right now in, in a, in the AI world, right? No one can even agree what a large language model is or an agentic model, right? So I think one of the biggest reasons why so many companies are getting scammed and getting disappointed and then they just get bearish on agents, which I think is a bad move. You know, they make a bad business decision, they go with one of these startups and then they think, okay, well hey, agents don't work. No, you made a bad decision. And one of the reasons why is because everyone's marketing agents, agents, agents, it allows them to raise more money, it allows them to get new clients and customers and then their text stinks because there's no agreed upon definition of what an agent actually is. And I think that it's become a mandatory buzzword, especially for public companies, right? So last year, public companies in their earnings call, they have to say AI, AI, AI.

Jordan Wilson [00:25:31]:
Or maybe that was like two years ago, but in 2024, you know, they said agents, agents, agents, agents, agents. And it's been a buzzword. And like I said that earlier study, 80% of executives don't even know what they're spending their money on when it comes to agentic AI, but they just know they have to gotta spend my money on it, right? And right now another study showed that 93% of business leaders, business leaders think they need AI agents for a competitive advantage, but they don't even know what for. It's just fomo. That's all it is. And I don't think that this is the last time that we're going to have this trending category that's going to take over the business narrative, right? And everyone's going to say, oh, you know, I don't know why we need agents, but we need them, right? Because that's what's going to, you know, help us cut down our, you know, our staffing or that's what's going to increase our productivity. And I think it's just FOMO right now. And like I said, real agents, they have advanced reasoning, they can plan multiple steps in ahead independently without human guidance.

Jordan Wilson [00:26:45]:
True agents don't need workflows built for them. Let me say that again. True agents do not need workflows built for them. What they need, they need memory systems that learn and can remember context across long conversations and tasks. And true agents integrate with the tools and systems to take actions in the real world. And most importantly, agents adapt in real time to unexpected situations and changing goals. Like a human, right? A human starts a task, they find out new information, they're like, oh, okay, I need to go get a new tool for this. I, I need a different file, I need to go find new information.

Jordan Wilson [00:27:32]:
Oh, I need to make a, a slide deck for this now. I need to create a spreadsheet for this now.

Jordan Wilson [00:27:37]:
Right?

Jordan Wilson [00:27:38]:
The deliverables change the direction of the outcome, can be modified. AI powered workflows, agentic AI models can't do that per se. They can't. A true agent, I, I, I literally like to say think of it like an intern because that's I think where they're at right now with general AI agents. I think narrow AI agents are actually where businesses are going to see the true, like the true value of AI agents. But a general AI agent, you have to think of it like me and you sitting in front of a computer. They have a browser, they have a computer, they have a terminal, they have a project and they get to work.

Jordan Wilson [00:28:21]:
Right?

Jordan Wilson [00:28:22]:
It's nothing pre built. We're not telling them what to do. At steps 1, 2, 3 and 4, we say here's your goal, here's your environment, you have all the needed information. Go get to work. So how can you spot the lies?

Jordan Wilson [00:28:38]:
Right?

Jordan Wilson [00:28:38]:
If this is such a problem, and it is, and I think so, many companies are going to waste multiple quarters, in some case more than a year, in many cases, millions of dollars and just really valuable resources, how can you spot the lies when it comes to agents? I already told you the easiest way. I said it's the trillionaires plus two. But think large language models. Just respond to prompts, all right? And there's no planning or persistence between conversations. AI powered workflows follow predetermined scripts that are built by humans with some AI featured sprinkled in along the way. But true agents set their own goals. They figure out step by step how to achieve them without needing any of it. Built by humans.

Jordan Wilson [00:29:31]:
And most products and companies and softwares today that are calling themselves agents are just fancy RPA systems. They're marketing automation. They're if this then flows with a little bit of AI sprinkled in. So here's the hot take again. Outside of the trillionaire five and the other two, I wouldn't trust anything with the word agent. I really wouldn't. Or at least I wouldn't trust my day to day business operations because that's what companies are ultimately looking to do when it comes to agents. They're trying to replace entire crucial workflows.

Jordan Wilson [00:30:14]:
I wouldn't, outside of the big five and the other two, I wouldn't trust any of them. And I think so many companies now are looking at general use agents which I don't think is a good thing. I think narrow agents are where we're first going to learn how to work with agents.

Jordan Wilson [00:30:30]:
Right.

Jordan Wilson [00:30:31]:
So narrow task specific which I actually think, you know, kind of some of these new sub agents from anthropic Claude when it comes to coding that's a great use case. I think a like AI agents who specifically code. I think those organizations that have already implemented those are going to see some great gains you know, having narrow use cases. But right now I think very few organizations are primed to handle today's general agents. Are they great? They're okay. But I do think you still have to be experimenting now. But one of the biggest reasons why so many organizations can't really take advantage of these more general AI agents that are available now is they skipped AI literacy.

Jordan Wilson [00:31:16]:
Right.

Jordan Wilson [00:31:16]:
And how can you expect your marketing team, your finance team, your HR team to know and understand and use AI agents if they still weren't even trained on the basics of GenAI in large language models? Again, that's a leadership issue. That is so many companies are skipping over investing in their people and just investing in flimsy agent software. And I'll say agents are real. I don't want you to get the wrong impression, right, that 95% are fake, but that 5% is very real. But I do think we are going to have an artificial bubble around that 95%. But don't let that sway you. Don't let that sway you. Focus on what matters, focus on what works and don't get swept up in the hype and the distractions.

Jordan Wilson [00:32:12]:
All right.

Jordan Wilson [00:32:12]:
I hope this helpful, I hope this episode was helpful and I just had to get this hot take out of the way and just say one more time, no, that's not an agent. And hopefully this helped you cut through the agentic AI marketing hype. So when you're making a decision for your company when it comes to your day to day business processes, you need to actually understand what an agent is, what it isn't. Do you need one and is your team ready to take advantage? All right, if you need more on this, you know we've got it in today's newsletter. So if you haven't already, Please go to your everyday AI.com Sign up for the free daily newsletter. Thank you for tuning in. Make sure to join us tomorrow. We're doing the Putting AI to Work at Wednesday, our new Wednesday series.

Jordan Wilson [00:32:58]:
I'm excited for it. It's going to be a good one, let me just say that. So thank you for tuning in. Hope to see you back tomorrow and every day for more Everyday AI. Thanks, y'. All.