In this video, the presenter challenges the prevailing narrative that AI is rapidly eliminating jobs, especially in tech. She opens with a Reddit anecdote about "vibe coding" where an employee relied on AI-generated statistics that were later discovered to be fabricated, highlighting the danger of AI hallucinations. She contrasts two corporate responses: IBM, which after experimenting with AI and recognizing its limits, announced a tripling of entry‑level hiring to preserve a future talent pipeline; and Salesforce, whose CEO publicly celebrated massive layoffs as proof of AI success, only to later admit reliability issues and regret the decision. The speaker argues that the fear of AI-driven job loss is largely manufactured by AI vendors, CEOs, and investors who profit from selling AI solutions, using fear as a sales tactic. She then focuses on specific roles, asserting that data analysts are unlikely to be replaced because companies still need human judgment and strategic thinking, whereas software engineers face greater disruption. She notes a growing market for professionals (lawyers, data scientists) who clean up AI errors, turning AI hallucinations into new revenue streams. Throughout, she emphasizes using AI as a copilot—leveraging it for acceleration and mundane tasks—while keeping humans as the pilot for judgment and decision‑making. The video concludes with a call to recognize AI’s limits, maintain human oversight, and understand that the real value lies in the work humans do, not in AI’s false promises.
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Okay, so men lie, women lie, and AI lies too. So first, I wanted to share what sparked this video because context matters, of course. So a student in my community posted a screenshot of a post from Reddit and it was absolutely insane. Apparently someone had been using AI at their job for a few months. So months of outputs, months of decisions made from their management. And then they realized that all the outputs and stats that the AI Provided was made up. Now, not sharing this because trying to be funny here. This is actually an insight of a peek into vibe coding gone wrong across the board. For every one of these stories, there's many, many more. There's also some people that may say that, hey, this might be fake or whatever. It doesn't matter. Again, this happens a lot more than we are actually willing to say out loud. There's tons of vibe coding gone wrong stories on Reddit if you ever wanted to take a look. Now, here's the thing that I actually wanted to talk about. So proceeding with that, IBM just announced that they are tripling their entry-level hiring, right? So IBM came out and said that they're tripling their entry-level hiring at their company. And here's why it matters. Because this is the same IBM that everyone was pointing to a year or two ago as proof that AI was killing jobs. They paused some hirings. The headlines went crazy. Everyone said it's over. Entry-level hiring is dead. AI is replacing everyone. Well, IBM actually did the work. They didn't just talk about AI on a stage. They implemented it across their operations and they saw what it could do and what it could not. And they came back and said that they found the limits of AI adoption, their actual words. And their response wasn't just to keep cutting people. Their response was to be humble and say, hey, they made mistakes and now they are tripling their entry-level hiring. So all the roles that they said that they were going away, they never went away. And their head of HR realized that if you cut your junior pipeline today, you'll We'll have no mid-level talent in 3 years. She said that companies that win in 3 to 5 years from now are the ones that are gonna be doubling down on hiring in this environment, not the ones panicking. And then you have the opposite side of the coin, right? Let's see what happens when a company ignores all of this, right? So let's talk about Salesforce. So their CEO gets on stage last September and doesn't just announce layoffs, he brags about them basically firing thousands of people as a marketing moment and framing it as proof that their AI product actually works. And then 3 months later, he comes back and says, basically that AI had reliability issues and that they regret their decisions. 4,000 people laid off just all for a talking point at some conference. And here's a part that I don't think anyone's like actually talking about when it comes down to AI. It's too much of like the rainbows and, you know, butterflies and good stuff about AI, but not too much on the other side of it, right? Right now there's like folks like lawyers making more money than ever, not because the legal market is necessarily booming, but because they're making money cleaning up the mess, um, from folks who use ChatGPT as their Right? You know, real cases, real consequences. And now a real human professional gets paid more to fix those mistakes. So this is a pattern. So anytime we move fast and we skip the human and then try to make AI our pilot and not our copilot, we're going to get mistakes. And when someone, whether it's a lawyer, a data scientist, whoever, we're actually going to be more in demand to clean that up, as we can see from, you know, IBM. But here's something I want to talk about that also is not really talked about, right? Because if we stop and think about this whole AI panic, like, where is it really coming from? Who has been the loudest voice telling us that AI is coming for our career? Who's been flooding the LinkedIn, every news article, every tech conference about this idea that humans are obsolete? It is the people who built the AI, right? The CEOs selling ChatGPT, Gemini, Claude, right? The investors backing those companies. Their incentive is not to give us the accurate picture of the job market. Their incentive is for companies to buy in and integrate as fast as possible. Fear is a great sales strategy, AI replace your workforce. That's a compelling selling pitch to a CFO looking to cut costs. And a significant portion of the panic that you felt about your career over the last 2+ years has been manufactured by people who profit from it. So it's not a conspiracy, that's just understanding the incentives. So if I sell hammers, I'm going to tell you everything looks like a nail. But let me be specific now, because I do coach data analysts and aspiring analysts, and I'm going to talk directly to us now. Are we cooked? Are data analysts cooked? In my opinion, absolutely not. I don't say that to just make you feel better. I say that because that's actually what I am seeing in the market with companies and people that I work with every day. Now, if you're a software engineer, on the other hand, that's a different conversation, right? Things like Lovable and things like that, that role is definitely being disrupted. That role, of all the tech roles, that's probably had the most disruption due to AI, right? But for analytics, We are good. The job market in AI, they're looking for people who can think, right? So I'm in groups, I'm seeing how business owners and data professionals, senior level managements, how they're using AI every day. No one's getting replaced, right? Just, just a sec. No one's getting replaced. They're using things to speed things up. I wanted to share this article I recently found past couple days. IBM is tripling the number of Gen Z entry-level jobs after finding the limitations of AI adoption. This is just the beginning of the shift when it comes down to this. The fallacy of like, oh my goodness, AI is taking all the jobs, taking like white-collar jobs. Understand a lot of it honestly has been like if you actually think about like who's been saying it a lot, I've been hearing it from what, like folks from basically the creators of these generative AI products, right? Like the ChatGPTs, the, the, like obviously the incentive For folks who run ChatGPT, Claude, Gemini, or whatever, all these, you know, AI products, and anyone who has like these like AI products, right? Their incentive is for, you know, companies to buy them and to integrate them and to use them more. And so there's just a lot of like propaganda in that type of stuff, to be honest with you. I'm seeing how other folks are like utilizing AI and things like that. And it's not in a way that's honestly that's going to be taking people's jobs, in my opinion, especially in terms of like us as like analysts and data. Or whatever like that, there's nothing to worry about at all. And this article, which I'm going to share about IBM tripling the number of— they say Gen Z entry-level jobs because there's been a whole lot of stuff about like, oh, entry-level jobs are kind of shrinking. In my opinion, entry-level jobs are— they just look different now. So whether it's even with like adding more jobs in the market for like entry-level, whatever, entry-level is still a— it still looks different than it did Pre-AI also goes into like, hey, the standard of what good looks like in terms of, or the standard of what qualified looks like, even for entry level, whatever it is, it's just a standard of what qualified looks like for any job across the board is just higher than it is now than it was 6 years ago, whatever it is. When it comes down to AI's impact on the job market, replacing jobs, or at least data analysts, right? We're just going to focus on data analysts. Software engineers, in my opinion, that's a completely different story. There's anyone who's probably more cooked except for the software engineers, but we're not software engineers, so we're good. But when it comes down to like data analytics, whether folks want to end up being like grow into data engineering, analytics engineering, whatever it is, we are good to go. We ain't got nothing to work— honestly, we really don't, right? But the big thing here is limits of finding the limits of AI adoption. There's so many limits when it comes down to AI adoption. Any company or anything that tries to make you sell or selling this idea that you can just allow AI to be— and as great as AI is, right, there are certain things that's just really good, like research, for example, right? If I wanted to do research on an industry, if I wanted to learn about, man, what, what are the, like, you know, big high-value problems in supply chain, and I want to do a project on that, using AI to you know, Gemini Deep Research or whatever to just like synthesize information. That is what it's really good for. But when it comes down to what to do with that information, you still need a human, right? You don't want AI to— you don't want AI. But when it comes down to like collecting information, synthesizing things like that, just to make it quicker for strategy, that's where we come in. It just saves us more time. It's not replacing anything. It's saving us more time. So for folks who don't want to be strategic or don't want to learn strategic thinking or that stuff like that, they're more cooked than anything. When you have time, like, I don't know if y'all have Saturdays or Sundays. I know for me Saturdays is usually my days of like shutting off and kind of like doing nothing per se and doing more mindless scrolling on the internet. There's like a lot of like vibe coding and AI, like, you know, horror stories on Reddit. So like the one that we shared today in the Slack, like there's multiple, there's a lot of those, you know, always like take some time to like look at like all the sides of AI adoption. It's not all sunshine and rainbows. There's a lot of stuff that is wrong. I even saw— not to get sidetracked— I even saw there's, uh, like lawyers, for example. Like, there's a lot— like, lawyers ain't going anywhere, right? There was a post that I saw about someone who said that, who was a lawyer or attorney, who said that she's gotten a lot more money just from people who think that ChatGPT is like A good replacement of a lawyer because she's had to, I guess, like clean things up or whatever. So there's like— anyways, that's the gist. Let me end off with just talking about and reminding you what AI is actually good for: acceleration, automating the boring stuff so you can focus on, you know, more strategic thinking, using it as your co-pilot. Remember that you are still the pilot. What AI is not good for, obviously, is replacing judgment. Remember, it hallucinates, it makes things up. So remember to never use AI as your pilot. You are always the pilot. AI is your copilot and nothing more. Again, men lie, women lie, and AI lies too, but the work that we put in doesn't. And so right now, that's the only currency that actually counts.
